id	sid	tid	token	lemma	pos
cjfa-8193	1	1	copernican	copernican	PROPN
cjfa-8193	1	2	journal	journal	PROPN
cjfa-8193	1	3	of	of	ADP
cjfa-8193	1	4	finance	finance	PROPN
cjfa-8193	1	5	&	&	CCONJ
cjfa-8193	1	6	accounting	accounting	PROPN
cjfa-8193	1	7	e	e	PROPN
cjfa-8193	1	8	-	-	PROPN
cjfa-8193	1	9	issn	issn	PROPN
cjfa-8193	1	10	2300	2300	NUM
cjfa-8193	1	11	-	-	SYM
cjfa-8193	1	12	3065	3065	NUM
cjfa-8193	1	13	p	p	PROPN
cjfa-8193	1	14	-	-	PUNCT
cjfa-8193	1	15	issn	issn	PROPN
cjfa-8193	1	16	2300	2300	NUM
cjfa-8193	1	17	-	-	SYM
cjfa-8193	1	18	12402015	12402015	NUM
cjfa-8193	1	19	,	,	PUNCT
cjfa-8193	1	20	volume	volume	NOUN
cjfa-8193	1	21	4	4	NUM
cjfa-8193	1	22	,	,	PUNCT
cjfa-8193	1	23	issue	issue	NOUN
cjfa-8193	1	24	2	2	NUM
cjfa-8193	1	25	date	date	NOUN
cjfa-8193	1	26	of	of	ADP
cjfa-8193	1	27	submission	submission	NOUN
cjfa-8193	1	28	:	:	PUNCT
cjfa-8193	1	29	may	may	AUX
cjfa-8193	1	30	16	16	NUM
cjfa-8193	1	31	,	,	PUNCT
cjfa-8193	1	32	2015	2015	NUM
cjfa-8193	1	33	;	;	PUNCT
cjfa-8193	1	34	date	date	NOUN
cjfa-8193	1	35	of	of	ADP
cjfa-8193	1	36	acceptance	acceptance	NOUN
cjfa-8193	1	37	:	:	PUNCT
cjfa-8193	1	38	october	october	PROPN
cjfa-8193	1	39	26	26	NUM
cjfa-8193	1	40	,	,	PUNCT
cjfa-8193	1	41	2015	2015	NUM
cjfa-8193	1	42	.	.	PUNCT
cjfa-8193	2	1	*	*	PUNCT
cjfa-8193	2	2	contact	contact	NOUN
cjfa-8193	2	3	information	information	NOUN
cjfa-8193	2	4	:	:	PUNCT
cjfa-8193	2	5	haawadh@kau.edu.sa	haawadh@kau.edu.sa	PROPN
cjfa-8193	2	6	,	,	PUNCT
cjfa-8193	2	7	department	department	NOUN
cjfa-8193	2	8	of	of	ADP
cjfa-8193	2	9	finance	finance	NOUN
cjfa-8193	2	10	,	,	PUNCT
cjfa-8193	2	11	king	king	PROPN
cjfa-8193	2	12	abdulaziz	abdulaziz	PROPN
cjfa-8193	2	13	university	university	PROPN
cjfa-8193	2	14	,	,	PUNCT
cjfa-8193	2	15	abdullah	abdullah	PROPN
cjfa-8193	2	16	sulayman	sulayman	PROPN
cjfa-8193	2	17	,	,	PUNCT
cjfa-8193	2	18	jeddah	jeddah	PROPN
cjfa-8193	2	19	21589	21589	NUM
cjfa-8193	2	20	,	,	PUNCT
cjfa-8193	2	21	saudi	saudi	PROPN
cjfa-8193	2	22	arabia	arabia	PROPN
cjfa-8193	2	23	,	,	PUNCT
cjfa-8193	2	24	phone	phone	NOUN
cjfa-8193	2	25	:	:	PUNCT
cjfa-8193	3	1	+966	+966	X
cjfa-8193	3	2	2	2	NUM
cjfa-8193	3	3	695	695	NUM
cjfa-8193	3	4	2000	2000	NUM
cjfa-8193	3	5	.	.	PUNCT
cjfa-8193	4	1	*	*	PUNCT
cjfa-8193	4	2	*	*	PUNCT
cjfa-8193	4	3	contact	contact	NOUN
cjfa-8193	4	4	information	information	NOUN
cjfa-8193	4	5	:	:	PUNCT
cjfa-8193	4	6	halnemer@kau.edu.sa	halnemer@kau.edu.sa	PROPN
cjfa-8193	4	7	,	,	PUNCT
cjfa-8193	4	8	department	department	NOUN
cjfa-8193	4	9	of	of	ADP
cjfa-8193	4	10	finance	finance	NOUN
cjfa-8193	4	11	and	and	CCONJ
cjfa-8193	4	12	insurance	insurance	NOUN
cjfa-8193	4	13	,	,	PUNCT
cjfa-8193	4	14	university	university	NOUN
cjfa-8193	4	15	of	of	ADP
cjfa-8193	4	16	jeddah	jeddah	PROPN
cjfa-8193	4	17	,	,	PUNCT
cjfa-8193	4	18	saudi	saudi	PROPN
cjfa-8193	4	19	arabia	arabia	PROPN
cjfa-8193	4	20	.	.	PUNCT
cjfa-8193	5	1	*	*	PUNCT
cjfa-8193	5	2	*	*	PUNCT
cjfa-8193	5	3	*	*	PUNCT
cjfa-8193	5	4	contact	contact	NOUN
cjfa-8193	5	5	information	information	NOUN
cjfa-8193	5	6	:	:	PUNCT
cjfa-8193	5	7	t.rodgers@coventry.ac.uk	t.rodgers@coventry.ac.uk	NUM
cjfa-8193	5	8	,	,	PUNCT
cjfa-8193	5	9	school	school	NOUN
cjfa-8193	5	10	of	of	ADP
cjfa-8193	5	11	economics	economic	NOUN
cjfa-8193	5	12	,	,	PUNCT
cjfa-8193	5	13	finance	finance	NOUN
cjfa-8193	5	14	and	and	CCONJ
cjfa-8193	5	15	accounting	accounting	NOUN
cjfa-8193	5	16	,	,	PUNCT
cjfa-8193	5	17	coventry	coventry	PROPN
cjfa-8193	5	18	university	university	PROPN
cjfa-8193	5	19	,	,	PUNCT
cjfa-8193	5	20	uk	uk	PROPN
cjfa-8193	5	21	.	.	PUNCT
cjfa-8193	6	1	*	*	PUNCT
cjfa-8193	6	2	*	*	PUNCT
cjfa-8193	6	3	*	*	PUNCT
cjfa-8193	6	4	*	*	PUNCT
cjfa-8193	6	5	contact	contact	NOUN
cjfa-8193	6	6	information	information	NOUN
cjfa-8193	6	7	:	:	PUNCT
cjfa-8193	7	1	j.niklewski@coventry.ac.uk	j.niklewski@coventry.ac.uk	ADJ
cjfa-8193	7	2	,	,	PUNCT
cjfa-8193	7	3	school	school	NOUN
cjfa-8193	7	4	of	of	ADP
cjfa-8193	7	5	economics	economic	NOUN
cjfa-8193	7	6	,	,	PUNCT
cjfa-8193	7	7	finance	finance	NOUN
cjfa-8193	7	8	and	and	CCONJ
cjfa-8193	7	9	accounting	accounting	NOUN
cjfa-8193	7	10	,	,	PUNCT
cjfa-8193	7	11	coventry	coventry	PROPN
cjfa-8193	7	12	university	university	PROPN
cjfa-8193	7	13	,	,	PUNCT
cjfa-8193	7	14	uk	uk	PROPN
cjfa-8193	7	15	.	.	PROPN
cjfa-8193	7	16	al	al	PROPN
cjfa-8193	7	17	-	-	PUNCT
cjfa-8193	7	18	hajieh	hajieh	PROPN
cjfa-8193	7	19	h.	h.	PROPN
cjfa-8193	7	20	,	,	PUNCT
cjfa-8193	7	21	alnemer	alnemer	PROPN
cjfa-8193	7	22	h.	h.	PROPN
cjfa-8193	7	23	,	,	PUNCT
cjfa-8193	7	24	rodgers	rodger	VERB
cjfa-8193	7	25	t.	t.	PROPN
cjfa-8193	7	26	,	,	PUNCT
cjfa-8193	7	27	&	&	CCONJ
cjfa-8193	7	28	niklewski	niklewski	PROPN
cjfa-8193	7	29	j.	j.	PROPN
cjfa-8193	7	30	(	(	PUNCT
cjfa-8193	7	31	2015	2015	NUM
cjfa-8193	7	32	)	)	PUNCT
cjfa-8193	7	33	.	.	PUNCT
cjfa-8193	8	1	forecasting	forecast	VERB
cjfa-8193	8	2	the	the	DET
cjfa-8193	8	3	jordanian	jordanian	ADJ
cjfa-8193	8	4	stock	stock	NOUN
cjfa-8193	8	5	index	index	PROPN
cjfa-8193	8	6	:	:	PUNCT
cjfa-8193	8	7	modelling	model	VERB
cjfa-8193	8	8	asymmetric	asymmetric	ADJ
cjfa-8193	8	9	volatility	volatility	NOUN
cjfa-8193	8	10	and	and	CCONJ
cjfa-8193	8	11	distribution	distribution	NOUN
cjfa-8193	8	12	effects	effect	NOUN
cjfa-8193	8	13	within	within	ADP
cjfa-8193	8	14	a	a	DET
cjfa-8193	8	15	garch	garch	NOUN
cjfa-8193	8	16	framework	framework	NOUN
cjfa-8193	8	17	.	.	PUNCT
cjfa-8193	9	1	copernican	copernican	PROPN
cjfa-8193	9	2	journal	journal	PROPN
cjfa-8193	9	3	of	of	ADP
cjfa-8193	9	4	finance	finance	PROPN
cjfa-8193	9	5	&	&	CCONJ
cjfa-8193	9	6	accounting	accounting	PROPN
cjfa-8193	9	7	,	,	PUNCT
cjfa-8193	9	8	4(2	4(2	NUM
cjfa-8193	9	9	)	)	PUNCT
cjfa-8193	9	10	,	,	PUNCT
cjfa-8193	9	11	9–26	9–26	NOUN
cjfa-8193	9	12	.	.	PUNCT
cjfa-8193	10	1	http://dx.doi.org/10.12775/cjfa.2015.013	http://dx.doi.org/10.12775/cjfa.2015.013	X
cjfa-8193	11	1	heitham	heitham	PROPN
cjfa-8193	11	2	al	al	PROPN
cjfa-8193	11	3	-	-	PUNCT
cjfa-8193	11	4	hajieh	hajieh	PROPN
cjfa-8193	11	5	*	*	PROPN
cjfa-8193	11	6	department	department	PROPN
cjfa-8193	11	7	of	of	ADP
cjfa-8193	11	8	finance	finance	NOUN
cjfa-8193	11	9	,	,	PUNCT
cjfa-8193	11	10	king	king	PROPN
cjfa-8193	11	11	abdulaziz	abdulaziz	PROPN
cjfa-8193	11	12	university	university	PROPN
cjfa-8193	11	13	,	,	PUNCT
cjfa-8193	11	14	saudi	saudi	PROPN
cjfa-8193	11	15	arabia	arabia	PROPN
cjfa-8193	11	16	hashem	hashem	PROPN
cjfa-8193	12	1	alnemer	alnemer	PROPN
cjfa-8193	12	2	*	*	PROPN
cjfa-8193	12	3	*	*	PROPN
cjfa-8193	12	4	department	department	PROPN
cjfa-8193	12	5	of	of	ADP
cjfa-8193	12	6	finance	finance	NOUN
cjfa-8193	12	7	and	and	CCONJ
cjfa-8193	12	8	insurance	insurance	NOUN
cjfa-8193	12	9	,	,	PUNCT
cjfa-8193	12	10	university	university	NOUN
cjfa-8193	12	11	of	of	ADP
cjfa-8193	12	12	jeddah	jeddah	PROPN
cjfa-8193	12	13	,	,	PUNCT
cjfa-8193	12	14	saudi	saudi	PROPN
cjfa-8193	12	15	arabia	arabia	PROPN
cjfa-8193	12	16	timothy	timothy	PROPN
cjfa-8193	12	17	rodgers	rodger	VERB
cjfa-8193	12	18	*	*	PROPN
cjfa-8193	12	19	*	*	PROPN
cjfa-8193	12	20	*	*	PUNCT
cjfa-8193	12	21	school	school	NOUN
cjfa-8193	12	22	of	of	ADP
cjfa-8193	12	23	economics	economic	NOUN
cjfa-8193	12	24	,	,	PUNCT
cjfa-8193	12	25	finance	finance	NOUN
cjfa-8193	12	26	and	and	CCONJ
cjfa-8193	12	27	accounting	accounting	NOUN
cjfa-8193	12	28	,	,	PUNCT
cjfa-8193	12	29	coventry	coventry	NOUN
cjfa-8193	12	30	university	university	PROPN
cjfa-8193	12	31	,	,	PUNCT
cjfa-8193	12	32	uk	uk	PROPN
cjfa-8193	12	33	jacek	jacek	PROPN
cjfa-8193	12	34	niklewski	niklewski	PROPN
cjfa-8193	12	35	*	*	PROPN
cjfa-8193	12	36	*	*	PUNCT
cjfa-8193	12	37	*	*	PUNCT
cjfa-8193	12	38	*	*	PUNCT
cjfa-8193	12	39	school	school	NOUN
cjfa-8193	12	40	of	of	ADP
cjfa-8193	12	41	economics	economic	NOUN
cjfa-8193	12	42	,	,	PUNCT
cjfa-8193	12	43	finance	finance	NOUN
cjfa-8193	12	44	and	and	CCONJ
cjfa-8193	12	45	accounting	accounting	NOUN
cjfa-8193	12	46	,	,	PUNCT
cjfa-8193	12	47	coventry	coventry	PROPN
cjfa-8193	12	48	university	university	PROPN
cjfa-8193	12	49	,	,	PUNCT
cjfa-8193	12	50	uk	uk	PROPN
cjfa-8193	12	51	forecasting	forecast	VERB
cjfa-8193	12	52	the	the	DET
cjfa-8193	12	53	jordanian	jordanian	ADJ
cjfa-8193	12	54	stock	stock	NOUN
cjfa-8193	12	55	index	index	PROPN
cjfa-8193	12	56	:	:	PUNCT
cjfa-8193	12	57	modelling	model	VERB
cjfa-8193	12	58	asymmetric	asymmetric	ADJ
cjfa-8193	12	59	volatility	volatility	NOUN
cjfa-8193	12	60	and	and	CCONJ
cjfa-8193	12	61	distribution	distribution	NOUN
cjfa-8193	12	62	effects	effect	NOUN
cjfa-8193	12	63	within	within	ADP
cjfa-8193	12	64	a	a	DET
cjfa-8193	12	65	garch	garch	NOUN
cjfa-8193	12	66	framework	framework	NOUN
cjfa-8193	12	67	keywords	keyword	NOUN
cjfa-8193	12	68	:	:	PUNCT
cjfa-8193	12	69	garch	garch	NOUN
cjfa-8193	12	70	,	,	PUNCT
cjfa-8193	12	71	asymmetry	asymmetry	NOUN
cjfa-8193	12	72	,	,	PUNCT
cjfa-8193	12	73	distributions	distribution	NOUN
cjfa-8193	12	74	.	.	PUNCT
cjfa-8193	13	1	j	j	PROPN
cjfa-8193	13	2	e	e	PROPN
cjfa-8193	13	3	l	l	PROPN
cjfa-8193	13	4	classification	classification	NOUN
cjfa-8193	13	5	:	:	PUNCT
cjfa-8193	13	6	c01	c01	PROPN
cjfa-8193	13	7	,	,	PUNCT
cjfa-8193	13	8	c58	c58	PROPN
cjfa-8193	13	9	,	,	PUNCT
cjfa-8193	13	10	g15	g15	PROPN
cjfa-8193	13	11	.	.	PUNCT
cjfa-8193	14	1	h.	h.	PROPN
cjfa-8193	14	2	al	al	PROPN
cjfa-8193	14	3	-	-	PUNCT
cjfa-8193	14	4	hajieh	hajieh	PROPN
cjfa-8193	14	5	,	,	PUNCT
cjfa-8193	14	6	h.	h.	PROPN
cjfa-8193	14	7	alnemer	alnemer	PROPN
cjfa-8193	14	8	,	,	PUNCT
cjfa-8193	14	9	t.	t.	PROPN
cjfa-8193	14	10	rodgers	rodgers	PROPN
cjfa-8193	14	11	,	,	PUNCT
cjfa-8193	14	12	j.	j.	PROPN
cjfa-8193	14	13	niklewski10	niklewski10	PROPN
cjfa-8193	14	14	abstract	abstract	PROPN
cjfa-8193	14	15	:	:	PUNCT
cjfa-8193	14	16	the	the	DET
cjfa-8193	14	17	modelling	modelling	NOUN
cjfa-8193	14	18	of	of	ADP
cjfa-8193	14	19	market	market	NOUN
cjfa-8193	14	20	returns	return	NOUN
cjfa-8193	14	21	can	can	AUX
cjfa-8193	14	22	be	be	AUX
cjfa-8193	14	23	especially	especially	ADV
cjfa-8193	14	24	problematical	problematical	ADJ
cjfa-8193	14	25	in	in	ADP
cjfa-8193	14	26	emerging	emerge	VERB
cjfa-8193	14	27	and	and	CCONJ
cjfa-8193	14	28	frontier	frontier	NOUN
cjfa-8193	14	29	financial	financial	ADJ
cjfa-8193	14	30	markets	market	NOUN
cjfa-8193	14	31	given	give	VERB
cjfa-8193	14	32	the	the	DET
cjfa-8193	14	33	propensity	propensity	NOUN
cjfa-8193	14	34	of	of	ADP
cjfa-8193	14	35	their	their	PRON
cjfa-8193	14	36	returns	return	NOUN
cjfa-8193	14	37	to	to	PART
cjfa-8193	14	38	exhibit	exhibit	VERB
cjfa-8193	14	39	significant	significant	ADJ
cjfa-8193	14	40	non	non	ADJ
cjfa-8193	14	41	-	-	ADJ
cjfa-8193	14	42	normality	normality	ADJ
cjfa-8193	14	43	and	and	CCONJ
cjfa-8193	14	44	volatility	volatility	NOUN
cjfa-8193	14	45	asymmetries	asymmetry	NOUN
cjfa-8193	14	46	.	.	PUNCT
cjfa-8193	15	1	this	this	DET
cjfa-8193	15	2	paper	paper	NOUN
cjfa-8193	15	3	attempts	attempt	VERB
cjfa-8193	15	4	to	to	PART
cjfa-8193	15	5	identify	identify	VERB
cjfa-8193	15	6	which	which	PRON
cjfa-8193	15	7	representations	representation	VERB
cjfa-8193	15	8	within	within	ADP
cjfa-8193	15	9	the	the	DET
cjfa-8193	15	10	garch	garch	NOUN
cjfa-8193	15	11	family	family	NOUN
cjfa-8193	15	12	of	of	ADP
cjfa-8193	15	13	models	model	NOUN
cjfa-8193	15	14	can	can	AUX
cjfa-8193	15	15	most	most	ADV
cjfa-8193	15	16	efficiently	efficiently	ADV
cjfa-8193	15	17	deal	deal	VERB
cjfa-8193	15	18	with	with	ADP
cjfa-8193	15	19	these	these	DET
cjfa-8193	15	20	issues	issue	NOUN
cjfa-8193	15	21	.	.	PUNCT
cjfa-8193	16	1	a	a	DET
cjfa-8193	16	2	number	number	NOUN
cjfa-8193	16	3	of	of	ADP
cjfa-8193	16	4	different	different	ADJ
cjfa-8193	16	5	distributions	distribution	NOUN
cjfa-8193	16	6	(	(	PUNCT
cjfa-8193	16	7	normal	normal	ADJ
cjfa-8193	16	8	,	,	PUNCT
cjfa-8193	16	9	student	student	NOUN
cjfa-8193	16	10	t	t	PROPN
cjfa-8193	16	11	,	,	PUNCT
cjfa-8193	16	12	ged	ge	VERB
cjfa-8193	16	13	and	and	CCONJ
cjfa-8193	16	14	skewed	skewed	ADJ
cjfa-8193	16	15	student	student	NOUN
cjfa-8193	16	16	)	)	PUNCT
cjfa-8193	16	17	and	and	CCONJ
cjfa-8193	16	18	different	different	ADJ
cjfa-8193	16	19	volatility	volatility	NOUN
cjfa-8193	16	20	of	of	ADP
cjfa-8193	16	21	returns	return	NOUN
cjfa-8193	16	22	asymmetry	asymmetry	VERB
cjfa-8193	16	23	representations	representation	NOUN
cjfa-8193	16	24	(	(	PUNCT
cjfa-8193	16	25	egarch	egarch	NOUN
cjfa-8193	16	26	and	and	CCONJ
cjfa-8193	16	27	gjr	gjr	NOUN
cjfa-8193	16	28	-	-	PUNCT
cjfa-8193	16	29	garch	garch	NOUN
cjfa-8193	16	30	)	)	PUNCT
cjfa-8193	16	31	are	be	AUX
cjfa-8193	16	32	examined	examine	VERB
cjfa-8193	16	33	.	.	PUNCT
cjfa-8193	17	1	our	our	PRON
cjfa-8193	17	2	data	datum	NOUN
cjfa-8193	17	3	set	set	VERB
cjfa-8193	17	4	consists	consist	NOUN
cjfa-8193	17	5	of	of	ADP
cjfa-8193	17	6	daily	daily	ADJ
cjfa-8193	17	7	jordanian	jordanian	ADJ
cjfa-8193	17	8	stock	stock	NOUN
cjfa-8193	17	9	market	market	NOUN
cjfa-8193	17	10	returns	return	NOUN
cjfa-8193	17	11	over	over	ADP
cjfa-8193	17	12	the	the	DET
cjfa-8193	17	13	period	period	NOUN
cjfa-8193	17	14	january	january	PROPN
cjfa-8193	17	15	2000	2000	NUM
cjfa-8193	17	16	–	–	PUNCT
cjfa-8193	17	17	november	november	PROPN
cjfa-8193	17	18	2014	2014	NUM
cjfa-8193	17	19	.	.	PUNCT
cjfa-8193	18	1	using	use	VERB
cjfa-8193	18	2	both	both	CCONJ
cjfa-8193	18	3	the	the	DET
cjfa-8193	18	4	superior	superior	ADJ
cjfa-8193	18	5	predicative	predicative	ADJ
cjfa-8193	18	6	ability	ability	NOUN
cjfa-8193	18	7	(	(	PUNCT
cjfa-8193	18	8	spa	spa	NOUN
cjfa-8193	18	9	)	)	PUNCT
cjfa-8193	18	10	and	and	CCONJ
cjfa-8193	18	11	model	model	NOUN
cjfa-8193	18	12	confidence	confidence	NOUN
cjfa-8193	18	13	set	set	NOUN
cjfa-8193	18	14	(	(	PUNCT
cjfa-8193	18	15	mcs	mcs	NOUN
cjfa-8193	18	16	)	)	PUNCT
cjfa-8193	18	17	testing	testing	NOUN
cjfa-8193	18	18	frameworks	framework	NOUN
cjfa-8193	18	19	it	it	PRON
cjfa-8193	18	20	is	be	AUX
cjfa-8193	18	21	found	find	VERB
cjfa-8193	18	22	that	that	SCONJ
cjfa-8193	18	23	using	use	VERB
cjfa-8193	18	24	gjr	gjr	NOUN
cjfa-8193	18	25	-	-	PUNCT
cjfa-8193	18	26	garch	garch	NOUN
cjfa-8193	18	27	with	with	ADP
cjfa-8193	18	28	a	a	DET
cjfa-8193	18	29	skewed	skewed	ADJ
cjfa-8193	18	30	student	student	NOUN
cjfa-8193	18	31	distribution	distribution	NOUN
cjfa-8193	18	32	most	most	ADV
cjfa-8193	18	33	accurately	accurately	ADV
cjfa-8193	18	34	and	and	CCONJ
cjfa-8193	18	35	efficiently	efficiently	ADV
cjfa-8193	18	36	forecasts	forecast	VERB
cjfa-8193	18	37	jordanian	jordanian	ADJ
cjfa-8193	18	38	market	market	NOUN
cjfa-8193	18	39	movements	movement	NOUN
cjfa-8193	18	40	.	.	PUNCT
cjfa-8193	19	1	our	our	PRON
cjfa-8193	19	2	findings	finding	NOUN
cjfa-8193	19	3	are	be	AUX
cjfa-8193	19	4	consistent	consistent	ADJ
cjfa-8193	19	5	with	with	ADP
cjfa-8193	19	6	similar	similar	ADJ
cjfa-8193	19	7	research	research	NOUN
cjfa-8193	19	8	undertaken	undertake	VERB
cjfa-8193	19	9	in	in	ADP
cjfa-8193	19	10	respect	respect	NOUN
cjfa-8193	19	11	to	to	ADP
cjfa-8193	19	12	developed	develop	VERB
cjfa-8193	19	13	markets	market	NOUN
cjfa-8193	19	14	.	.	PUNCT
cjfa-8193	19	15	 	 	SPACE
cjfa-8193	20	1	introduction	introduction	NOUN
cjfa-8193	20	2	the	the	DET
cjfa-8193	20	3	global	global	ADJ
cjfa-8193	20	4	financial	financial	ADJ
cjfa-8193	20	5	crisis	crisis	NOUN
cjfa-8193	20	6	of	of	ADP
cjfa-8193	20	7	2007	2007	NUM
cjfa-8193	20	8	-	-	SYM
cjfa-8193	20	9	09	09	NUM
cjfa-8193	20	10	and	and	CCONJ
cjfa-8193	20	11	subsequent	subsequent	ADJ
cjfa-8193	20	12	shocks	shock	NOUN
cjfa-8193	20	13	in	in	ADP
cjfa-8193	20	14	the	the	DET
cjfa-8193	20	15	euro	euro	NOUN
cjfa-8193	20	16	-	-	PUNCT
cjfa-8193	20	17	area	area	NOUN
cjfa-8193	20	18	and	and	CCONJ
cjfa-8193	20	19	beyond	beyond	NOUN
cjfa-8193	20	20	has	have	AUX
cjfa-8193	20	21	led	lead	VERB
cjfa-8193	20	22	researchers	researcher	NOUN
cjfa-8193	20	23	to	to	PART
cjfa-8193	20	24	examine	examine	VERB
cjfa-8193	20	25	again	again	ADV
cjfa-8193	20	26	the	the	DET
cjfa-8193	20	27	ways	way	NOUN
cjfa-8193	20	28	in	in	ADP
cjfa-8193	20	29	which	which	PRON
cjfa-8193	20	30	they	they	PRON
cjfa-8193	20	31	model	model	VERB
cjfa-8193	20	32	stock	stock	NOUN
cjfa-8193	20	33	market	market	NOUN
cjfa-8193	20	34	returns	return	NOUN
cjfa-8193	20	35	.	.	PUNCT
cjfa-8193	21	1	it	it	PRON
cjfa-8193	21	2	has	have	AUX
cjfa-8193	21	3	become	become	VERB
cjfa-8193	21	4	increasingly	increasingly	ADV
cjfa-8193	21	5	apparent	apparent	ADJ
cjfa-8193	21	6	that	that	SCONJ
cjfa-8193	21	7	the	the	DET
cjfa-8193	21	8	‘	'	PUNCT
cjfa-8193	21	9	standard	standard	ADJ
cjfa-8193	21	10	assumptions	assumption	NOUN
cjfa-8193	21	11	’	'	PUNCT
cjfa-8193	21	12	made	make	VERB
cjfa-8193	21	13	in	in	ADP
cjfa-8193	21	14	respect	respect	NOUN
cjfa-8193	21	15	to	to	ADP
cjfa-8193	21	16	the	the	DET
cjfa-8193	21	17	ways	way	NOUN
cjfa-8193	21	18	in	in	ADP
cjfa-8193	21	19	which	which	PRON
cjfa-8193	21	20	statistical	statistical	ADJ
cjfa-8193	21	21	series	series	NOUN
cjfa-8193	21	22	are	be	AUX
cjfa-8193	21	23	distributed	distribute	VERB
cjfa-8193	21	24	are	be	AUX
cjfa-8193	21	25	not	not	PART
cjfa-8193	21	26	applicable	applicable	ADJ
cjfa-8193	21	27	in	in	ADP
cjfa-8193	21	28	financial	financial	ADJ
cjfa-8193	21	29	markets	market	NOUN
cjfa-8193	21	30	.	.	PUNCT
cjfa-8193	22	1	as	as	SCONJ
cjfa-8193	22	2	the	the	DET
cjfa-8193	22	3	global	global	ADJ
cjfa-8193	22	4	economy	economy	NOUN
cjfa-8193	22	5	becomes	become	VERB
cjfa-8193	22	6	more	more	ADV
cjfa-8193	22	7	integrated	integrated	ADJ
cjfa-8193	22	8	it	it	PRON
cjfa-8193	22	9	is	be	AUX
cjfa-8193	22	10	also	also	ADV
cjfa-8193	22	11	becoming	become	VERB
cjfa-8193	22	12	increasingly	increasingly	ADV
cjfa-8193	22	13	important	important	ADJ
cjfa-8193	22	14	to	to	PART
cjfa-8193	22	15	understand	understand	VERB
cjfa-8193	22	16	how	how	SCONJ
cjfa-8193	22	17	emerging	emerging	ADJ
cjfa-8193	22	18	and	and	CCONJ
cjfa-8193	22	19	frontier	frontier	NOUN
cjfa-8193	22	20	markets	market	NOUN
cjfa-8193	22	21	react	react	VERB
cjfa-8193	22	22	in	in	ADP
cjfa-8193	22	23	periods	period	NOUN
cjfa-8193	22	24	of	of	ADP
cjfa-8193	22	25	high	high	ADJ
cjfa-8193	22	26	volatility	volatility	NOUN
cjfa-8193	22	27	.	.	PUNCT
cjfa-8193	23	1	in	in	ADP
cjfa-8193	23	2	this	this	DET
cjfa-8193	23	3	paper	paper	NOUN
cjfa-8193	23	4	we	we	PRON
cjfa-8193	23	5	explore	explore	VERB
cjfa-8193	23	6	which	which	DET
cjfa-8193	23	7	elements	element	NOUN
cjfa-8193	23	8	of	of	ADP
cjfa-8193	23	9	the	the	DET
cjfa-8193	23	10	garch	garch	NOUN
cjfa-8193	23	11	family	family	NOUN
cjfa-8193	23	12	of	of	ADP
cjfa-8193	23	13	models	model	NOUN
cjfa-8193	23	14	can	can	AUX
cjfa-8193	23	15	be	be	AUX
cjfa-8193	23	16	used	use	VERB
cjfa-8193	23	17	to	to	PART
cjfa-8193	23	18	efficiently	efficiently	ADV
cjfa-8193	23	19	and	and	CCONJ
cjfa-8193	23	20	effectively	effectively	ADV
cjfa-8193	23	21	model	model	NOUN
cjfa-8193	23	22	markets	market	NOUN
cjfa-8193	23	23	in	in	ADP
cjfa-8193	23	24	jordan	jordan	PROPN
cjfa-8193	23	25	from	from	ADP
cjfa-8193	23	26	january	january	PROPN
cjfa-8193	23	27	2000	2000	NUM
cjfa-8193	23	28	to	to	ADP
cjfa-8193	23	29	november	november	PROPN
cjfa-8193	23	30	2014	2014	NUM
cjfa-8193	23	31	.	.	PUNCT
cjfa-8193	24	1	the	the	DET
cjfa-8193	24	2	paper	paper	NOUN
cjfa-8193	24	3	begins	begin	VERB
cjfa-8193	24	4	with	with	ADP
cjfa-8193	24	5	a	a	DET
cjfa-8193	24	6	brief	brief	ADJ
cjfa-8193	24	7	review	review	NOUN
cjfa-8193	24	8	of	of	ADP
cjfa-8193	24	9	the	the	DET
cjfa-8193	24	10	literature	literature	NOUN
cjfa-8193	24	11	in	in	ADP
cjfa-8193	24	12	the	the	DET
cjfa-8193	24	13	second	second	ADJ
cjfa-8193	24	14	section	section	NOUN
cjfa-8193	24	15	.	.	PUNCT
cjfa-8193	25	1	this	this	PRON
cjfa-8193	25	2	is	be	AUX
cjfa-8193	25	3	followed	follow	VERB
cjfa-8193	25	4	in	in	ADP
cjfa-8193	25	5	the	the	DET
cjfa-8193	25	6	subsequent	subsequent	ADJ
cjfa-8193	25	7	section	section	NOUN
cjfa-8193	25	8	by	by	ADP
cjfa-8193	25	9	a	a	DET
cjfa-8193	25	10	description	description	NOUN
cjfa-8193	25	11	of	of	ADP
cjfa-8193	25	12	the	the	DET
cjfa-8193	25	13	data	datum	NOUN
cjfa-8193	25	14	and	and	CCONJ
cjfa-8193	25	15	methodology	methodology	NOUN
cjfa-8193	25	16	.	.	PUNCT
cjfa-8193	26	1	the	the	DET
cjfa-8193	26	2	most	most	ADV
cjfa-8193	26	3	efficient	efficient	ADJ
cjfa-8193	26	4	model	model	NOUN
cjfa-8193	26	5	is	be	AUX
cjfa-8193	26	6	then	then	ADV
cjfa-8193	26	7	identified	identify	VERB
cjfa-8193	26	8	using	use	VERB
cjfa-8193	26	9	the	the	DET
cjfa-8193	26	10	superior	superior	ADJ
cjfa-8193	26	11	predictive	predictive	ADJ
cjfa-8193	26	12	ability	ability	NOUN
cjfa-8193	26	13	(	(	PUNCT
cjfa-8193	26	14	spa	spa	NOUN
cjfa-8193	26	15	)	)	PUNCT
cjfa-8193	26	16	and	and	CCONJ
cjfa-8193	26	17	model	model	NOUN
cjfa-8193	26	18	confidence	confidence	NOUN
cjfa-8193	26	19	set	set	NOUN
cjfa-8193	26	20	(	(	PUNCT
cjfa-8193	26	21	mcs	mcs	NOUN
cjfa-8193	26	22	)	)	PUNCT
cjfa-8193	26	23	prediction	prediction	NOUN
cjfa-8193	26	24	frameworks	framework	NOUN
cjfa-8193	26	25	before	before	ADV
cjfa-8193	26	26	,	,	PUNCT
cjfa-8193	26	27	finally	finally	ADV
cjfa-8193	26	28	,	,	PUNCT
cjfa-8193	26	29	some	some	DET
cjfa-8193	26	30	brief	brief	ADJ
cjfa-8193	26	31	conclusions	conclusion	NOUN
cjfa-8193	26	32	are	be	AUX
cjfa-8193	26	33	drawn	draw	VERB
cjfa-8193	26	34	.	.	PUNCT
cjfa-8193	27	1	literature	literature	NOUN
cjfa-8193	27	2	:	:	PUNCT
cjfa-8193	27	3	volatility	volatility	NOUN
cjfa-8193	27	4	modelling	modelling	NOUN
cjfa-8193	27	5	in	in	ADP
cjfa-8193	27	6	the	the	DET
cjfa-8193	27	7	garch	garch	NOUN
cjfa-8193	27	8	framework	framework	NOUN
cjfa-8193	27	9	the	the	DET
cjfa-8193	27	10	garch	garch	NOUN
cjfa-8193	27	11	model	model	NOUN
cjfa-8193	27	12	was	be	AUX
cjfa-8193	27	13	first	first	ADV
cjfa-8193	27	14	introduced	introduce	VERB
cjfa-8193	27	15	by	by	ADP
cjfa-8193	27	16	bollerslev	bollerslev	ADJ
cjfa-8193	27	17	(	(	PUNCT
cjfa-8193	27	18	1986	1986	NUM
cjfa-8193	27	19	)	)	PUNCT
cjfa-8193	27	20	.	.	PUNCT
cjfa-8193	28	1	much	much	ADJ
cjfa-8193	28	2	of	of	ADP
cjfa-8193	28	3	the	the	DET
cjfa-8193	28	4	subsequent	subsequent	ADJ
cjfa-8193	28	5	research	research	NOUN
cjfa-8193	28	6	in	in	ADP
cjfa-8193	28	7	this	this	DET
cjfa-8193	28	8	area	area	NOUN
cjfa-8193	28	9	has	have	AUX
cjfa-8193	28	10	focused	focus	VERB
cjfa-8193	28	11	on	on	ADP
cjfa-8193	28	12	developing	develop	VERB
cjfa-8193	28	13	the	the	DET
cjfa-8193	28	14	model	model	NOUN
cjfa-8193	28	15	to	to	PART
cjfa-8193	28	16	better	well	ADV
cjfa-8193	28	17	reflect	reflect	VERB
cjfa-8193	28	18	the	the	DET
cjfa-8193	28	19	data	datum	NOUN
cjfa-8193	28	20	found	find	VERB
cjfa-8193	28	21	in	in	ADP
cjfa-8193	28	22	real	real	ADJ
cjfa-8193	28	23	-	-	PUNCT
cjfa-8193	28	24	world	world	NOUN
cjfa-8193	28	25	settings	setting	NOUN
cjfa-8193	28	26	,	,	PUNCT
cjfa-8193	28	27	such	such	ADJ
cjfa-8193	28	28	as	as	ADP
cjfa-8193	28	29	,	,	PUNCT
cjfa-8193	28	30	for	for	ADP
cjfa-8193	28	31	example	example	NOUN
cjfa-8193	28	32	,	,	PUNCT
cjfa-8193	28	33	financial	financial	ADJ
cjfa-8193	28	34	markets	market	NOUN
cjfa-8193	28	35	.	.	PUNCT
cjfa-8193	29	1	the	the	DET
cjfa-8193	29	2	finance	finance	NOUN
cjfa-8193	29	3	-	-	PUNCT
cjfa-8193	29	4	related	relate	VERB
cjfa-8193	29	5	literature	literature	NOUN
cjfa-8193	29	6	focuses	focus	VERB
cjfa-8193	29	7	principally	principally	ADV
cjfa-8193	29	8	on	on	ADP
cjfa-8193	29	9	modelling	modelling	NOUN
cjfa-8193	29	10	(	(	PUNCT
cjfa-8193	29	11	i	i	NOUN
cjfa-8193	29	12	)	)	PUNCT
cjfa-8193	29	13	the	the	DET
cjfa-8193	29	14	structure	structure	NOUN
cjfa-8193	29	15	of	of	ADP
cjfa-8193	29	16	the	the	DET
cjfa-8193	29	17	volatility	volatility	NOUN
cjfa-8193	29	18	(	(	PUNCT
cjfa-8193	29	19	ii	ii	NOUN
cjfa-8193	29	20	)	)	PUNCT
cjfa-8193	29	21	the	the	DET
cjfa-8193	29	22	nature	nature	NOUN
cjfa-8193	29	23	of	of	ADP
cjfa-8193	29	24	the	the	DET
cjfa-8193	29	25	distribution	distribution	NOUN
cjfa-8193	29	26	of	of	ADP
cjfa-8193	29	27	the	the	DET
cjfa-8193	29	28	returns	return	NOUN
cjfa-8193	29	29	.	.	PUNCT
cjfa-8193	30	1	forecasting	forecast	VERB
cjfa-8193	30	2	the	the	DET
cjfa-8193	30	3	jordanian	jordanian	ADJ
cjfa-8193	30	4	stock	stock	NOUN
cjfa-8193	30	5	index	index	PROPN
cjfa-8193	30	6	…	…	PUNCT
cjfa-8193	30	7	11	11	NUM
cjfa-8193	30	8	much	much	ADJ
cjfa-8193	30	9	of	of	ADP
cjfa-8193	30	10	the	the	DET
cjfa-8193	30	11	work	work	NOUN
cjfa-8193	30	12	on	on	ADP
cjfa-8193	30	13	modelling	model	VERB
cjfa-8193	30	14	the	the	DET
cjfa-8193	30	15	structure	structure	NOUN
cjfa-8193	30	16	of	of	ADP
cjfa-8193	30	17	volatility	volatility	NOUN
cjfa-8193	30	18	relates	relate	VERB
cjfa-8193	30	19	to	to	ADP
cjfa-8193	30	20	the	the	DET
cjfa-8193	30	21	asymmetries	asymmetry	NOUN
cjfa-8193	30	22	found	find	VERB
cjfa-8193	30	23	in	in	ADP
cjfa-8193	30	24	stock	stock	NOUN
cjfa-8193	30	25	market	market	NOUN
cjfa-8193	30	26	returns	return	NOUN
cjfa-8193	30	27	.	.	PUNCT
cjfa-8193	31	1	for	for	ADP
cjfa-8193	31	2	example	example	NOUN
cjfa-8193	31	3	,	,	PUNCT
cjfa-8193	31	4	engle	engle	PROPN
cjfa-8193	31	5	and	and	CCONJ
cjfa-8193	31	6	ng	ng	PROPN
cjfa-8193	31	7	(	(	PUNCT
cjfa-8193	31	8	1993	1993	NUM
cjfa-8193	31	9	)	)	PUNCT
cjfa-8193	31	10	found	find	VERB
cjfa-8193	31	11	evidence	evidence	NOUN
cjfa-8193	31	12	supporting	support	VERB
cjfa-8193	31	13	the	the	DET
cjfa-8193	31	14	quadratic	quadratic	ADJ
cjfa-8193	31	15	-	-	PUNCT
cjfa-8193	31	16	garch	garch	NOUN
cjfa-8193	31	17	model	model	NOUN
cjfa-8193	31	18	.	.	PUNCT
cjfa-8193	32	1	others	other	NOUN
cjfa-8193	32	2	,	,	PUNCT
cjfa-8193	32	3	such	such	ADJ
cjfa-8193	32	4	as	as	ADP
cjfa-8193	32	5	brailsford	brailsford	PROPN
cjfa-8193	32	6	and	and	CCONJ
cjfa-8193	32	7	faff	faff	PROPN
cjfa-8193	32	8	(	(	PUNCT
cjfa-8193	32	9	1996	1996	NUM
cjfa-8193	32	10	)	)	PUNCT
cjfa-8193	32	11	,	,	PUNCT
cjfa-8193	32	12	found	find	VERB
cjfa-8193	32	13	evidence	evidence	NOUN
cjfa-8193	32	14	to	to	PART
cjfa-8193	32	15	support	support	VERB
cjfa-8193	32	16	gjr	gjr	NOUN
cjfa-8193	32	17	-	-	PUNCT
cjfa-8193	32	18	garch	garch	NOUN
cjfa-8193	32	19	and	and	CCONJ
cjfa-8193	32	20	heynen	heynen	PROPN
cjfa-8193	32	21	and	and	CCONJ
cjfa-8193	32	22	kat	kat	PROPN
cjfa-8193	32	23	(	(	PUNCT
cjfa-8193	32	24	1994	1994	NUM
cjfa-8193	32	25	)	)	PUNCT
cjfa-8193	32	26	argued	argue	VERB
cjfa-8193	32	27	that	that	SCONJ
cjfa-8193	32	28	egarch	egarch	PROPN
cjfa-8193	32	29	has	have	VERB
cjfa-8193	32	30	a	a	DET
cjfa-8193	32	31	superior	superior	ADJ
cjfa-8193	32	32	predictive	predictive	ADJ
cjfa-8193	32	33	ability	ability	NOUN
cjfa-8193	32	34	.	.	PUNCT
cjfa-8193	33	1	although	although	SCONJ
cjfa-8193	33	2	the	the	DET
cjfa-8193	33	3	literature	literature	NOUN
cjfa-8193	33	4	does	do	AUX
cjfa-8193	33	5	not	not	PART
cjfa-8193	33	6	show	show	VERB
cjfa-8193	33	7	one	one	NUM
cjfa-8193	33	8	individual	individual	ADJ
cjfa-8193	33	9	asymmetry	asymmetry	NOUN
cjfa-8193	33	10	specification	specification	NOUN
cjfa-8193	33	11	as	as	ADP
cjfa-8193	33	12	being	be	AUX
cjfa-8193	33	13	clearly	clearly	ADV
cjfa-8193	33	14	superior	superior	ADJ
cjfa-8193	33	15	to	to	ADP
cjfa-8193	33	16	others	other	NOUN
cjfa-8193	33	17	,	,	PUNCT
cjfa-8193	33	18	awartani	awartani	NOUN
cjfa-8193	33	19	and	and	CCONJ
cjfa-8193	33	20	corradi	corradi	PROPN
cjfa-8193	33	21	(	(	PUNCT
cjfa-8193	33	22	2005	2005	NUM
cjfa-8193	33	23	)	)	PUNCT
cjfa-8193	33	24	argue	argue	VERB
cjfa-8193	33	25	that	that	SCONJ
cjfa-8193	33	26	they	they	PRON
cjfa-8193	33	27	generally	generally	ADV
cjfa-8193	33	28	outperform	outperform	VERB
cjfa-8193	33	29	non	non	ADJ
cjfa-8193	33	30	-	-	ADJ
cjfa-8193	33	31	asymmetric	asymmetric	ADJ
cjfa-8193	33	32	specifications	specification	NOUN
cjfa-8193	33	33	in	in	ADP
cjfa-8193	33	34	financial	financial	ADJ
cjfa-8193	33	35	market	market	NOUN
cjfa-8193	33	36	prediction	prediction	NOUN
cjfa-8193	33	37	.	.	PUNCT
cjfa-8193	34	1	however	however	ADV
cjfa-8193	34	2	,	,	PUNCT
cjfa-8193	34	3	it	it	PRON
cjfa-8193	34	4	can	can	AUX
cjfa-8193	34	5	be	be	AUX
cjfa-8193	34	6	noted	note	VERB
cjfa-8193	34	7	that	that	SCONJ
cjfa-8193	34	8	the	the	DET
cjfa-8193	34	9	evidence	evidence	NOUN
cjfa-8193	34	10	is	be	AUX
cjfa-8193	34	11	not	not	PART
cjfa-8193	34	12	unequivocal	unequivocal	ADJ
cjfa-8193	34	13	;	;	PUNCT
cjfa-8193	34	14	mcmillan	mcmillan	PROPN
cjfa-8193	34	15	,	,	PUNCT
cjfa-8193	34	16	speight	speight	PROPN
cjfa-8193	34	17	,	,	PUNCT
cjfa-8193	34	18	and	and	CCONJ
cjfa-8193	34	19	apgwilym	apgwilym	PROPN
cjfa-8193	34	20	(	(	PUNCT
cjfa-8193	34	21	2000	2000	NUM
cjfa-8193	34	22	)	)	PUNCT
cjfa-8193	34	23	found	find	VERB
cjfa-8193	34	24	garch	garch	NOUN
cjfa-8193	34	25	,	,	PUNCT
cjfa-8193	34	26	moving	move	VERB
cjfa-8193	34	27	average	average	ADJ
cjfa-8193	34	28	and	and	CCONJ
cjfa-8193	34	29	exponential	exponential	ADJ
cjfa-8193	34	30	smoothing	smoothing	NOUN
cjfa-8193	34	31	models	model	NOUN
cjfa-8193	34	32	to	to	PART
cjfa-8193	34	33	provide	provide	VERB
cjfa-8193	34	34	marginally	marginally	ADV
cjfa-8193	34	35	superior	superior	ADJ
cjfa-8193	34	36	daily	daily	ADJ
cjfa-8193	34	37	volatility	volatility	NOUN
cjfa-8193	34	38	forecasts	forecast	NOUN
cjfa-8193	34	39	.	.	PUNCT
cjfa-8193	35	1	their	their	PRON
cjfa-8193	35	2	work	work	NOUN
cjfa-8193	35	3	also	also	ADV
cjfa-8193	35	4	strongly	strongly	ADV
cjfa-8193	35	5	suggested	suggest	VERB
cjfa-8193	35	6	that	that	SCONJ
cjfa-8193	35	7	egarch	egarch	NOUN
cjfa-8193	35	8	does	do	AUX
cjfa-8193	35	9	not	not	PART
cjfa-8193	35	10	necessarily	necessarily	ADV
cjfa-8193	35	11	outperform	outperform	VERB
cjfa-8193	35	12	simple	simple	ADJ
cjfa-8193	35	13	garch	garch	NOUN
cjfa-8193	35	14	model	model	NOUN
cjfa-8193	35	15	in	in	ADP
cjfa-8193	35	16	forecasting	forecast	VERB
cjfa-8193	35	17	market	market	NOUN
cjfa-8193	35	18	volatility	volatility	NOUN
cjfa-8193	35	19	.	.	PUNCT
cjfa-8193	36	1	for	for	ADP
cjfa-8193	36	2	the	the	DET
cjfa-8193	36	3	purposes	purpose	NOUN
cjfa-8193	36	4	of	of	ADP
cjfa-8193	36	5	our	our	PRON
cjfa-8193	36	6	paper	paper	NOUN
cjfa-8193	36	7	methodologies	methodology	NOUN
cjfa-8193	36	8	with	with	ADP
cjfa-8193	36	9	the	the	DET
cjfa-8193	36	10	greatest	great	ADJ
cjfa-8193	36	11	out	out	ADP
cjfa-8193	36	12	-	-	PUNCT
cjfa-8193	36	13	of	of	ADP
cjfa-8193	36	14	-	-	PUNCT
cjfa-8193	36	15	sample	sample	NOUN
cjfa-8193	36	16	forecasting	forecasting	NOUN
cjfa-8193	36	17	accuracy	accuracy	NOUN
cjfa-8193	36	18	are	be	AUX
cjfa-8193	36	19	the	the	DET
cjfa-8193	36	20	most	most	ADV
cjfa-8193	36	21	desirable	desirable	ADJ
cjfa-8193	36	22	.	.	PUNCT
cjfa-8193	37	1	balaban	balaban	NOUN
cjfa-8193	37	2	(	(	PUNCT
cjfa-8193	37	3	2004	2004	NUM
cjfa-8193	37	4	)	)	PUNCT
cjfa-8193	37	5	tested	test	VERB
cjfa-8193	37	6	a	a	DET
cjfa-8193	37	7	series	series	NOUN
cjfa-8193	37	8	of	of	ADP
cjfa-8193	37	9	both	both	CCONJ
cjfa-8193	37	10	symmetric	symmetric	ADJ
cjfa-8193	37	11	and	and	CCONJ
cjfa-8193	37	12	asymmetric	asymmetric	ADJ
cjfa-8193	37	13	models	model	NOUN
cjfa-8193	37	14	(	(	PUNCT
cjfa-8193	37	15	included	include	VERB
cjfa-8193	37	16	arch	arch	ADJ
cjfa-8193	37	17	,	,	PUNCT
cjfa-8193	37	18	garch	garch	NOUN
cjfa-8193	37	19	,	,	PUNCT
cjfa-8193	37	20	gjrgarch	gjrgarch	NOUN
cjfa-8193	37	21	and	and	CCONJ
cjfa-8193	37	22	egarch	egarch	NOUN
cjfa-8193	37	23	)	)	PUNCT
cjfa-8193	37	24	.	.	PUNCT
cjfa-8193	38	1	their	their	PRON
cjfa-8193	38	2	results	result	NOUN
cjfa-8193	38	3	suggest	suggest	VERB
cjfa-8193	38	4	that	that	SCONJ
cjfa-8193	38	5	all	all	DET
cjfa-8193	38	6	models	model	NOUN
cjfa-8193	38	7	are	be	AUX
cjfa-8193	38	8	biased	biased	ADJ
cjfa-8193	38	9	and	and	CCONJ
cjfa-8193	38	10	generally	generally	ADV
cjfa-8193	38	11	over	over	ADV
cjfa-8193	38	12	-	-	PUNCT
cjfa-8193	38	13	predict	predict	VERB
cjfa-8193	38	14	volatility	volatility	NOUN
cjfa-8193	38	15	.	.	PUNCT
cjfa-8193	39	1	model	model	NOUN
cjfa-8193	39	2	performance	performance	NOUN
cjfa-8193	39	3	in	in	ADP
cjfa-8193	39	4	these	these	DET
cjfa-8193	39	5	latter	latter	ADJ
cjfa-8193	39	6	respects	respect	NOUN
cjfa-8193	39	7	was	be	AUX
cjfa-8193	39	8	best	good	ADJ
cjfa-8193	39	9	for	for	ADP
cjfa-8193	39	10	garch	garch	NOUN
cjfa-8193	39	11	and	and	CCONJ
cjfa-8193	39	12	worst	bad	ADJ
cjfa-8193	39	13	for	for	ADP
cjfa-8193	39	14	gjr	gjr	NOUN
cjfa-8193	39	15	-	-	PUNCT
cjfa-8193	39	16	garch	garch	NOUN
cjfa-8193	39	17	.	.	PUNCT
cjfa-8193	40	1	however	however	ADV
cjfa-8193	40	2	,	,	PUNCT
cjfa-8193	40	3	they	they	PRON
cjfa-8193	40	4	also	also	ADV
cjfa-8193	40	5	noted	note	VERB
cjfa-8193	40	6	that	that	SCONJ
cjfa-8193	40	7	if	if	SCONJ
cjfa-8193	40	8	avoidance	avoidance	NOUN
cjfa-8193	40	9	of	of	ADP
cjfa-8193	40	10	under	under	NOUN
cjfa-8193	40	11	-	-	PUNCT
cjfa-8193	40	12	prediction	prediction	NOUN
cjfa-8193	40	13	was	be	AUX
cjfa-8193	40	14	the	the	DET
cjfa-8193	40	15	key	key	ADJ
cjfa-8193	40	16	decision	decision	NOUN
cjfa-8193	40	17	criteria	criterion	NOUN
cjfa-8193	40	18	,	,	PUNCT
cjfa-8193	40	19	arch	arch	ADJ
cjfa-8193	40	20	was	be	AUX
cjfa-8193	40	21	the	the	DET
cjfa-8193	40	22	preferred	preferred	ADJ
cjfa-8193	40	23	model	model	NOUN
cjfa-8193	40	24	.	.	PUNCT
cjfa-8193	41	1	a	a	DET
cjfa-8193	41	2	further	further	ADJ
cjfa-8193	41	3	issue	issue	NOUN
cjfa-8193	41	4	that	that	PRON
cjfa-8193	41	5	is	be	AUX
cjfa-8193	41	6	important	important	ADJ
cjfa-8193	41	7	to	to	PART
cjfa-8193	41	8	consider	consider	VERB
cjfa-8193	41	9	is	be	AUX
cjfa-8193	41	10	that	that	SCONJ
cjfa-8193	41	11	the	the	DET
cjfa-8193	41	12	nature	nature	NOUN
cjfa-8193	41	13	of	of	ADP
cjfa-8193	41	14	volatility	volatility	NOUN
cjfa-8193	41	15	in	in	ADP
cjfa-8193	41	16	emerging	emerge	VERB
cjfa-8193	41	17	and	and	CCONJ
cjfa-8193	41	18	frontier	frontier	NOUN
cjfa-8193	41	19	markets	market	NOUN
cjfa-8193	41	20	differs	differ	VERB
cjfa-8193	41	21	considerably	considerably	ADV
cjfa-8193	41	22	from	from	ADP
cjfa-8193	41	23	that	that	PRON
cjfa-8193	41	24	found	find	VERB
cjfa-8193	41	25	in	in	ADP
cjfa-8193	41	26	developed	develop	VERB
cjfa-8193	41	27	markets	market	NOUN
cjfa-8193	41	28	(	(	PUNCT
cjfa-8193	41	29	andrikopoulos	andrikopoulo	NOUN
cjfa-8193	41	30	,	,	PUNCT
cjfa-8193	41	31	niklewski	niklewski	ADJ
cjfa-8193	41	32	and	and	CCONJ
cjfa-8193	41	33	rodgers	rodger	NOUN
cjfa-8193	41	34	forthcoming	forthcoming	ADJ
cjfa-8193	41	35	)	)	PUNCT
cjfa-8193	41	36	.	.	PUNCT
cjfa-8193	42	1	given	give	VERB
cjfa-8193	42	2	that	that	SCONJ
cjfa-8193	42	3	the	the	DET
cjfa-8193	42	4	focus	focus	NOUN
cjfa-8193	42	5	of	of	ADP
cjfa-8193	42	6	this	this	DET
cjfa-8193	42	7	paper	paper	NOUN
cjfa-8193	42	8	is	be	AUX
cjfa-8193	42	9	jordan	jordan	PROPN
cjfa-8193	42	10	,	,	PUNCT
cjfa-8193	42	11	it	it	PRON
cjfa-8193	42	12	is	be	AUX
cjfa-8193	42	13	important	important	ADJ
cjfa-8193	42	14	to	to	PART
cjfa-8193	42	15	consider	consider	VERB
cjfa-8193	42	16	how	how	SCONJ
cjfa-8193	42	17	different	different	ADJ
cjfa-8193	42	18	garch	garch	NOUN
cjfa-8193	42	19	specifications	specification	NOUN
cjfa-8193	42	20	perform	perform	VERB
cjfa-8193	42	21	in	in	ADP
cjfa-8193	42	22	these	these	DET
cjfa-8193	42	23	market	market	NOUN
cjfa-8193	42	24	-	-	PUNCT
cjfa-8193	42	25	types	type	NOUN
cjfa-8193	42	26	.	.	PUNCT
cjfa-8193	43	1	gokcan	gokcan	NOUN
cjfa-8193	43	2	(	(	PUNCT
cjfa-8193	43	3	2000	2000	NUM
cjfa-8193	43	4	)	)	PUNCT
cjfa-8193	43	5	examined	examine	VERB
cjfa-8193	43	6	seven	seven	NUM
cjfa-8193	43	7	emerging	emerge	VERB
cjfa-8193	43	8	market	market	NOUN
cjfa-8193	43	9	(	(	PUNCT
cjfa-8193	43	10	argentina	argentina	PROPN
cjfa-8193	43	11	,	,	PUNCT
cjfa-8193	43	12	brazil	brazil	PROPN
cjfa-8193	43	13	,	,	PUNCT
cjfa-8193	43	14	colombia	colombia	PROPN
cjfa-8193	43	15	,	,	PUNCT
cjfa-8193	43	16	malaysia	malaysia	PROPN
cjfa-8193	43	17	,	,	PUNCT
cjfa-8193	43	18	mexico	mexico	PROPN
cjfa-8193	43	19	,	,	PUNCT
cjfa-8193	43	20	philippines	philippine	NOUN
cjfa-8193	43	21	,	,	PUNCT
cjfa-8193	43	22	taiwan	taiwan	PROPN
cjfa-8193	43	23	)	)	PUNCT
cjfa-8193	43	24	and	and	CCONJ
cjfa-8193	43	25	found	find	VERB
cjfa-8193	43	26	that	that	DET
cjfa-8193	43	27	garch(1,1	garch(1,1	NOUN
cjfa-8193	43	28	)	)	PUNCT
cjfa-8193	43	29	outperformed	outperform	VERB
cjfa-8193	43	30	egarch	egarch	NOUN
cjfa-8193	43	31	everywhere	everywhere	ADV
cjfa-8193	43	32	with	with	ADP
cjfa-8193	43	33	the	the	DET
cjfa-8193	43	34	exception	exception	NOUN
cjfa-8193	43	35	of	of	ADP
cjfa-8193	43	36	brazil	brazil	PROPN
cjfa-8193	43	37	.	.	PUNCT
cjfa-8193	44	1	the	the	DET
cjfa-8193	44	2	most	most	ADV
cjfa-8193	44	3	compelling	compelling	ADJ
cjfa-8193	44	4	conclusion	conclusion	NOUN
cjfa-8193	44	5	we	we	PRON
cjfa-8193	44	6	draw	draw	VERB
cjfa-8193	44	7	from	from	ADP
cjfa-8193	44	8	the	the	DET
cjfa-8193	44	9	literature	literature	NOUN
cjfa-8193	44	10	in	in	ADP
cjfa-8193	44	11	respect	respect	NOUN
cjfa-8193	44	12	to	to	ADP
cjfa-8193	44	13	modelling	model	VERB
cjfa-8193	44	14	volatility	volatility	NOUN
cjfa-8193	44	15	structure	structure	NOUN
cjfa-8193	44	16	is	be	AUX
cjfa-8193	44	17	that	that	SCONJ
cjfa-8193	44	18	it	it	PRON
cjfa-8193	44	19	is	be	AUX
cjfa-8193	44	20	difficult	difficult	ADJ
cjfa-8193	44	21	to	to	PART
cjfa-8193	44	22	identify	identify	VERB
cjfa-8193	44	23	one	one	NUM
cjfa-8193	44	24	single	single	ADJ
cjfa-8193	44	25	model	model	NOUN
cjfa-8193	44	26	that	that	PRON
cjfa-8193	44	27	is	be	AUX
cjfa-8193	44	28	clearly	clearly	ADV
cjfa-8193	44	29	superior	superior	ADJ
cjfa-8193	44	30	to	to	ADP
cjfa-8193	44	31	others	other	NOUN
cjfa-8193	44	32	.	.	PUNCT
cjfa-8193	45	1	this	this	PRON
cjfa-8193	45	2	indicates	indicate	VERB
cjfa-8193	45	3	to	to	ADP
cjfa-8193	45	4	us	we	PRON
cjfa-8193	45	5	that	that	SCONJ
cjfa-8193	45	6	it	it	PRON
cjfa-8193	45	7	may	may	AUX
cjfa-8193	45	8	be	be	AUX
cjfa-8193	45	9	necessary	necessary	ADJ
cjfa-8193	45	10	to	to	PART
cjfa-8193	45	11	test	test	VERB
cjfa-8193	45	12	a	a	DET
cjfa-8193	45	13	number	number	NOUN
cjfa-8193	45	14	of	of	ADP
cjfa-8193	45	15	volatility	volatility	NOUN
cjfa-8193	45	16	specifications	specification	NOUN
cjfa-8193	45	17	.	.	PUNCT
cjfa-8193	46	1	a	a	DET
cjfa-8193	46	2	standard	standard	ADJ
cjfa-8193	46	3	feature	feature	NOUN
cjfa-8193	46	4	of	of	ADP
cjfa-8193	46	5	most	most	ADJ
cjfa-8193	46	6	financial	financial	ADJ
cjfa-8193	46	7	markets	market	NOUN
cjfa-8193	46	8	is	be	AUX
cjfa-8193	46	9	that	that	SCONJ
cjfa-8193	46	10	their	their	PRON
cjfa-8193	46	11	returns	return	NOUN
cjfa-8193	46	12	are	be	AUX
cjfa-8193	46	13	nonnormal	nonnormal	ADJ
cjfa-8193	46	14	with	with	ADP
cjfa-8193	46	15	distributions	distribution	NOUN
cjfa-8193	46	16	exhibiting	exhibit	VERB
cjfa-8193	46	17	‘	'	PUNCT
cjfa-8193	46	18	fat	fat	ADJ
cjfa-8193	46	19	-	-	PUNCT
cjfa-8193	46	20	tailed	tailed	ADJ
cjfa-8193	46	21	’	'	PUNCT
cjfa-8193	46	22	characteristics	characteristic	NOUN
cjfa-8193	46	23	(	(	PUNCT
cjfa-8193	46	24	mittnik	mittnik	NOUN
cjfa-8193	46	25	,	,	PUNCT
cjfa-8193	46	26	paolella	paolella	NOUN
cjfa-8193	46	27	,	,	PUNCT
cjfa-8193	46	28	and	and	CCONJ
cjfa-8193	46	29	rachev	rachev	VERB
cjfa-8193	46	30	2000	2000	NUM
cjfa-8193	46	31	)	)	PUNCT
cjfa-8193	46	32	.	.	PUNCT
cjfa-8193	47	1	this	this	PRON
cjfa-8193	47	2	appears	appear	VERB
cjfa-8193	47	3	to	to	PART
cjfa-8193	47	4	be	be	AUX
cjfa-8193	47	5	particularly	particularly	ADV
cjfa-8193	47	6	an	an	DET
cjfa-8193	47	7	issue	issue	NOUN
cjfa-8193	47	8	in	in	ADP
cjfa-8193	47	9	emerging	emerge	VERB
cjfa-8193	47	10	markets	market	NOUN
cjfa-8193	47	11	.	.	PUNCT
cjfa-8193	48	1	brooks	brooks	PROPN
cjfa-8193	48	2	(	(	PUNCT
cjfa-8193	48	3	2007	2007	NUM
cjfa-8193	48	4	)	)	PUNCT
cjfa-8193	48	5	studied	study	VERB
cjfa-8193	48	6	a	a	DET
cjfa-8193	48	7	set	set	NOUN
cjfa-8193	48	8	of	of	ADP
cjfa-8193	48	9	such	such	ADJ
cjfa-8193	48	10	markets	market	NOUN
cjfa-8193	48	11	(	(	PUNCT
cjfa-8193	48	12	including	include	VERB
cjfa-8193	48	13	mena	mena	PROPN
cjfa-8193	48	14	reh	reh	PROPN
cjfa-8193	48	15	.	.	PUNCT
cjfa-8193	49	1	al	al	PROPN
cjfa-8193	49	2	-	-	PUNCT
cjfa-8193	49	3	hajieh	hajieh	PROPN
cjfa-8193	49	4	,	,	PUNCT
cjfa-8193	49	5	h.	h.	PROPN
cjfa-8193	49	6	alnemer	alnemer	PROPN
cjfa-8193	49	7	,	,	PUNCT
cjfa-8193	49	8	t.	t.	PROPN
cjfa-8193	49	9	rodgers	rodgers	PROPN
cjfa-8193	49	10	,	,	PUNCT
cjfa-8193	49	11	j.	j.	PROPN
cjfa-8193	49	12	niklewski12	niklewski12	PROPN
cjfa-8193	49	13	gion	gion	PROPN
cjfa-8193	49	14	countries	country	NOUN
cjfa-8193	49	15	)	)	PUNCT
cjfa-8193	49	16	using	use	VERB
cjfa-8193	49	17	the	the	DET
cjfa-8193	49	18	asymmetric	asymmetric	ADJ
cjfa-8193	49	19	power	power	NOUN
cjfa-8193	49	20	arch	arch	NOUN
cjfa-8193	49	21	model	model	NOUN
cjfa-8193	49	22	.	.	PUNCT
cjfa-8193	50	1	he	he	PRON
cjfa-8193	50	2	found	find	VERB
cjfa-8193	50	3	that	that	SCONJ
cjfa-8193	50	4	unlike	unlike	ADP
cjfa-8193	50	5	developed	develop	VERB
cjfa-8193	50	6	markets	market	NOUN
cjfa-8193	50	7	,	,	PUNCT
cjfa-8193	50	8	where	where	SCONJ
cjfa-8193	50	9	non	non	ADJ
cjfa-8193	50	10	-	-	ADJ
cjfa-8193	50	11	normal	normal	ADJ
cjfa-8193	50	12	conditional	conditional	ADJ
cjfa-8193	50	13	error	error	NOUN
cjfa-8193	50	14	distributions	distribution	NOUN
cjfa-8193	50	15	appear	appear	VERB
cjfa-8193	50	16	to	to	PART
cjfa-8193	50	17	fit	fit	VERB
cjfa-8193	50	18	the	the	DET
cjfa-8193	50	19	data	datum	NOUN
cjfa-8193	50	20	well	well	ADV
cjfa-8193	50	21	,	,	PUNCT
cjfa-8193	50	22	there	there	PRON
cjfa-8193	50	23	were	be	VERB
cjfa-8193	50	24	a	a	DET
cjfa-8193	50	25	set	set	NOUN
cjfa-8193	50	26	of	of	ADP
cjfa-8193	50	27	emerging	emerge	VERB
cjfa-8193	50	28	markets	market	NOUN
cjfa-8193	50	29	where	where	SCONJ
cjfa-8193	50	30	estimation	estimation	NOUN
cjfa-8193	50	31	problems	problem	NOUN
cjfa-8193	50	32	arise	arise	VERB
cjfa-8193	50	33	using	use	VERB
cjfa-8193	50	34	a	a	DET
cjfa-8193	50	35	conditional	conditional	ADJ
cjfa-8193	50	36	t	t	NOUN
cjfa-8193	50	37	distribution	distribution	NOUN
cjfa-8193	50	38	.	.	PUNCT
cjfa-8193	51	1	it	it	PRON
cjfa-8193	51	2	was	be	AUX
cjfa-8193	51	3	also	also	ADV
cjfa-8193	51	4	found	find	VERB
cjfa-8193	51	5	that	that	SCONJ
cjfa-8193	51	6	the	the	DET
cjfa-8193	51	7	degree	degree	NOUN
cjfa-8193	51	8	of	of	ADP
cjfa-8193	51	9	volatility	volatility	NOUN
cjfa-8193	51	10	asymmetry	asymmetry	NOUN
cjfa-8193	51	11	appears	appear	VERB
cjfa-8193	51	12	to	to	PART
cjfa-8193	51	13	vary	vary	VERB
cjfa-8193	51	14	across	across	ADP
cjfa-8193	51	15	markets	market	NOUN
cjfa-8193	51	16	,	,	PUNCT
cjfa-8193	51	17	with	with	ADP
cjfa-8193	51	18	the	the	DET
cjfa-8193	51	19	middle	middle	ADJ
cjfa-8193	51	20	eastern	eastern	ADJ
cjfa-8193	51	21	and	and	CCONJ
cjfa-8193	51	22	african	african	ADJ
cjfa-8193	51	23	markets	market	NOUN
cjfa-8193	51	24	having	have	VERB
cjfa-8193	51	25	very	very	ADV
cjfa-8193	51	26	different	different	ADJ
cjfa-8193	51	27	volatility	volatility	NOUN
cjfa-8193	51	28	asymmetry	asymmetry	NOUN
cjfa-8193	51	29	characteristics	characteristic	NOUN
cjfa-8193	51	30	to	to	ADP
cjfa-8193	51	31	latin	latin	ADJ
cjfa-8193	51	32	american	american	ADJ
cjfa-8193	51	33	markets	market	NOUN
cjfa-8193	51	34	.	.	PUNCT
cjfa-8193	52	1	brooks	brooks	PROPN
cjfa-8193	52	2	(	(	PUNCT
cjfa-8193	52	3	2007	2007	NUM
cjfa-8193	52	4	)	)	PUNCT
cjfa-8193	52	5	found	find	VERB
cjfa-8193	52	6	that	that	SCONJ
cjfa-8193	52	7	a	a	DET
cjfa-8193	52	8	fat	fat	NOUN
cjfa-8193	52	9	-	-	PUNCT
cjfa-8193	52	10	tailed	tail	VERB
cjfa-8193	52	11	t	t	NOUN
cjfa-8193	52	12	-	-	PUNCT
cjfa-8193	52	13	distribution	distribution	NOUN
cjfa-8193	52	14	was	be	AUX
cjfa-8193	52	15	needed	need	VERB
cjfa-8193	52	16	to	to	PART
cjfa-8193	52	17	model	model	VERB
cjfa-8193	52	18	the	the	DET
cjfa-8193	52	19	distribution	distribution	NOUN
cjfa-8193	52	20	of	of	ADP
cjfa-8193	52	21	returns	return	NOUN
cjfa-8193	52	22	in	in	ADP
cjfa-8193	52	23	most	most	ADJ
cjfa-8193	52	24	mena	mena	PROPN
cjfa-8193	52	25	markets	market	NOUN
cjfa-8193	52	26	.	.	PUNCT
cjfa-8193	53	1	however	however	ADV
cjfa-8193	53	2	,	,	PUNCT
cjfa-8193	53	3	there	there	PRON
cjfa-8193	53	4	were	be	VERB
cjfa-8193	53	5	differences	difference	NOUN
cjfa-8193	53	6	.	.	PUNCT
cjfa-8193	54	1	for	for	ADP
cjfa-8193	54	2	example	example	NOUN
cjfa-8193	54	3	,	,	PUNCT
cjfa-8193	54	4	turkey	turkey	PROPN
cjfa-8193	54	5	,	,	PUNCT
cjfa-8193	54	6	egypt	egypt	PROPN
cjfa-8193	54	7	and	and	CCONJ
cjfa-8193	54	8	morocco	morocco	PROPN
cjfa-8193	54	9	display	display	VERB
cjfa-8193	54	10	much	much	ADV
cjfa-8193	54	11	larger	large	ADJ
cjfa-8193	54	12	kurtosis	kurtosis	NOUN
cjfa-8193	54	13	and	and	CCONJ
cjfa-8193	54	14	exhibit	exhibit	VERB
cjfa-8193	54	15	fatter	fat	ADJ
cjfa-8193	54	16	tails	tail	NOUN
cjfa-8193	54	17	than	than	ADP
cjfa-8193	54	18	jordan	jordan	PROPN
cjfa-8193	54	19	.	.	PUNCT
cjfa-8193	55	1	likelihood	likelihood	NOUN
cjfa-8193	55	2	ratio	ratio	NOUN
cjfa-8193	55	3	tests	test	NOUN
cjfa-8193	55	4	were	be	AUX
cjfa-8193	55	5	found	find	VERB
cjfa-8193	55	6	to	to	PART
cjfa-8193	55	7	clearly	clearly	ADV
cjfa-8193	55	8	favour	favour	VERB
cjfa-8193	55	9	the	the	DET
cjfa-8193	55	10	aparch	aparch	NOUN
cjfa-8193	55	11	with	with	ADP
cjfa-8193	55	12	t	t	NOUN
cjfa-8193	55	13	-	-	PUNCT
cjfa-8193	55	14	distribution	distribution	NOUN
cjfa-8193	55	15	rather	rather	ADV
cjfa-8193	55	16	than	than	ADP
cjfa-8193	55	17	a	a	DET
cjfa-8193	55	18	normal	normal	ADJ
cjfa-8193	55	19	distribution	distribution	NOUN
cjfa-8193	55	20	.	.	PUNCT
cjfa-8193	56	1	it	it	PRON
cjfa-8193	56	2	is	be	AUX
cjfa-8193	56	3	possible	possible	ADJ
cjfa-8193	56	4	that	that	SCONJ
cjfa-8193	56	5	such	such	ADJ
cjfa-8193	56	6	differences	difference	NOUN
cjfa-8193	56	7	may	may	AUX
cjfa-8193	56	8	reflect	reflect	VERB
cjfa-8193	56	9	the	the	DET
cjfa-8193	56	10	islamic	islamic	ADJ
cjfa-8193	56	11	nature	nature	NOUN
cjfa-8193	56	12	of	of	ADP
cjfa-8193	56	13	these	these	DET
cjfa-8193	56	14	markets	market	NOUN
cjfa-8193	56	15	.	.	PUNCT
cjfa-8193	57	1	for	for	ADP
cjfa-8193	57	2	example	example	NOUN
cjfa-8193	57	3	,	,	PUNCT
cjfa-8193	57	4	al	al	PROPN
cjfa-8193	57	5	-	-	PUNCT
cjfa-8193	57	6	hajieh	hajieh	PROPN
cjfa-8193	57	7	,	,	PUNCT
cjfa-8193	57	8	redhead	redhead	NOUN
cjfa-8193	57	9	,	,	PUNCT
cjfa-8193	57	10	and	and	CCONJ
cjfa-8193	57	11	rodgers	rodger	NOUN
cjfa-8193	57	12	(	(	PUNCT
cjfa-8193	57	13	2011	2011	NUM
cjfa-8193	57	14	)	)	PUNCT
cjfa-8193	57	15	found	find	VERB
cjfa-8193	57	16	that	that	SCONJ
cjfa-8193	57	17	the	the	DET
cjfa-8193	57	18	month	month	NOUN
cjfa-8193	57	19	of	of	ADP
cjfa-8193	57	20	ramadan	ramadan	PROPN
cjfa-8193	57	21	(	(	PUNCT
cjfa-8193	57	22	islamic	islamic	PROPN
cjfa-8193	57	23	holy	holy	PROPN
cjfa-8193	57	24	month	month	NOUN
cjfa-8193	57	25	)	)	PUNCT
cjfa-8193	57	26	shows	show	VERB
cjfa-8193	57	27	high	high	ADJ
cjfa-8193	57	28	level	level	NOUN
cjfa-8193	57	29	of	of	ADP
cjfa-8193	57	30	volatility	volatility	NOUN
cjfa-8193	57	31	and	and	CCONJ
cjfa-8193	57	32	the	the	DET
cjfa-8193	57	33	overall	overall	ADJ
cjfa-8193	57	34	impact	impact	NOUN
cjfa-8193	57	35	of	of	ADP
cjfa-8193	57	36	ramadan	ramadan	PROPN
cjfa-8193	57	37	on	on	ADP
cjfa-8193	57	38	returns	return	NOUN
cjfa-8193	57	39	is	be	AUX
cjfa-8193	57	40	statistically	statistically	ADV
cjfa-8193	57	41	significant	significant	ADJ
cjfa-8193	57	42	in	in	ADP
cjfa-8193	57	43	most	most	ADJ
cjfa-8193	57	44	middle	middle	PROPN
cjfa-8193	57	45	east	east	PROPN
cjfa-8193	57	46	countries	country	NOUN
cjfa-8193	57	47	.	.	PUNCT
cjfa-8193	58	1	we	we	PRON
cjfa-8193	58	2	conclude	conclude	VERB
cjfa-8193	58	3	the	the	DET
cjfa-8193	58	4	literature	literature	NOUN
cjfa-8193	58	5	review	review	NOUN
cjfa-8193	58	6	by	by	ADP
cjfa-8193	58	7	identifying	identify	VERB
cjfa-8193	58	8	that	that	SCONJ
cjfa-8193	58	9	we	we	PRON
cjfa-8193	58	10	are	be	AUX
cjfa-8193	58	11	aware	aware	ADJ
cjfa-8193	58	12	of	of	ADP
cjfa-8193	58	13	no	no	DET
cjfa-8193	58	14	studies	study	NOUN
cjfa-8193	58	15	of	of	ADP
cjfa-8193	58	16	volatility	volatility	NOUN
cjfa-8193	58	17	forecasting	forecasting	NOUN
cjfa-8193	58	18	in	in	ADP
cjfa-8193	58	19	emerging	emerge	VERB
cjfa-8193	58	20	markets	market	NOUN
cjfa-8193	58	21	that	that	PRON
cjfa-8193	58	22	have	have	AUX
cjfa-8193	58	23	examined	examine	VERB
cjfa-8193	58	24	the	the	DET
cjfa-8193	58	25	combined	combine	VERB
cjfa-8193	58	26	issues	issue	NOUN
cjfa-8193	58	27	of	of	ADP
cjfa-8193	58	28	the	the	DET
cjfa-8193	58	29	distribution	distribution	NOUN
cjfa-8193	58	30	of	of	ADP
cjfa-8193	58	31	returns	return	NOUN
cjfa-8193	58	32	and	and	CCONJ
cjfa-8193	58	33	the	the	DET
cjfa-8193	58	34	garch	garch	NOUN
cjfa-8193	58	35	model	model	NOUN
cjfa-8193	58	36	specification	specification	NOUN
cjfa-8193	58	37	.	.	PUNCT
cjfa-8193	59	1	we	we	PRON
cjfa-8193	59	2	have	have	AUX
cjfa-8193	59	3	also	also	ADV
cjfa-8193	59	4	identified	identify	VERB
cjfa-8193	59	5	from	from	ADP
cjfa-8193	59	6	the	the	DET
cjfa-8193	59	7	literature	literature	NOUN
cjfa-8193	59	8	that	that	SCONJ
cjfa-8193	59	9	(	(	PUNCT
cjfa-8193	59	10	i	i	NOUN
cjfa-8193	59	11	)	)	PUNCT
cjfa-8193	59	12	no	no	DET
cjfa-8193	59	13	single	single	ADJ
cjfa-8193	59	14	garch	garch	NOUN
cjfa-8193	59	15	model	model	NOUN
cjfa-8193	59	16	specifications	specification	NOUN
cjfa-8193	59	17	clearly	clearly	ADV
cjfa-8193	59	18	outperforms	outperform	VERB
cjfa-8193	59	19	other	other	ADJ
cjfa-8193	59	20	forms	form	NOUN
cjfa-8193	59	21	in	in	ADP
cjfa-8193	59	22	all	all	DET
cjfa-8193	59	23	circumstances	circumstance	NOUN
cjfa-8193	59	24	and	and	CCONJ
cjfa-8193	59	25	(	(	PUNCT
cjfa-8193	59	26	ii	ii	NOUN
cjfa-8193	59	27	)	)	PUNCT
cjfa-8193	59	28	evidence	evidence	NOUN
cjfa-8193	59	29	to	to	PART
cjfa-8193	59	30	suggest	suggest	VERB
cjfa-8193	59	31	that	that	SCONJ
cjfa-8193	59	32	the	the	DET
cjfa-8193	59	33	distribution	distribution	NOUN
cjfa-8193	59	34	of	of	ADP
cjfa-8193	59	35	returns	return	NOUN
cjfa-8193	59	36	in	in	ADP
cjfa-8193	59	37	emerging	emerge	VERB
cjfa-8193	59	38	markets	market	NOUN
cjfa-8193	59	39	(	(	PUNCT
cjfa-8193	59	40	like	like	ADP
cjfa-8193	59	41	jordan	jordan	PROPN
cjfa-8193	59	42	)	)	PUNCT
cjfa-8193	59	43	can	can	AUX
cjfa-8193	59	44	follow	follow	VERB
cjfa-8193	59	45	a	a	DET
cjfa-8193	59	46	number	number	NOUN
cjfa-8193	59	47	of	of	ADP
cjfa-8193	59	48	possible	possible	ADJ
cjfa-8193	59	49	forms	form	NOUN
cjfa-8193	59	50	and	and	CCONJ
cjfa-8193	59	51	that	that	SCONJ
cjfa-8193	59	52	these	these	PRON
cjfa-8193	59	53	can	can	AUX
cjfa-8193	59	54	interact	interact	VERB
cjfa-8193	59	55	with	with	ADP
cjfa-8193	59	56	volatility	volatility	NOUN
cjfa-8193	59	57	models	model	NOUN
cjfa-8193	59	58	in	in	ADP
cjfa-8193	59	59	different	different	ADJ
cjfa-8193	59	60	ways	way	NOUN
cjfa-8193	59	61	.	.	PUNCT
cjfa-8193	60	1	in	in	ADP
cjfa-8193	60	2	this	this	DET
cjfa-8193	60	3	paper	paper	NOUN
cjfa-8193	60	4	we	we	PRON
cjfa-8193	60	5	therefore	therefore	ADV
cjfa-8193	60	6	test	test	VERB
cjfa-8193	60	7	a	a	DET
cjfa-8193	60	8	number	number	NOUN
cjfa-8193	60	9	of	of	ADP
cjfa-8193	60	10	possible	possible	ADJ
cjfa-8193	60	11	distribution	distribution	NOUN
cjfa-8193	60	12	-	-	PUNCT
cjfa-8193	60	13	types	type	NOUN
cjfa-8193	60	14	(	(	PUNCT
cjfa-8193	60	15	normal	normal	ADJ
cjfa-8193	60	16	,	,	PUNCT
cjfa-8193	60	17	student	student	NOUN
cjfa-8193	60	18	-	-	PUNCT
cjfa-8193	60	19	t	t	NOUN
cjfa-8193	60	20	,	,	PUNCT
cjfa-8193	60	21	ged	ge	VERB
cjfa-8193	60	22	,	,	PUNCT
cjfa-8193	60	23	and	and	CCONJ
cjfa-8193	60	24	skewed	skewed	ADJ
cjfa-8193	60	25	student	student	NOUN
cjfa-8193	60	26	)	)	PUNCT
cjfa-8193	60	27	and	and	CCONJ
cjfa-8193	60	28	garch	garch	NOUN
cjfa-8193	60	29	model	model	NOUN
cjfa-8193	60	30	types	type	NOUN
cjfa-8193	60	31	(	(	PUNCT
cjfa-8193	60	32	garch	garch	NOUN
cjfa-8193	60	33	,	,	PUNCT
cjfa-8193	60	34	gjr	gjr	NOUN
cjfa-8193	60	35	-	-	PUNCT
cjfa-8193	60	36	garch	garch	NOUN
cjfa-8193	60	37	and	and	CCONJ
cjfa-8193	60	38	egarch	egarch	NOUN
cjfa-8193	60	39	)	)	PUNCT
cjfa-8193	60	40	in	in	ADP
cjfa-8193	60	41	order	order	NOUN
cjfa-8193	60	42	to	to	PART
cjfa-8193	60	43	identify	identify	VERB
cjfa-8193	60	44	the	the	DET
cjfa-8193	60	45	most	most	ADV
cjfa-8193	60	46	efficient	efficient	ADJ
cjfa-8193	60	47	volatility	volatility	NOUN
cjfa-8193	60	48	forecasting	forecasting	NOUN
cjfa-8193	60	49	model	model	NOUN
cjfa-8193	60	50	for	for	ADP
cjfa-8193	60	51	jordan	jordan	PROPN
cjfa-8193	60	52	.	.	PUNCT
cjfa-8193	61	1	data	datum	NOUN
cjfa-8193	61	2	description	description	NOUN
cjfa-8193	61	3	the	the	DET
cjfa-8193	61	4	empirical	empirical	ADJ
cjfa-8193	61	5	investigation	investigation	NOUN
cjfa-8193	61	6	is	be	AUX
cjfa-8193	61	7	undertaken	undertake	VERB
cjfa-8193	61	8	in	in	ADP
cjfa-8193	61	9	respect	respect	NOUN
cjfa-8193	61	10	to	to	ADP
cjfa-8193	61	11	daily	daily	ADJ
cjfa-8193	61	12	closing	closing	NOUN
cjfa-8193	61	13	price	price	NOUN
cjfa-8193	61	14	data	datum	NOUN
cjfa-8193	61	15	for	for	ADP
cjfa-8193	61	16	the	the	DET
cjfa-8193	61	17	jordanian	jordanian	ADJ
cjfa-8193	61	18	amman	amman	PROPN
cjfa-8193	61	19	stock	stock	PROPN
cjfa-8193	61	20	exchange	exchange	PROPN
cjfa-8193	61	21	index	index	NOUN
cjfa-8193	61	22	(	(	PUNCT
cjfa-8193	61	23	ase	ase	NOUN
cjfa-8193	61	24	)	)	PUNCT
cjfa-8193	61	25	covering	cover	VERB
cjfa-8193	61	26	the	the	DET
cjfa-8193	61	27	period	period	NOUN
cjfa-8193	61	28	2nd	2nd	ADJ
cjfa-8193	61	29	january	january	PROPN
cjfa-8193	61	30	2000	2000	NUM
cjfa-8193	61	31	to	to	ADP
cjfa-8193	61	32	27th	27th	NOUN
cjfa-8193	61	33	november	november	PROPN
cjfa-8193	61	34	2014	2014	NUM
cjfa-8193	61	35	.	.	PUNCT
cjfa-8193	62	1	the	the	DET
cjfa-8193	62	2	data	data	NOUN
cjfa-8193	62	3	source	source	NOUN
cjfa-8193	62	4	is	be	AUX
cjfa-8193	62	5	the	the	DET
cjfa-8193	62	6	thomson	thomson	PROPN
cjfa-8193	62	7	-	-	PUNCT
cjfa-8193	62	8	reuters	reuters	PROPN
cjfa-8193	62	9	eikon	eikon	PROPN
cjfa-8193	62	10	database	database	NOUN
cjfa-8193	62	11	and	and	CCONJ
cjfa-8193	62	12	the	the	DET
cjfa-8193	62	13	dataset	dataset	NOUN
cjfa-8193	62	14	comprises	comprise	NOUN
cjfa-8193	62	15	of	of	ADP
cjfa-8193	62	16	a	a	DET
cjfa-8193	62	17	total	total	NOUN
cjfa-8193	62	18	of	of	ADP
cjfa-8193	62	19	3655	3655	NUM
cjfa-8193	62	20	trading	trading	NOUN
cjfa-8193	62	21	days	day	NOUN
cjfa-8193	62	22	.	.	PUNCT
cjfa-8193	63	1	daily	daily	ADJ
cjfa-8193	63	2	returns	return	NOUN
cjfa-8193	63	3	computed	compute	VERB
cjfa-8193	63	4	as	as	ADP
cjfa-8193	63	5	the	the	DET
cjfa-8193	63	6	log	log	NOUN
cjfa-8193	63	7	-	-	PUNCT
cjfa-8193	63	8	difference	difference	NOUN
cjfa-8193	63	9	of	of	ADP
cjfa-8193	63	10	the	the	DET
cjfa-8193	63	11	daily	daily	ADJ
cjfa-8193	63	12	closing	closing	NOUN
cjfa-8193	63	13	prices	price	NOUN
cjfa-8193	63	14	:	:	PUNCT
cjfa-8193	63	15	forecasting	forecast	VERB
cjfa-8193	63	16	the	the	DET
cjfa-8193	63	17	jordanian	jordanian	ADJ
cjfa-8193	63	18	stock	stock	NOUN
cjfa-8193	63	19	index	index	PROPN
cjfa-8193	63	20	…	…	PUNCT
cjfa-8193	63	21	13	13	NUM
cjfa-8193	63	22	brooks	brook	NOUN
cjfa-8193	63	23	(	(	PUNCT
cjfa-8193	63	24	2007	2007	NUM
cjfa-8193	63	25	)	)	PUNCT
cjfa-8193	63	26	found	find	VERB
cjfa-8193	63	27	that	that	SCONJ
cjfa-8193	63	28	a	a	DET
cjfa-8193	63	29	fat	fat	NOUN
cjfa-8193	63	30	-	-	PUNCT
cjfa-8193	63	31	tailed	tail	VERB
cjfa-8193	63	32	t	t	NOUN
cjfa-8193	63	33	-	-	PUNCT
cjfa-8193	63	34	distribution	distribution	NOUN
cjfa-8193	63	35	was	be	AUX
cjfa-8193	63	36	needed	need	VERB
cjfa-8193	63	37	to	to	PART
cjfa-8193	63	38	model	model	VERB
cjfa-8193	63	39	the	the	DET
cjfa-8193	63	40	distribution	distribution	NOUN
cjfa-8193	63	41	of	of	ADP
cjfa-8193	63	42	returns	return	NOUN
cjfa-8193	63	43	in	in	ADP
cjfa-8193	63	44	most	most	ADJ
cjfa-8193	63	45	mena	mena	PROPN
cjfa-8193	63	46	markets	market	NOUN
cjfa-8193	63	47	.	.	PUNCT
cjfa-8193	64	1	however	however	ADV
cjfa-8193	64	2	,	,	PUNCT
cjfa-8193	64	3	there	there	PRON
cjfa-8193	64	4	were	be	VERB
cjfa-8193	64	5	differences	difference	NOUN
cjfa-8193	64	6	.	.	PUNCT
cjfa-8193	65	1	for	for	ADP
cjfa-8193	65	2	example	example	NOUN
cjfa-8193	65	3	,	,	PUNCT
cjfa-8193	65	4	turkey	turkey	PROPN
cjfa-8193	65	5	,	,	PUNCT
cjfa-8193	65	6	egypt	egypt	PROPN
cjfa-8193	65	7	and	and	CCONJ
cjfa-8193	65	8	morocco	morocco	PROPN
cjfa-8193	65	9	display	display	VERB
cjfa-8193	65	10	much	much	ADV
cjfa-8193	65	11	larger	large	ADJ
cjfa-8193	65	12	kurtosis	kurtosis	NOUN
cjfa-8193	65	13	and	and	CCONJ
cjfa-8193	65	14	exhibit	exhibit	VERB
cjfa-8193	65	15	fatter	fat	ADJ
cjfa-8193	65	16	tails	tail	NOUN
cjfa-8193	65	17	than	than	ADP
cjfa-8193	65	18	jordan	jordan	PROPN
cjfa-8193	65	19	.	.	PUNCT
cjfa-8193	66	1	likelihood	likelihood	NOUN
cjfa-8193	66	2	ratio	ratio	NOUN
cjfa-8193	66	3	tests	test	NOUN
cjfa-8193	66	4	were	be	AUX
cjfa-8193	66	5	found	find	VERB
cjfa-8193	66	6	to	to	PART
cjfa-8193	66	7	clearly	clearly	ADV
cjfa-8193	66	8	favour	favour	VERB
cjfa-8193	66	9	the	the	DET
cjfa-8193	66	10	aparch	aparch	NOUN
cjfa-8193	66	11	with	with	ADP
cjfa-8193	66	12	t	t	NOUN
cjfa-8193	66	13	-	-	PUNCT
cjfa-8193	66	14	distribution	distribution	NOUN
cjfa-8193	66	15	rather	rather	ADV
cjfa-8193	66	16	than	than	ADP
cjfa-8193	66	17	a	a	DET
cjfa-8193	66	18	normal	normal	ADJ
cjfa-8193	66	19	distribution	distribution	NOUN
cjfa-8193	66	20	.	.	PUNCT
cjfa-8193	67	1	it	it	PRON
cjfa-8193	67	2	is	be	AUX
cjfa-8193	67	3	possible	possible	ADJ
cjfa-8193	67	4	that	that	SCONJ
cjfa-8193	67	5	such	such	ADJ
cjfa-8193	67	6	differences	difference	NOUN
cjfa-8193	67	7	may	may	AUX
cjfa-8193	67	8	reflect	reflect	VERB
cjfa-8193	67	9	the	the	DET
cjfa-8193	67	10	islamic	islamic	ADJ
cjfa-8193	67	11	nature	nature	NOUN
cjfa-8193	67	12	of	of	ADP
cjfa-8193	67	13	these	these	DET
cjfa-8193	67	14	markets	market	NOUN
cjfa-8193	67	15	.	.	PUNCT
cjfa-8193	68	1	for	for	ADP
cjfa-8193	68	2	example	example	NOUN
cjfa-8193	68	3	,	,	PUNCT
cjfa-8193	68	4	al	al	PROPN
cjfa-8193	68	5	-	-	PUNCT
cjfa-8193	68	6	hajieh	hajieh	PROPN
cjfa-8193	68	7	,	,	PUNCT
cjfa-8193	68	8	redhead	redhead	NOUN
cjfa-8193	68	9	,	,	PUNCT
cjfa-8193	68	10	and	and	CCONJ
cjfa-8193	68	11	rodgers	rodger	NOUN
cjfa-8193	68	12	(	(	PUNCT
cjfa-8193	68	13	2011	2011	NUM
cjfa-8193	68	14	)	)	PUNCT
cjfa-8193	68	15	found	find	VERB
cjfa-8193	68	16	that	that	SCONJ
cjfa-8193	68	17	the	the	DET
cjfa-8193	68	18	month	month	NOUN
cjfa-8193	68	19	of	of	ADP
cjfa-8193	68	20	ramadan	ramadan	PROPN
cjfa-8193	68	21	(	(	PUNCT
cjfa-8193	68	22	islamic	islamic	PROPN
cjfa-8193	68	23	holy	holy	PROPN
cjfa-8193	68	24	month	month	NOUN
cjfa-8193	68	25	)	)	PUNCT
cjfa-8193	68	26	shows	show	VERB
cjfa-8193	68	27	high	high	ADJ
cjfa-8193	68	28	level	level	NOUN
cjfa-8193	68	29	of	of	ADP
cjfa-8193	68	30	volatility	volatility	NOUN
cjfa-8193	68	31	and	and	CCONJ
cjfa-8193	68	32	the	the	DET
cjfa-8193	68	33	overall	overall	ADJ
cjfa-8193	68	34	impact	impact	NOUN
cjfa-8193	68	35	of	of	ADP
cjfa-8193	68	36	ramadan	ramadan	PROPN
cjfa-8193	68	37	on	on	ADP
cjfa-8193	68	38	returns	return	NOUN
cjfa-8193	68	39	is	be	AUX
cjfa-8193	68	40	statistically	statistically	ADV
cjfa-8193	68	41	significant	significant	ADJ
cjfa-8193	68	42	in	in	ADP
cjfa-8193	68	43	most	most	ADJ
cjfa-8193	68	44	middle	middle	PROPN
cjfa-8193	68	45	east	east	PROPN
cjfa-8193	68	46	countries	country	NOUN
cjfa-8193	68	47	.	.	PUNCT
cjfa-8193	69	1	we	we	PRON
cjfa-8193	69	2	conclude	conclude	VERB
cjfa-8193	69	3	the	the	DET
cjfa-8193	69	4	literature	literature	NOUN
cjfa-8193	69	5	review	review	NOUN
cjfa-8193	69	6	by	by	ADP
cjfa-8193	69	7	identifying	identify	VERB
cjfa-8193	69	8	that	that	SCONJ
cjfa-8193	69	9	we	we	PRON
cjfa-8193	69	10	are	be	AUX
cjfa-8193	69	11	aware	aware	ADJ
cjfa-8193	69	12	of	of	ADP
cjfa-8193	69	13	no	no	DET
cjfa-8193	69	14	studies	study	NOUN
cjfa-8193	69	15	of	of	ADP
cjfa-8193	69	16	volatility	volatility	NOUN
cjfa-8193	69	17	forecasting	forecasting	NOUN
cjfa-8193	69	18	in	in	ADP
cjfa-8193	69	19	emerging	emerge	VERB
cjfa-8193	69	20	markets	market	NOUN
cjfa-8193	69	21	that	that	PRON
cjfa-8193	69	22	have	have	AUX
cjfa-8193	69	23	examined	examine	VERB
cjfa-8193	69	24	the	the	DET
cjfa-8193	69	25	combined	combine	VERB
cjfa-8193	69	26	issues	issue	NOUN
cjfa-8193	69	27	of	of	ADP
cjfa-8193	69	28	the	the	DET
cjfa-8193	69	29	distribution	distribution	NOUN
cjfa-8193	69	30	of	of	ADP
cjfa-8193	69	31	returns	return	NOUN
cjfa-8193	69	32	and	and	CCONJ
cjfa-8193	69	33	the	the	DET
cjfa-8193	69	34	garch	garch	NOUN
cjfa-8193	69	35	model	model	NOUN
cjfa-8193	69	36	specification	specification	NOUN
cjfa-8193	69	37	.	.	PUNCT
cjfa-8193	70	1	we	we	PRON
cjfa-8193	70	2	have	have	AUX
cjfa-8193	70	3	also	also	ADV
cjfa-8193	70	4	identified	identify	VERB
cjfa-8193	70	5	from	from	ADP
cjfa-8193	70	6	the	the	DET
cjfa-8193	70	7	literature	literature	NOUN
cjfa-8193	70	8	that	that	SCONJ
cjfa-8193	70	9	(	(	PUNCT
cjfa-8193	70	10	i	i	NOUN
cjfa-8193	70	11	)	)	PUNCT
cjfa-8193	70	12	no	no	DET
cjfa-8193	70	13	single	single	ADJ
cjfa-8193	70	14	garch	garch	NOUN
cjfa-8193	70	15	model	model	NOUN
cjfa-8193	70	16	specifications	specification	NOUN
cjfa-8193	70	17	clearly	clearly	ADV
cjfa-8193	70	18	outperforms	outperform	VERB
cjfa-8193	70	19	other	other	ADJ
cjfa-8193	70	20	forms	form	NOUN
cjfa-8193	70	21	in	in	ADP
cjfa-8193	70	22	all	all	DET
cjfa-8193	70	23	circumstances	circumstance	NOUN
cjfa-8193	70	24	and	and	CCONJ
cjfa-8193	70	25	(	(	PUNCT
cjfa-8193	70	26	ii	ii	NOUN
cjfa-8193	70	27	)	)	PUNCT
cjfa-8193	70	28	evidence	evidence	NOUN
cjfa-8193	70	29	to	to	PART
cjfa-8193	70	30	suggest	suggest	VERB
cjfa-8193	70	31	that	that	SCONJ
cjfa-8193	70	32	the	the	DET
cjfa-8193	70	33	distribution	distribution	NOUN
cjfa-8193	70	34	of	of	ADP
cjfa-8193	70	35	returns	return	NOUN
cjfa-8193	70	36	in	in	ADP
cjfa-8193	70	37	emerging	emerge	VERB
cjfa-8193	70	38	markets	market	NOUN
cjfa-8193	70	39	(	(	PUNCT
cjfa-8193	70	40	like	like	ADP
cjfa-8193	70	41	jordan	jordan	PROPN
cjfa-8193	70	42	)	)	PUNCT
cjfa-8193	70	43	can	can	AUX
cjfa-8193	70	44	follow	follow	VERB
cjfa-8193	70	45	a	a	DET
cjfa-8193	70	46	number	number	NOUN
cjfa-8193	70	47	of	of	ADP
cjfa-8193	70	48	possible	possible	ADJ
cjfa-8193	70	49	forms	form	NOUN
cjfa-8193	70	50	and	and	CCONJ
cjfa-8193	70	51	that	that	SCONJ
cjfa-8193	70	52	these	these	PRON
cjfa-8193	70	53	can	can	AUX
cjfa-8193	70	54	interact	interact	VERB
cjfa-8193	70	55	with	with	ADP
cjfa-8193	70	56	volatility	volatility	NOUN
cjfa-8193	70	57	models	model	NOUN
cjfa-8193	70	58	in	in	ADP
cjfa-8193	70	59	different	different	ADJ
cjfa-8193	70	60	ways	way	NOUN
cjfa-8193	70	61	.	.	PUNCT
cjfa-8193	71	1	in	in	ADP
cjfa-8193	71	2	this	this	DET
cjfa-8193	71	3	paper	paper	NOUN
cjfa-8193	71	4	we	we	PRON
cjfa-8193	71	5	therefore	therefore	ADV
cjfa-8193	71	6	test	test	VERB
cjfa-8193	71	7	a	a	DET
cjfa-8193	71	8	number	number	NOUN
cjfa-8193	71	9	of	of	ADP
cjfa-8193	71	10	possible	possible	ADJ
cjfa-8193	71	11	distribution	distribution	NOUN
cjfa-8193	71	12	-	-	PUNCT
cjfa-8193	71	13	types	type	NOUN
cjfa-8193	71	14	(	(	PUNCT
cjfa-8193	71	15	normal	normal	ADJ
cjfa-8193	71	16	,	,	PUNCT
cjfa-8193	71	17	student	student	NOUN
cjfa-8193	71	18	-	-	PUNCT
cjfa-8193	71	19	t	t	NOUN
cjfa-8193	71	20	,	,	PUNCT
cjfa-8193	71	21	ged	ge	VERB
cjfa-8193	71	22	,	,	PUNCT
cjfa-8193	71	23	and	and	CCONJ
cjfa-8193	71	24	skewed	skewed	ADJ
cjfa-8193	71	25	student	student	NOUN
cjfa-8193	71	26	)	)	PUNCT
cjfa-8193	71	27	and	and	CCONJ
cjfa-8193	71	28	garch	garch	NOUN
cjfa-8193	71	29	model	model	NOUN
cjfa-8193	71	30	types	type	NOUN
cjfa-8193	71	31	(	(	PUNCT
cjfa-8193	71	32	garch	garch	NOUN
cjfa-8193	71	33	,	,	PUNCT
cjfa-8193	71	34	gjr	gjr	NOUN
cjfa-8193	71	35	-	-	PUNCT
cjfa-8193	71	36	garch	garch	NOUN
cjfa-8193	71	37	and	and	CCONJ
cjfa-8193	71	38	egarch	egarch	NOUN
cjfa-8193	71	39	)	)	PUNCT
cjfa-8193	71	40	in	in	ADP
cjfa-8193	71	41	order	order	NOUN
cjfa-8193	71	42	to	to	PART
cjfa-8193	71	43	identify	identify	VERB
cjfa-8193	71	44	the	the	DET
cjfa-8193	71	45	most	most	ADV
cjfa-8193	71	46	efficient	efficient	ADJ
cjfa-8193	71	47	volatility	volatility	NOUN
cjfa-8193	71	48	forecasting	forecasting	NOUN
cjfa-8193	71	49	model	model	NOUN
cjfa-8193	71	50	for	for	ADP
cjfa-8193	71	51	jordan	jordan	PROPN
cjfa-8193	71	52	.	.	PUNCT
cjfa-8193	72	1	data	datum	NOUN
cjfa-8193	72	2	description	description	NOUN
cjfa-8193	72	3	the	the	DET
cjfa-8193	72	4	empirical	empirical	ADJ
cjfa-8193	72	5	investigation	investigation	NOUN
cjfa-8193	72	6	is	be	AUX
cjfa-8193	72	7	undertaken	undertake	VERB
cjfa-8193	72	8	in	in	ADP
cjfa-8193	72	9	respect	respect	NOUN
cjfa-8193	72	10	to	to	ADP
cjfa-8193	72	11	daily	daily	ADJ
cjfa-8193	72	12	closing	closing	NOUN
cjfa-8193	72	13	price	price	NOUN
cjfa-8193	72	14	data	datum	NOUN
cjfa-8193	72	15	for	for	ADP
cjfa-8193	72	16	the	the	DET
cjfa-8193	72	17	jordanian	jordanian	ADJ
cjfa-8193	72	18	amman	amman	PROPN
cjfa-8193	72	19	stock	stock	PROPN
cjfa-8193	72	20	exchange	exchange	PROPN
cjfa-8193	72	21	index	index	NOUN
cjfa-8193	72	22	(	(	PUNCT
cjfa-8193	72	23	ase	ase	NOUN
cjfa-8193	72	24	)	)	PUNCT
cjfa-8193	72	25	covering	cover	VERB
cjfa-8193	72	26	the	the	DET
cjfa-8193	72	27	period	period	NOUN
cjfa-8193	72	28	2nd	2nd	ADJ
cjfa-8193	72	29	january	january	PROPN
cjfa-8193	72	30	2000	2000	NUM
cjfa-8193	72	31	to	to	ADP
cjfa-8193	72	32	27th	27th	NOUN
cjfa-8193	72	33	november	november	PROPN
cjfa-8193	72	34	2014	2014	NUM
cjfa-8193	72	35	.	.	PUNCT
cjfa-8193	73	1	the	the	DET
cjfa-8193	73	2	data	data	NOUN
cjfa-8193	73	3	source	source	NOUN
cjfa-8193	73	4	is	be	AUX
cjfa-8193	73	5	the	the	DET
cjfa-8193	73	6	thomson	thomson	PROPN
cjfa-8193	73	7	-	-	PUNCT
cjfa-8193	73	8	reuters	reuters	PROPN
cjfa-8193	73	9	eikon	eikon	PROPN
cjfa-8193	73	10	database	database	NOUN
cjfa-8193	73	11	and	and	CCONJ
cjfa-8193	73	12	the	the	DET
cjfa-8193	73	13	dataset	dataset	NOUN
cjfa-8193	73	14	comprises	comprise	NOUN
cjfa-8193	73	15	of	of	ADP
cjfa-8193	73	16	a	a	DET
cjfa-8193	73	17	total	total	NOUN
cjfa-8193	73	18	of	of	ADP
cjfa-8193	73	19	3655	3655	NUM
cjfa-8193	73	20	trading	trading	NOUN
cjfa-8193	73	21	days	day	NOUN
cjfa-8193	73	22	.	.	PUNCT
cjfa-8193	74	1	daily	daily	ADJ
cjfa-8193	74	2	returns	return	NOUN
cjfa-8193	74	3	computed	compute	VERB
cjfa-8193	74	4	as	as	ADP
cjfa-8193	74	5	the	the	DET
cjfa-8193	74	6	logdifference	logdifference	NOUN
cjfa-8193	74	7	of	of	ADP
cjfa-8193	74	8	the	the	DET
cjfa-8193	74	9	daily	daily	ADJ
cjfa-8193	74	10	closing	closing	NOUN
cjfa-8193	74	11	prices	price	NOUN
cjfa-8193	74	12	:	:	PUNCT
cjfa-8193	74	13	ase	ase	NOUN
cjfa-8193	74	14	index	index	NOUN
cjfa-8193	74	15	closing	closing	NOUN
cjfa-8193	74	16	prices	price	NOUN
cjfa-8193	74	17	are	be	AUX
cjfa-8193	74	18	presented	present	VERB
cjfa-8193	74	19	in	in	ADP
cjfa-8193	74	20	figure	figure	NOUN
cjfa-8193	74	21	1	1	NUM
cjfa-8193	74	22	and	and	CCONJ
cjfa-8193	74	23	the	the	DET
cjfa-8193	74	24	daily	daily	ADJ
cjfa-8193	74	25	returns	return	NOUN
cjfa-8193	74	26	in	in	ADP
cjfa-8193	74	27	figure	figure	NOUN
cjfa-8193	74	28	2	2	NUM
cjfa-8193	74	29	.	.	PUNCT
cjfa-8193	75	1	a	a	DET
cjfa-8193	75	2	number	number	NOUN
cjfa-8193	75	3	of	of	ADP
cjfa-8193	75	4	volatility	volatility	NOUN
cjfa-8193	75	5	clusters	cluster	NOUN
cjfa-8193	75	6	can	can	AUX
cjfa-8193	75	7	be	be	AUX
cjfa-8193	75	8	observed	observe	VERB
cjfa-8193	75	9	in	in	ADP
cjfa-8193	75	10	the	the	DET
cjfa-8193	75	11	returns	return	NOUN
cjfa-8193	75	12	data	datum	NOUN
cjfa-8193	75	13	;	;	PUNCT
cjfa-8193	75	14	for	for	ADP
cjfa-8193	75	15	example	example	NOUN
cjfa-8193	75	16	,	,	PUNCT
cjfa-8193	75	17	a	a	DET
cjfa-8193	75	18	cluster	cluster	NOUN
cjfa-8193	75	19	corresponding	correspond	VERB
cjfa-8193	75	20	to	to	ADP
cjfa-8193	75	21	the	the	DET
cjfa-8193	75	22	2007	2007	NUM
cjfa-8193	75	23	-	-	SYM
cjfa-8193	75	24	09	09	NUM
cjfa-8193	75	25	global	global	ADJ
cjfa-8193	75	26	financial	financial	ADJ
cjfa-8193	75	27	crisis	crisis	NOUN
cjfa-8193	75	28	.	.	PUNCT
cjfa-8193	76	1	figure	figure	NOUN
cjfa-8193	76	2	1	1	NUM
cjfa-8193	76	3	.	.	PUNCT
cjfa-8193	77	1	daily	daily	ADJ
cjfa-8193	77	2	jordanian	jordanian	ADJ
cjfa-8193	77	3	price	price	NOUN
cjfa-8193	77	4	index	index	NOUN
cjfa-8193	77	5	january	january	PROPN
cjfa-8193	77	6	2000	2000	NUM
cjfa-8193	77	7	–	–	PUNCT
cjfa-8193	77	8	november	november	PROPN
cjfa-8193	77	9	2014	2014	NUM
cjfa-8193	77	10	]	]	X
cjfa-8193	77	11	1[lnln	1[lnln	NUM
cjfa-8193	77	12	1	1	NOUN
cjfa-8193	77	13	ttt	ttt	NOUN
cjfa-8193	77	14	ppr	ppr	NOUN
cjfa-8193	78	1	[	[	X
cjfa-8193	78	2	1	1	NUM
cjfa-8193	78	3	]	]	X
cjfa-8193	78	4	ase	ase	NOUN
cjfa-8193	78	5	index	index	NOUN
cjfa-8193	78	6	closing	closing	NOUN
cjfa-8193	78	7	prices	price	NOUN
cjfa-8193	78	8	are	be	AUX
cjfa-8193	78	9	presented	present	VERB
cjfa-8193	78	10	in	in	ADP
cjfa-8193	78	11	figure	figure	NOUN
cjfa-8193	78	12	1	1	NUM
cjfa-8193	78	13	and	and	CCONJ
cjfa-8193	78	14	the	the	DET
cjfa-8193	78	15	daily	daily	ADJ
cjfa-8193	78	16	returns	return	NOUN
cjfa-8193	78	17	in	in	ADP
cjfa-8193	78	18	figure	figure	NOUN
cjfa-8193	78	19	2	2	NUM
cjfa-8193	78	20	.	.	PUNCT
cjfa-8193	79	1	a	a	DET
cjfa-8193	79	2	number	number	NOUN
cjfa-8193	79	3	of	of	ADP
cjfa-8193	79	4	volatility	volatility	NOUN
cjfa-8193	79	5	clusters	cluster	NOUN
cjfa-8193	79	6	can	can	AUX
cjfa-8193	79	7	be	be	AUX
cjfa-8193	79	8	observed	observe	VERB
cjfa-8193	79	9	in	in	ADP
cjfa-8193	79	10	the	the	DET
cjfa-8193	79	11	returns	return	NOUN
cjfa-8193	79	12	data	datum	NOUN
cjfa-8193	79	13	;	;	PUNCT
cjfa-8193	79	14	for	for	ADP
cjfa-8193	79	15	example	example	NOUN
cjfa-8193	79	16	,	,	PUNCT
cjfa-8193	79	17	a	a	DET
cjfa-8193	79	18	cluster	cluster	NOUN
cjfa-8193	79	19	corresponding	correspond	VERB
cjfa-8193	79	20	to	to	ADP
cjfa-8193	79	21	the	the	DET
cjfa-8193	79	22	2007	2007	NUM
cjfa-8193	79	23	-	-	SYM
cjfa-8193	79	24	09	09	NUM
cjfa-8193	79	25	global	global	ADJ
cjfa-8193	79	26	financial	financial	ADJ
cjfa-8193	79	27	crisis	crisis	NOUN
cjfa-8193	79	28	.	.	PUNCT
cjfa-8193	80	1	figure	figure	NOUN
cjfa-8193	80	2	1	1	NUM
cjfa-8193	80	3	.	.	PUNCT
cjfa-8193	81	1	daily	daily	ADJ
cjfa-8193	81	2	jordanian	jordanian	ADJ
cjfa-8193	81	3	price	price	NOUN
cjfa-8193	81	4	index	index	NOUN
cjfa-8193	81	5	january	january	PROPN
cjfa-8193	81	6	2000	2000	NUM
cjfa-8193	81	7	–	–	PUNCT
cjfa-8193	81	8	november	november	PROPN
cjfa-8193	81	9	2014	2014	NUM
cjfa-8193	81	10	s	s	PART
cjfa-8193	81	11	o	o	NOUN
cjfa-8193	81	12	u	u	NOUN
cjfa-8193	81	13	r	r	NOUN
cjfa-8193	81	14	c	c	NOUN
cjfa-8193	81	15	e	e	NOUN
cjfa-8193	81	16	:	:	PUNCT
cjfa-8193	81	17	created	create	VERB
cjfa-8193	81	18	by	by	ADP
cjfa-8193	81	19	the	the	DET
cjfa-8193	81	20	authors	author	NOUN
cjfa-8193	81	21	using	use	VERB
cjfa-8193	81	22	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	81	23	7	7	NUM
cjfa-8193	81	24	software	software	NOUN
cjfa-8193	81	25	and	and	CCONJ
cjfa-8193	81	26	data	datum	NOUN
cjfa-8193	81	27	from	from	ADP
cjfa-8193	81	28	thomson	thomson	PROPN
cjfa-8193	81	29	reuters	reuters	PROPN
cjfa-8193	81	30	eikontm	eikontm	PROPN
cjfa-8193	81	31	.	.	PUNCT
cjfa-8193	82	1	a	a	DET
cjfa-8193	82	2	preliminary	preliminary	ADJ
cjfa-8193	82	3	statistical	statistical	ADJ
cjfa-8193	82	4	analysis	analysis	NOUN
cjfa-8193	82	5	of	of	ADP
cjfa-8193	82	6	the	the	DET
cjfa-8193	82	7	daily	daily	ADJ
cjfa-8193	82	8	returns	return	NOUN
cjfa-8193	82	9	is	be	AUX
cjfa-8193	82	10	presented	present	VERB
cjfa-8193	82	11	in	in	ADP
cjfa-8193	82	12	table	table	NOUN
cjfa-8193	82	13	1	1	NUM
cjfa-8193	82	14	.	.	PUNCT
cjfa-8193	83	1	it	it	PRON
cjfa-8193	83	2	can	can	AUX
cjfa-8193	83	3	be	be	AUX
cjfa-8193	83	4	noted	note	VERB
cjfa-8193	83	5	that	that	SCONJ
cjfa-8193	83	6	average	average	ADJ
cjfa-8193	83	7	daily	daily	ADJ
cjfa-8193	83	8	returns	return	NOUN
cjfa-8193	83	9	are	be	AUX
cjfa-8193	83	10	small	small	ADJ
cjfa-8193	83	11	relative	relative	ADJ
cjfa-8193	83	12	to	to	ADP
cjfa-8193	83	13	the	the	DET
cjfa-8193	83	14	standard	standard	ADJ
cjfa-8193	83	15	deviation	deviation	NOUN
cjfa-8193	83	16	.	.	PUNCT
cjfa-8193	84	1	the	the	DET
cjfa-8193	84	2	series	series	NOUN
cjfa-8193	84	3	also	also	ADV
cjfa-8193	84	4	displays	display	VERB
cjfa-8193	84	5	negative	negative	ADJ
cjfa-8193	84	6	skewness	skewness	NOUN
cjfa-8193	84	7	and	and	CCONJ
cjfa-8193	84	8	strong	strong	ADJ
cjfa-8193	84	9	positive	positive	ADJ
cjfa-8193	84	10	kurtosis	kurtosis	NOUN
cjfa-8193	84	11	;	;	PUNCT
cjfa-8193	84	12	these	these	PRON
cjfa-8193	84	13	are	be	AUX
cjfa-8193	84	14	indicative	indicative	ADJ
cjfa-8193	84	15	of	of	ADP
cjfa-8193	84	16	a	a	DET
cjfa-8193	84	17	heavy	heavy	ADJ
cjfa-8193	84	18	tailed	tailed	ADJ
cjfa-8193	84	19	non	non	ADJ
cjfa-8193	84	20	-	-	ADJ
cjfa-8193	84	21	gaussian	gaussian	ADJ
cjfa-8193	84	22	distribution	distribution	NOUN
cjfa-8193	84	23	.	.	PUNCT
cjfa-8193	85	1	table	table	NOUN
cjfa-8193	85	2	1	1	NUM
cjfa-8193	85	3	.	.	PUNCT
cjfa-8193	85	4	descriptive	descriptive	ADJ
cjfa-8193	85	5	statistics	statistic	NOUN
cjfa-8193	85	6	of	of	ADP
cjfa-8193	85	7	daily	daily	ADJ
cjfa-8193	85	8	returns	return	NOUN
cjfa-8193	85	9	january	january	PROPN
cjfa-8193	85	10	2000	2000	NUM
cjfa-8193	85	11	–	–	PUNCT
cjfa-8193	85	12	november	november	PROPN
cjfa-8193	85	13	2014	2014	NUM
cjfa-8193	85	14	mean	mean	NOUN
cjfa-8193	85	15	std	std	PROPN
cjfa-8193	85	16	.	.	PROPN
cjfa-8193	85	17	dev	dev	PROPN
cjfa-8193	85	18	min	min	PROPN
cjfa-8193	85	19	max	max	PROPN
cjfa-8193	85	20	skewness	skewness	PROPN
cjfa-8193	85	21	excess	excess	ADJ
cjfa-8193	85	22	kurtosis	kurtosis	NOUN
cjfa-8193	85	23	j	j	PROPN
cjfa-8193	85	24	-	-	PUNCT
cjfa-8193	85	25	b	b	PROPN
cjfa-8193	85	26	test	test	NOUN
cjfa-8193	85	27	arch	arch	NOUN
cjfa-8193	85	28	test1	test1	PROPN
cjfa-8193	85	29	l	l	PROPN
cjfa-8193	85	30	-	-	PROPN
cjfa-8193	85	31	b	b	PROPN
cjfa-8193	85	32	test1	test1	PROPN
cjfa-8193	85	33	adf	adf	PROPN
cjfa-8193	85	34	test	test	VERB
cjfa-8193	85	35	0.025	0.025	NUM
cjfa-8193	85	36	0.946	0.946	NUM
cjfa-8193	85	37	-6.428	-6.428	PUNCT
cjfa-8193	85	38	6.198	6.198	NUM
cjfa-8193	85	39	-0.363	-0.363	NOUN
cjfa-8193	85	40	6.167	6.167	NUM
cjfa-8193	85	41	5872.2	5872.2	NUM
cjfa-8193	85	42	*	*	SYM
cjfa-8193	85	43	*	*	NOUN
cjfa-8193	86	1	107.9	107.9	NUM
cjfa-8193	86	2	*	*	SYM
cjfa-8193	86	3	*	*	PUNCT
cjfa-8193	86	4	2571	2571	NUM
cjfa-8193	86	5	*	*	PUNCT
cjfa-8193	86	6	*	*	PUNCT
cjfa-8193	87	1	-32.8	-32.8	PUNCT
cjfa-8193	87	2	*	*	PUNCT
cjfa-8193	87	3	*	*	PUNCT
cjfa-8193	88	1	*	*	PUNCT
cjfa-8193	88	2	*	*	PUNCT
cjfa-8193	88	3	 	 	SPACE
cjfa-8193	88	4	significant	significant	ADJ
cjfa-8193	88	5	at	at	ADP
cjfa-8193	88	6	1	1	NUM
cjfa-8193	88	7	%	%	NOUN
cjfa-8193	88	8	.	.	PUNCT
cjfa-8193	89	1	1both	1both	NUM
cjfa-8193	89	2	the	the	DET
cjfa-8193	89	3	ljung	ljung	PROPN
cjfa-8193	89	4	-	-	PUNCT
cjfa-8193	89	5	box	box	NOUN
cjfa-8193	89	6	and	and	CCONJ
cjfa-8193	89	7	the	the	DET
cjfa-8193	89	8	arch	arch	ADJ
cjfa-8193	89	9	tests	test	NOUN
cjfa-8193	89	10	use	use	VERB
cjfa-8193	89	11	10	10	NUM
cjfa-8193	89	12	lags	lag	NOUN
cjfa-8193	89	13	.	.	PUNCT
cjfa-8193	90	1	s	s	PART
cjfa-8193	90	2	o	o	X
cjfa-8193	90	3	u	u	NOUN
cjfa-8193	90	4	r	r	NOUN
cjfa-8193	90	5	c	c	NOUN
cjfa-8193	90	6	e	e	NOUN
cjfa-8193	90	7	:	:	PUNCT
cjfa-8193	90	8	estimated	estimate	VERB
cjfa-8193	90	9	by	by	ADP
cjfa-8193	90	10	the	the	DET
cjfa-8193	90	11	authors	author	NOUN
cjfa-8193	90	12	using	use	VERB
cjfa-8193	90	13	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	90	14	7	7	NUM
cjfa-8193	90	15	.	.	PUNCT
cjfa-8193	91	1	h.	h.	PROPN
cjfa-8193	91	2	al	al	PROPN
cjfa-8193	91	3	-	-	PUNCT
cjfa-8193	91	4	hajieh	hajieh	PROPN
cjfa-8193	91	5	,	,	PUNCT
cjfa-8193	91	6	h.	h.	PROPN
cjfa-8193	91	7	alnemer	alnemer	PROPN
cjfa-8193	91	8	,	,	PUNCT
cjfa-8193	91	9	t.	t.	PROPN
cjfa-8193	91	10	rodgers	rodgers	PROPN
cjfa-8193	91	11	,	,	PUNCT
cjfa-8193	91	12	j.	j.	PROPN
cjfa-8193	91	13	niklewski14	niklewski14	PROPN
cjfa-8193	91	14	figure	figure	NOUN
cjfa-8193	91	15	2	2	NUM
cjfa-8193	91	16	.	.	X
cjfa-8193	92	1	jordanian	jordanian	ADJ
cjfa-8193	92	2	daily	daily	ADJ
cjfa-8193	92	3	percentage	percentage	NOUN
cjfa-8193	92	4	returns	return	NOUN
cjfa-8193	92	5	january	january	PROPN
cjfa-8193	92	6	2000	2000	NUM
cjfa-8193	92	7	–	–	PUNCT
cjfa-8193	92	8	november	november	PROPN
cjfa-8193	92	9	2014	2014	NUM
cjfa-8193	92	10	s	s	PART
cjfa-8193	92	11	o	o	NOUN
cjfa-8193	92	12	u	u	NOUN
cjfa-8193	92	13	r	r	NOUN
cjfa-8193	92	14	c	c	NOUN
cjfa-8193	92	15	e	e	NOUN
cjfa-8193	92	16	:	:	PUNCT
cjfa-8193	92	17	created	create	VERB
cjfa-8193	92	18	by	by	ADP
cjfa-8193	92	19	the	the	DET
cjfa-8193	92	20	authors	author	NOUN
cjfa-8193	92	21	using	use	VERB
cjfa-8193	92	22	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	92	23	7	7	NUM
cjfa-8193	92	24	.	.	PUNCT
cjfa-8193	93	1	this	this	PRON
cjfa-8193	93	2	is	be	AUX
cjfa-8193	93	3	confirmed	confirm	VERB
cjfa-8193	93	4	by	by	ADP
cjfa-8193	93	5	the	the	DET
cjfa-8193	93	6	jarque	jarque	NOUN
cjfa-8193	93	7	-	-	PUNCT
cjfa-8193	93	8	bera	bera	NOUN
cjfa-8193	93	9	test	test	NOUN
cjfa-8193	93	10	which	which	PRON
cjfa-8193	93	11	rejects	reject	VERB
cjfa-8193	93	12	unconditional	unconditional	ADJ
cjfa-8193	93	13	normality	normality	NOUN
cjfa-8193	93	14	and	and	CCONJ
cjfa-8193	93	15	further	further	ADJ
cjfa-8193	93	16	confirmatory	confirmatory	ADJ
cjfa-8193	93	17	evidence	evidence	NOUN
cjfa-8193	93	18	is	be	AUX
cjfa-8193	93	19	provided	provide	VERB
cjfa-8193	93	20	in	in	ADP
cjfa-8193	93	21	the	the	DET
cjfa-8193	93	22	related	relate	VERB
cjfa-8193	93	23	histogram	histogram	NOUN
cjfa-8193	93	24	(	(	PUNCT
cjfa-8193	93	25	figure	figure	NOUN
cjfa-8193	93	26	3	3	NUM
cjfa-8193	93	27	)	)	PUNCT
cjfa-8193	93	28	.	.	PUNCT
cjfa-8193	94	1	figure	figure	VERB
cjfa-8193	94	2	3	3	NUM
cjfa-8193	94	3	.	.	PUNCT
cjfa-8193	94	4	histogram	histogram	NOUN
cjfa-8193	94	5	of	of	ADP
cjfa-8193	94	6	jordanian	jordanian	ADJ
cjfa-8193	94	7	daily	daily	ADJ
cjfa-8193	94	8	returns	return	NOUN
cjfa-8193	94	9	january	january	PROPN
cjfa-8193	94	10	2000	2000	NUM
cjfa-8193	94	11	–	–	PUNCT
cjfa-8193	94	12	november	november	PROPN
cjfa-8193	94	13	2014	2014	NUM
cjfa-8193	94	14	s	s	PART
cjfa-8193	94	15	o	o	NOUN
cjfa-8193	94	16	u	u	NOUN
cjfa-8193	94	17	r	r	NOUN
cjfa-8193	94	18	c	c	NOUN
cjfa-8193	94	19	e	e	NOUN
cjfa-8193	94	20	:	:	PUNCT
cjfa-8193	94	21	created	create	VERB
cjfa-8193	94	22	by	by	ADP
cjfa-8193	94	23	the	the	DET
cjfa-8193	94	24	authors	author	NOUN
cjfa-8193	94	25	using	use	VERB
cjfa-8193	94	26	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	94	27	7	7	NUM
cjfa-8193	94	28	.	.	PUNCT
cjfa-8193	95	1	forecasting	forecast	VERB
cjfa-8193	95	2	the	the	DET
cjfa-8193	95	3	jordanian	jordanian	ADJ
cjfa-8193	95	4	stock	stock	NOUN
cjfa-8193	95	5	index	index	PROPN
cjfa-8193	95	6	…	…	PUNCT
cjfa-8193	95	7	15	15	NUM
cjfa-8193	95	8	the	the	DET
cjfa-8193	95	9	ljung	ljung	PROPN
cjfa-8193	95	10	-	-	PUNCT
cjfa-8193	95	11	box	box	NOUN
cjfa-8193	95	12	q	q	NOUN
cjfa-8193	95	13	-	-	PUNCT
cjfa-8193	95	14	test	test	NOUN
cjfa-8193	95	15	and	and	CCONJ
cjfa-8193	95	16	the	the	DET
cjfa-8193	95	17	arch	arch	ADJ
cjfa-8193	95	18	tests	test	NOUN
cjfa-8193	95	19	suggest	suggest	VERB
cjfa-8193	95	20	autocorrelation	autocorrelation	NOUN
cjfa-8193	95	21	and	and	CCONJ
cjfa-8193	95	22	hetroskedasticity	hetroskedasticity	NOUN
cjfa-8193	95	23	within	within	ADP
cjfa-8193	95	24	the	the	DET
cjfa-8193	95	25	data	datum	NOUN
cjfa-8193	95	26	and	and	CCONJ
cjfa-8193	95	27	the	the	DET
cjfa-8193	95	28	adf	adf	PROPN
cjfa-8193	95	29	(	(	PUNCT
cjfa-8193	95	30	augmented	augment	VERB
cjfa-8193	95	31	dickey	dickey	NOUN
cjfa-8193	95	32	-	-	PUNCT
cjfa-8193	95	33	fuller	fuller	NOUN
cjfa-8193	95	34	)	)	PUNCT
cjfa-8193	95	35	unit	unit	NOUN
cjfa-8193	95	36	root	root	PROPN
cjfa-8193	95	37	test	test	NOUN
cjfa-8193	95	38	rejects	reject	VERB
cjfa-8193	95	39	the	the	DET
cjfa-8193	95	40	null	null	ADJ
cjfa-8193	95	41	hypothesis	hypothesis	NOUN
cjfa-8193	95	42	of	of	ADP
cjfa-8193	95	43	data	datum	NOUN
cjfa-8193	95	44	non	non	ADJ
cjfa-8193	95	45	-	-	ADJ
cjfa-8193	95	46	stationary	stationary	ADJ
cjfa-8193	95	47	.	.	PUNCT
cjfa-8193	96	1	the	the	DET
cjfa-8193	96	2	research	research	NOUN
cjfa-8193	96	3	methodology	methodology	NOUN
cjfa-8193	96	4	a	a	DET
cjfa-8193	96	5	total	total	NOUN
cjfa-8193	96	6	of	of	ADP
cjfa-8193	96	7	12	12	NUM
cjfa-8193	96	8	garch	garch	NOUN
cjfa-8193	96	9	-	-	PUNCT
cjfa-8193	96	10	model	model	NOUN
cjfa-8193	96	11	-	-	PUNCT
cjfa-8193	96	12	specification	specification	NOUN
cjfa-8193	96	13	/	/	SYM
cjfa-8193	96	14	distribution	distribution	NOUN
cjfa-8193	96	15	pairs	pair	NOUN
cjfa-8193	96	16	are	be	AUX
cjfa-8193	96	17	tested	test	VERB
cjfa-8193	96	18	with	with	ADP
cjfa-8193	96	19	the	the	DET
cjfa-8193	96	20	results	result	NOUN
cjfa-8193	96	21	being	be	AUX
cjfa-8193	96	22	presented	present	VERB
cjfa-8193	96	23	in	in	ADP
cjfa-8193	96	24	tables	table	NOUN
cjfa-8193	96	25	3–7	3–7	NOUN
cjfa-8193	96	26	.	.	PUNCT
cjfa-8193	97	1	the	the	DET
cjfa-8193	97	2	models	model	NOUN
cjfa-8193	97	3	tested	test	VERB
cjfa-8193	97	4	are	be	AUX
cjfa-8193	97	5	:	:	PUNCT
cjfa-8193	97	6	garchbased	garchbased	ADJ
cjfa-8193	97	7	specifications	specification	NOUN
cjfa-8193	97	8	(	(	PUNCT
cjfa-8193	97	9	garch	garch	NOUN
cjfa-8193	97	10	-	-	PUNCT
cjfa-8193	97	11	n	n	NOUN
cjfa-8193	97	12	,	,	PUNCT
cjfa-8193	97	13	garch	garch	NOUN
cjfa-8193	97	14	-	-	PUNCT
cjfa-8193	97	15	t	t	NOUN
cjfa-8193	97	16	,	,	PUNCT
cjfa-8193	97	17	garch	garch	NOUN
cjfa-8193	97	18	-	-	PUNCT
cjfa-8193	97	19	ged	ge	VERB
cjfa-8193	97	20	and	and	CCONJ
cjfa-8193	97	21	garch	garch	NOUN
cjfa-8193	97	22	-	-	PUNCT
cjfa-8193	97	23	st)1	st)1	PROPN
cjfa-8193	97	24	;	;	PUNCT
cjfa-8193	97	25	and	and	CCONJ
cjfa-8193	97	26	two	two	NUM
cjfa-8193	97	27	sets	set	NOUN
cjfa-8193	97	28	of	of	ADP
cjfa-8193	97	29	asymmetry	asymmetry	NOUN
cjfa-8193	97	30	-	-	PUNCT
cjfa-8193	97	31	type	type	NOUN
cjfa-8193	97	32	specifications	specification	NOUN
cjfa-8193	97	33	:	:	PUNCT
cjfa-8193	97	34	(	(	PUNCT
cjfa-8193	97	35	i	i	NOUN
cjfa-8193	97	36	)	)	PUNCT
cjfa-8193	97	37	egarch	egarch	NOUN
cjfa-8193	97	38	(	(	PUNCT
cjfa-8193	97	39	egarch	egarch	NOUN
cjfa-8193	97	40	-	-	PUNCT
cjfa-8193	97	41	n	n	CCONJ
cjfa-8193	97	42	,	,	PUNCT
cjfa-8193	97	43	egarch	egarch	NOUN
cjfa-8193	97	44	-	-	PUNCT
cjfa-8193	97	45	t	t	NOUN
cjfa-8193	97	46	,	,	PUNCT
cjfa-8193	97	47	egarch	egarch	NOUN
cjfa-8193	97	48	-	-	PUNCT
cjfa-8193	97	49	ged	ge	VERB
cjfa-8193	97	50	and	and	CCONJ
cjfa-8193	97	51	egarch	egarch	NOUN
cjfa-8193	97	52	-	-	PUNCT
cjfa-8193	97	53	st	st	NOUN
cjfa-8193	97	54	)	)	PUNCT
cjfa-8193	97	55	and	and	CCONJ
cjfa-8193	97	56	(	(	PUNCT
cjfa-8193	97	57	ii	ii	NOUN
cjfa-8193	97	58	)	)	PUNCT
cjfa-8193	97	59	gjr	gjr	NOUN
cjfa-8193	97	60	-	-	PUNCT
cjfa-8193	97	61	garch	garch	NOUN
cjfa-8193	97	62	(	(	PUNCT
cjfa-8193	97	63	gjr	gjr	NOUN
cjfa-8193	97	64	-	-	PUNCT
cjfa-8193	97	65	garch	garch	NOUN
cjfa-8193	97	66	-	-	PUNCT
cjfa-8193	97	67	n	n	NOUN
cjfa-8193	97	68	,	,	PUNCT
cjfa-8193	97	69	gjr-	gjr-	ADJ
cjfa-8193	97	70	 	 	SPACE
cjfa-8193	97	71	garch-	garch-	PROPN
cjfa-8193	97	72	 	 	SPACE
cjfa-8193	97	73	t	t	PROPN
cjfa-8193	97	74	,	,	PUNCT
cjfa-8193	97	75	gjr	gjr	NOUN
cjfa-8193	97	76	 	 	SPACE
cjfa-8193	97	77	garch	garch	NOUN
cjfa-8193	97	78	-	-	PUNCT
cjfa-8193	97	79	ged	ge	VERB
cjfa-8193	97	80	and	and	CCONJ
cjfa-8193	97	81	gjrgarch	gjrgarch	NOUN
cjfa-8193	97	82	-	-	PUNCT
cjfa-8193	97	83	st	st	PROPN
cjfa-8193	97	84	)	)	PUNCT
cjfa-8193	97	85	.	.	PUNCT
cjfa-8193	98	1	the	the	DET
cjfa-8193	98	2	alternative	alternative	ADJ
cjfa-8193	98	3	models	model	NOUN
cjfa-8193	98	4	are	be	AUX
cjfa-8193	98	5	subsequently	subsequently	ADV
cjfa-8193	98	6	evaluated	evaluate	VERB
cjfa-8193	98	7	by	by	ADP
cjfa-8193	98	8	:	:	PUNCT
cjfa-8193	98	9	(	(	PUNCT
cjfa-8193	98	10	i	i	NOUN
cjfa-8193	98	11	)	)	PUNCT
cjfa-8193	98	12	an	an	DET
cjfa-8193	98	13	evaluation	evaluation	NOUN
cjfa-8193	98	14	of	of	ADP
cjfa-8193	98	15	model	model	NOUN
cjfa-8193	98	16	parameters	parameter	NOUN
cjfa-8193	98	17	and	and	CCONJ
cjfa-8193	98	18	(	(	PUNCT
cjfa-8193	98	19	ii	ii	NOUN
cjfa-8193	98	20	)	)	PUNCT
cjfa-8193	98	21	an	an	DET
cjfa-8193	98	22	evaluation	evaluation	NOUN
cjfa-8193	98	23	of	of	ADP
cjfa-8193	98	24	model	model	NOUN
cjfa-8193	98	25	forecasting	forecasting	NOUN
cjfa-8193	98	26	performance	performance	NOUN
cjfa-8193	98	27	.	.	PUNCT
cjfa-8193	99	1	for	for	ADP
cjfa-8193	99	2	robustness	robustness	NOUN
cjfa-8193	99	3	,	,	PUNCT
cjfa-8193	99	4	the	the	DET
cjfa-8193	99	5	latter	latter	ADJ
cjfa-8193	99	6	undertakes	undertake	VERB
cjfa-8193	99	7	a	a	DET
cjfa-8193	99	8	series	series	NOUN
cjfa-8193	99	9	of	of	ADP
cjfa-8193	99	10	tests	test	NOUN
cjfa-8193	99	11	using	use	VERB
cjfa-8193	99	12	both	both	CCONJ
cjfa-8193	99	13	the	the	DET
cjfa-8193	99	14	superior	superior	ADJ
cjfa-8193	99	15	predictive	predictive	ADJ
cjfa-8193	99	16	ability	ability	NOUN
cjfa-8193	99	17	(	(	PUNCT
cjfa-8193	99	18	spa	spa	NOUN
cjfa-8193	99	19	)	)	PUNCT
cjfa-8193	99	20	test	test	NOUN
cjfa-8193	99	21	hansen	hansen	NOUN
cjfa-8193	99	22	(	(	PUNCT
cjfa-8193	99	23	2005	2005	NUM
cjfa-8193	99	24	)	)	PUNCT
cjfa-8193	99	25	and	and	CCONJ
cjfa-8193	99	26	the	the	DET
cjfa-8193	99	27	model	model	NOUN
cjfa-8193	99	28	confidence	confidence	NOUN
cjfa-8193	99	29	set	set	NOUN
cjfa-8193	99	30	(	(	PUNCT
cjfa-8193	99	31	mcs	mcs	NOUN
cjfa-8193	99	32	)	)	PUNCT
cjfa-8193	99	33	test	test	NOUN
cjfa-8193	99	34	(	(	PUNCT
cjfa-8193	99	35	hansen	hansen	PROPN
cjfa-8193	99	36	,	,	PUNCT
cjfa-8193	99	37	lunde	lunde	PROPN
cjfa-8193	99	38	,	,	PUNCT
cjfa-8193	99	39	and	and	CCONJ
cjfa-8193	99	40	nason	nason	PROPN
cjfa-8193	99	41	2011	2011	NUM
cjfa-8193	99	42	)	)	PUNCT
cjfa-8193	99	43	.	.	PUNCT
cjfa-8193	100	1	both	both	PRON
cjfa-8193	100	2	are	be	AUX
cjfa-8193	100	3	available	available	ADJ
cjfa-8193	100	4	in	in	ADP
cjfa-8193	100	5	the	the	DET
cjfa-8193	100	6	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	100	7	72	72	NUM
cjfa-8193	100	8	software	software	NOUN
cjfa-8193	100	9	package	package	NOUN
cjfa-8193	100	10	used	use	VERB
cjfa-8193	100	11	in	in	ADP
cjfa-8193	100	12	this	this	DET
cjfa-8193	100	13	paper	paper	NOUN
cjfa-8193	100	14	.	.	PUNCT
cjfa-8193	101	1	the	the	DET
cjfa-8193	101	2	forecast	forecast	NOUN
cjfa-8193	101	3	-	-	PUNCT
cjfa-8193	101	4	based	base	VERB
cjfa-8193	101	5	tests	test	NOUN
cjfa-8193	101	6	use	use	VERB
cjfa-8193	101	7	a	a	DET
cjfa-8193	101	8	‘	'	PUNCT
cjfa-8193	101	9	loss	loss	NOUN
cjfa-8193	101	10	-	-	PUNCT
cjfa-8193	101	11	function	function	NOUN
cjfa-8193	101	12	’	'	PUNCT
cjfa-8193	101	13	to	to	PART
cjfa-8193	101	14	identify	identify	VERB
cjfa-8193	101	15	the	the	DET
cjfa-8193	101	16	most	most	ADV
cjfa-8193	101	17	efficient	efficient	ADJ
cjfa-8193	101	18	model	model	NOUN
cjfa-8193	101	19	.	.	PUNCT
cjfa-8193	102	1	the	the	DET
cjfa-8193	102	2	loss	loss	NOUN
cjfa-8193	102	3	function	function	NOUN
cjfa-8193	102	4	can	can	AUX
cjfa-8193	102	5	be	be	AUX
cjfa-8193	102	6	estimated	estimate	VERB
cjfa-8193	102	7	using	use	VERB
cjfa-8193	102	8	mean	mean	NOUN
cjfa-8193	102	9	squared	square	VERB
cjfa-8193	102	10	error	error	NOUN
cjfa-8193	102	11	(	(	PUNCT
cjfa-8193	102	12	mse	mse	NOUN
cjfa-8193	102	13	)	)	PUNCT
cjfa-8193	102	14	and	and	CCONJ
cjfa-8193	102	15	mean	mean	VERB
cjfa-8193	102	16	absolute	absolute	ADJ
cjfa-8193	102	17	deviation	deviation	NOUN
cjfa-8193	102	18	(	(	PUNCT
cjfa-8193	102	19	mad	mad	ADJ
cjfa-8193	102	20	)	)	PUNCT
cjfa-8193	102	21	statistics	statistic	NOUN
cjfa-8193	102	22	.	.	PUNCT
cjfa-8193	103	1	spa	spa	NOUN
cjfa-8193	103	2	identifies	identify	VERB
cjfa-8193	103	3	the	the	DET
cjfa-8193	103	4	‘	'	PUNCT
cjfa-8193	103	5	best	good	ADJ
cjfa-8193	103	6	’	'	PUNCT
cjfa-8193	103	7	model	model	NOUN
cjfa-8193	103	8	in	in	ADP
cjfa-8193	103	9	terms	term	NOUN
cjfa-8193	103	10	of	of	ADP
cjfa-8193	103	11	predictive	predictive	ADJ
cjfa-8193	103	12	ability	ability	NOUN
cjfa-8193	103	13	and	and	CCONJ
cjfa-8193	103	14	mcs	mcs	PROPN
cjfa-8193	103	15	identifies	identify	VERB
cjfa-8193	103	16	the	the	DET
cjfa-8193	103	17	‘	'	PUNCT
cjfa-8193	103	18	best	good	ADJ
cjfa-8193	103	19	’	'	PUNCT
cjfa-8193	103	20	model	model	NOUN
cjfa-8193	103	21	set	set	NOUN
cjfa-8193	103	22	.	.	PUNCT
cjfa-8193	104	1	the	the	DET
cjfa-8193	104	2	model	model	NOUN
cjfa-8193	104	3	specifications	specification	NOUN
cjfa-8193	104	4	and	and	CCONJ
cjfa-8193	104	5	the	the	DET
cjfa-8193	104	6	distributions	distribution	NOUN
cjfa-8193	104	7	tested	test	VERB
cjfa-8193	104	8	are	be	AUX
cjfa-8193	104	9	identified	identify	VERB
cjfa-8193	104	10	below	below	ADV
cjfa-8193	104	11	.	.	PUNCT
cjfa-8193	105	1	they	they	PRON
cjfa-8193	105	2	consist	consist	VERB
cjfa-8193	105	3	of	of	ADP
cjfa-8193	105	4	three	three	NUM
cjfa-8193	105	5	different	different	ADJ
cjfa-8193	105	6	conditional	conditional	ADJ
cjfa-8193	105	7	volatility	volatility	NOUN
cjfa-8193	105	8	specifications	specification	NOUN
cjfa-8193	105	9	and	and	CCONJ
cjfa-8193	105	10	four	four	NUM
cjfa-8193	105	11	different	different	ADJ
cjfa-8193	105	12	statistical	statistical	ADJ
cjfa-8193	105	13	distributions	distribution	NOUN
cjfa-8193	105	14	.	.	PUNCT
cjfa-8193	106	1	(	(	PUNCT
cjfa-8193	106	2	i	i	NOUN
cjfa-8193	106	3	)	)	PUNCT
cjfa-8193	106	4	 	 	SPACE
cjfa-8193	106	5	garch	garch	VERB
cjfa-8193	106	6	the	the	DET
cjfa-8193	106	7	garch	garch	NOUN
cjfa-8193	106	8	model	model	NOUN
cjfa-8193	106	9	,	,	PUNCT
cjfa-8193	106	10	as	as	SCONJ
cjfa-8193	106	11	introduced	introduce	VERB
cjfa-8193	106	12	by	by	ADP
cjfa-8193	106	13	bollerslev	bollerslev	ADJ
cjfa-8193	106	14	(	(	PUNCT
cjfa-8193	106	15	1986	1986	NUM
cjfa-8193	106	16	)	)	PUNCT
cjfa-8193	106	17	,	,	PUNCT
cjfa-8193	106	18	is	be	AUX
cjfa-8193	106	19	a	a	DET
cjfa-8193	106	20	generalisation	generalisation	NOUN
cjfa-8193	106	21	of	of	ADP
cjfa-8193	106	22	the	the	DET
cjfa-8193	106	23	arch	arch	ADJ
cjfa-8193	106	24	specification	specification	NOUN
cjfa-8193	106	25	of	of	ADP
cjfa-8193	106	26	engle	engle	PROPN
cjfa-8193	106	27	(	(	PUNCT
cjfa-8193	106	28	1982	1982	NUM
cjfa-8193	106	29	)	)	PUNCT
cjfa-8193	106	30	.	.	PUNCT
cjfa-8193	107	1	the	the	DET
cjfa-8193	107	2	model	model	NOUN
cjfa-8193	107	3	specifies	specifie	NOUN
cjfa-8193	107	4	that	that	PRON
cjfa-8193	107	5	the	the	DET
cjfa-8193	107	6	conditional	conditional	ADJ
cjfa-8193	107	7	variance	variance	NOUN
cjfa-8193	107	8	is	be	AUX
cjfa-8193	107	9	a	a	DET
cjfa-8193	107	10	function	function	NOUN
cjfa-8193	107	11	of	of	ADP
cjfa-8193	107	12	the	the	DET
cjfa-8193	107	13	lagged	lag	VERB
cjfa-8193	107	14	squared	square	VERB
cjfa-8193	107	15	residuals	residual	NOUN
cjfa-8193	107	16	as	as	ADV
cjfa-8193	107	17	well	well	ADV
cjfa-8193	107	18	as	as	ADP
cjfa-8193	107	19	of	of	ADP
cjfa-8193	107	20	its	its	PRON
cjfa-8193	107	21	past	past	ADJ
cjfa-8193	107	22	conditional	conditional	ADJ
cjfa-8193	107	23	variances	variance	NOUN
cjfa-8193	107	24	.	.	PUNCT
cjfa-8193	108	1	although	although	SCONJ
cjfa-8193	108	2	the	the	DET
cjfa-8193	108	3	equation	equation	NOUN
cjfa-8193	108	4	may	may	AUX
cjfa-8193	108	5	be	be	AUX
cjfa-8193	108	6	specified	specify	VERB
cjfa-8193	108	7	with	with	ADP
cjfa-8193	108	8	a	a	DET
cjfa-8193	108	9	number	number	NOUN
cjfa-8193	108	10	1	1	NUM
cjfa-8193	108	11	 	 	SPACE
cjfa-8193	108	12	n	n	PRON
cjfa-8193	108	13	stands	stand	VERB
cjfa-8193	108	14	for	for	ADP
cjfa-8193	108	15	the	the	DET
cjfa-8193	108	16	normal	normal	ADJ
cjfa-8193	108	17	distribution	distribution	NOUN
cjfa-8193	108	18	,	,	PUNCT
cjfa-8193	108	19	t	t	PROPN
cjfa-8193	108	20	the	the	DET
cjfa-8193	108	21	student	student	NOUN
cjfa-8193	108	22	t	t	NOUN
cjfa-8193	108	23	distribution	distribution	NOUN
cjfa-8193	108	24	,	,	PUNCT
cjfa-8193	108	25	ged	ge	VERB
cjfa-8193	108	26	the	the	DET
cjfa-8193	108	27	generalised	generalise	VERB
cjfa-8193	108	28	error	error	NOUN
cjfa-8193	108	29	distribution	distribution	NOUN
cjfa-8193	108	30	and	and	CCONJ
cjfa-8193	108	31	st	st	NOUN
cjfa-8193	108	32	the	the	DET
cjfa-8193	108	33	standardised	standardised	ADJ
cjfa-8193	108	34	skewed	skewed	ADJ
cjfa-8193	108	35	student	student	NOUN
cjfa-8193	108	36	distribution	distribution	NOUN
cjfa-8193	108	37	.	.	PUNCT
cjfa-8193	109	1	2	2	NUM
cjfa-8193	109	2	 	 	SPACE
cjfa-8193	109	3	the	the	DET
cjfa-8193	109	4	mulcom	mulcom	PROPN
cjfa-8193	109	5	3.0	3.0	NUM
cjfa-8193	109	6	package	package	NOUN
cjfa-8193	109	7	running	run	VERB
cjfa-8193	109	8	spa	spa	NOUN
cjfa-8193	109	9	and	and	CCONJ
cjfa-8193	109	10	mcs	mcs	PROPN
cjfa-8193	109	11	was	be	AUX
cjfa-8193	109	12	developed	develop	VERB
cjfa-8193	109	13	by	by	ADP
cjfa-8193	109	14	hansen	hansen	PROPN
cjfa-8193	109	15	and	and	CCONJ
cjfa-8193	109	16	lunde	lunde	PROPN
cjfa-8193	109	17	(	(	PUNCT
cjfa-8193	109	18	2014	2014	NUM
cjfa-8193	109	19	)	)	PUNCT
cjfa-8193	109	20	.	.	PUNCT
cjfa-8193	110	1	h.	h.	PROPN
cjfa-8193	110	2	al	al	PROPN
cjfa-8193	110	3	-	-	PUNCT
cjfa-8193	110	4	hajieh	hajieh	PROPN
cjfa-8193	110	5	,	,	PUNCT
cjfa-8193	110	6	h.	h.	PROPN
cjfa-8193	110	7	alnemer	alnemer	PROPN
cjfa-8193	110	8	,	,	PUNCT
cjfa-8193	110	9	t.	t.	PROPN
cjfa-8193	110	10	rodgers	rodgers	PROPN
cjfa-8193	110	11	,	,	PUNCT
cjfa-8193	110	12	j.	j.	PROPN
cjfa-8193	110	13	niklewski16	niklewski16	PROPN
cjfa-8193	110	14	of	of	ADP
cjfa-8193	110	15	lags	lag	NOUN
cjfa-8193	110	16	in	in	ADP
cjfa-8193	110	17	each	each	DET
cjfa-8193	110	18	term	term	NOUN
cjfa-8193	110	19	a	a	DET
cjfa-8193	110	20	single	single	ADJ
cjfa-8193	110	21	lag	lag	NOUN
cjfa-8193	110	22	in	in	ADP
cjfa-8193	110	23	each	each	PRON
cjfa-8193	110	24	is	be	AUX
cjfa-8193	110	25	usually	usually	ADV
cjfa-8193	110	26	adequate	adequate	ADJ
cjfa-8193	110	27	in	in	ADP
cjfa-8193	110	28	financial	financial	ADJ
cjfa-8193	110	29	market	market	NOUN
cjfa-8193	110	30	data	datum	NOUN
cjfa-8193	110	31	.	.	PUNCT
cjfa-8193	111	1	we	we	PRON
cjfa-8193	111	2	follow	follow	VERB
cjfa-8193	111	3	this	this	DET
cjfa-8193	111	4	conversion	conversion	NOUN
cjfa-8193	111	5	in	in	ADP
cjfa-8193	111	6	this	this	DET
cjfa-8193	111	7	paper	paper	NOUN
cjfa-8193	111	8	.	.	PUNCT
cjfa-8193	112	1	the	the	DET
cjfa-8193	112	2	model	model	NOUN
cjfa-8193	112	3	specifications	specification	NOUN
cjfa-8193	112	4	and	and	CCONJ
cjfa-8193	112	5	the	the	DET
cjfa-8193	112	6	distributions	distribution	NOUN
cjfa-8193	112	7	tested	test	VERB
cjfa-8193	112	8	are	be	AUX
cjfa-8193	112	9	identified	identify	VERB
cjfa-8193	112	10	below	below	ADV
cjfa-8193	112	11	.	.	PUNCT
cjfa-8193	113	1	they	they	PRON
cjfa-8193	113	2	consist	consist	VERB
cjfa-8193	113	3	of	of	ADP
cjfa-8193	113	4	three	three	NUM
cjfa-8193	113	5	different	different	ADJ
cjfa-8193	113	6	conditional	conditional	ADJ
cjfa-8193	113	7	volatility	volatility	NOUN
cjfa-8193	113	8	specifications	specification	NOUN
cjfa-8193	113	9	and	and	CCONJ
cjfa-8193	113	10	four	four	NUM
cjfa-8193	113	11	different	different	ADJ
cjfa-8193	113	12	statistical	statistical	ADJ
cjfa-8193	113	13	distributions	distribution	NOUN
cjfa-8193	113	14	.	.	PUNCT
cjfa-8193	114	1	(	(	PUNCT
cjfa-8193	114	2	i	i	NOUN
cjfa-8193	114	3	)	)	PUNCT
cjfa-8193	114	4	garch	garch	VERB
cjfa-8193	114	5	the	the	DET
cjfa-8193	114	6	garch	garch	NOUN
cjfa-8193	114	7	model	model	NOUN
cjfa-8193	114	8	,	,	PUNCT
cjfa-8193	114	9	as	as	SCONJ
cjfa-8193	114	10	introduced	introduce	VERB
cjfa-8193	114	11	by	by	ADP
cjfa-8193	114	12	bollerslev	bollerslev	ADJ
cjfa-8193	114	13	(	(	PUNCT
cjfa-8193	114	14	1986	1986	NUM
cjfa-8193	114	15	)	)	PUNCT
cjfa-8193	114	16	,	,	PUNCT
cjfa-8193	114	17	is	be	AUX
cjfa-8193	114	18	a	a	DET
cjfa-8193	114	19	generalisation	generalisation	NOUN
cjfa-8193	114	20	of	of	ADP
cjfa-8193	114	21	the	the	DET
cjfa-8193	114	22	arch	arch	ADJ
cjfa-8193	114	23	specification	specification	NOUN
cjfa-8193	114	24	of	of	ADP
cjfa-8193	114	25	engle	engle	PROPN
cjfa-8193	114	26	(	(	PUNCT
cjfa-8193	114	27	1982	1982	NUM
cjfa-8193	114	28	)	)	PUNCT
cjfa-8193	114	29	.	.	PUNCT
cjfa-8193	115	1	the	the	DET
cjfa-8193	115	2	model	model	NOUN
cjfa-8193	115	3	specifies	specifie	NOUN
cjfa-8193	115	4	that	that	PRON
cjfa-8193	115	5	the	the	DET
cjfa-8193	115	6	conditional	conditional	ADJ
cjfa-8193	115	7	variance	variance	NOUN
cjfa-8193	115	8	is	be	AUX
cjfa-8193	115	9	a	a	DET
cjfa-8193	115	10	function	function	NOUN
cjfa-8193	115	11	of	of	ADP
cjfa-8193	115	12	the	the	DET
cjfa-8193	115	13	lagged	lag	VERB
cjfa-8193	115	14	squared	square	VERB
cjfa-8193	115	15	residuals	residual	NOUN
cjfa-8193	115	16	as	as	ADV
cjfa-8193	115	17	well	well	ADV
cjfa-8193	115	18	as	as	ADP
cjfa-8193	115	19	of	of	ADP
cjfa-8193	115	20	its	its	PRON
cjfa-8193	115	21	past	past	ADJ
cjfa-8193	115	22	conditional	conditional	ADJ
cjfa-8193	115	23	variances	variance	NOUN
cjfa-8193	115	24	.	.	PUNCT
cjfa-8193	116	1	although	although	SCONJ
cjfa-8193	116	2	the	the	DET
cjfa-8193	116	3	equation	equation	NOUN
cjfa-8193	116	4	may	may	AUX
cjfa-8193	116	5	be	be	AUX
cjfa-8193	116	6	specified	specify	VERB
cjfa-8193	116	7	with	with	ADP
cjfa-8193	116	8	a	a	DET
cjfa-8193	116	9	number	number	NOUN
cjfa-8193	116	10	of	of	ADP
cjfa-8193	116	11	lags	lag	NOUN
cjfa-8193	116	12	in	in	ADP
cjfa-8193	116	13	each	each	DET
cjfa-8193	116	14	term	term	NOUN
cjfa-8193	116	15	a	a	DET
cjfa-8193	116	16	single	single	ADJ
cjfa-8193	116	17	lag	lag	NOUN
cjfa-8193	116	18	in	in	ADP
cjfa-8193	116	19	each	each	PRON
cjfa-8193	116	20	is	be	AUX
cjfa-8193	116	21	usually	usually	ADV
cjfa-8193	116	22	adequate	adequate	ADJ
cjfa-8193	116	23	in	in	ADP
cjfa-8193	116	24	financial	financial	ADJ
cjfa-8193	116	25	market	market	NOUN
cjfa-8193	116	26	data	datum	NOUN
cjfa-8193	116	27	.	.	PUNCT
cjfa-8193	117	1	we	we	PRON
cjfa-8193	117	2	follow	follow	VERB
cjfa-8193	117	3	this	this	DET
cjfa-8193	117	4	conversion	conversion	NOUN
cjfa-8193	117	5	in	in	ADP
cjfa-8193	117	6	this	this	DET
cjfa-8193	117	7	paper	paper	NOUN
cjfa-8193	117	8	.	.	PUNCT
cjfa-8193	118	1	(	(	PUNCT
cjfa-8193	118	2	ii	ii	NOUN
cjfa-8193	118	3	)	)	PUNCT
cjfa-8193	118	4	egarch	egarch	NOUN
cjfa-8193	118	5	it	it	PRON
cjfa-8193	118	6	is	be	AUX
cjfa-8193	118	7	often	often	ADV
cjfa-8193	118	8	observed	observe	VERB
cjfa-8193	118	9	that	that	SCONJ
cjfa-8193	118	10	volatilities	volatility	NOUN
cjfa-8193	118	11	associated	associate	VERB
cjfa-8193	118	12	with	with	ADP
cjfa-8193	118	13	downward	downward	ADJ
cjfa-8193	118	14	movements	movement	NOUN
cjfa-8193	118	15	in	in	ADP
cjfa-8193	118	16	financial	financial	ADJ
cjfa-8193	118	17	markets	market	NOUN
cjfa-8193	118	18	are	be	AUX
cjfa-8193	118	19	greater	great	ADJ
cjfa-8193	118	20	than	than	ADP
cjfa-8193	118	21	the	the	DET
cjfa-8193	118	22	volatilities	volatility	NOUN
cjfa-8193	118	23	observed	observe	VERB
cjfa-8193	118	24	by	by	ADP
cjfa-8193	118	25	upward	upward	ADJ
cjfa-8193	118	26	movements	movement	NOUN
cjfa-8193	118	27	of	of	ADP
cjfa-8193	118	28	the	the	DET
cjfa-8193	118	29	same	same	ADJ
cjfa-8193	118	30	magnitude	magnitude	NOUN
cjfa-8193	118	31	.	.	PUNCT
cjfa-8193	119	1	in	in	ADP
cjfa-8193	119	2	such	such	ADJ
cjfa-8193	119	3	circumstances	circumstance	NOUN
cjfa-8193	119	4	the	the	DET
cjfa-8193	119	5	symmetry	symmetry	NOUN
cjfa-8193	119	6	imposed	impose	VERB
cjfa-8193	119	7	on	on	ADP
cjfa-8193	119	8	the	the	DET
cjfa-8193	119	9	conditional	conditional	ADJ
cjfa-8193	119	10	variance	variance	NOUN
cjfa-8193	119	11	structure	structure	NOUN
cjfa-8193	119	12	in	in	ADP
cjfa-8193	119	13	the	the	DET
cjfa-8193	119	14	garch	garch	NOUN
cjfa-8193	119	15	model	model	NOUN
cjfa-8193	119	16	may	may	AUX
cjfa-8193	119	17	not	not	PART
cjfa-8193	119	18	be	be	AUX
cjfa-8193	119	19	appropriate	appropriate	ADJ
cjfa-8193	119	20	.	.	PUNCT
cjfa-8193	120	1	to	to	PART
cjfa-8193	120	2	address	address	VERB
cjfa-8193	120	3	this	this	DET
cjfa-8193	120	4	issue	issue	NOUN
cjfa-8193	120	5	,	,	PUNCT
cjfa-8193	120	6	nelson	nelson	PROPN
cjfa-8193	120	7	(	(	PUNCT
cjfa-8193	120	8	1991	1991	NUM
cjfa-8193	120	9	)	)	PUNCT
cjfa-8193	120	10	proposes	propose	VERB
cjfa-8193	120	11	the	the	DET
cjfa-8193	120	12	exponential	exponential	ADJ
cjfa-8193	120	13	garch	garch	NOUN
cjfa-8193	120	14	(	(	PUNCT
cjfa-8193	120	15	egarch	egarch	NOUN
cjfa-8193	120	16	)	)	PUNCT
cjfa-8193	120	17	model	model	NOUN
cjfa-8193	120	18	.	.	PUNCT
cjfa-8193	121	1	the	the	DET
cjfa-8193	121	2	specification	specification	NOUN
cjfa-8193	121	3	for	for	ADP
cjfa-8193	121	4	the	the	DET
cjfa-8193	121	5	conditional	conditional	ADJ
cjfa-8193	121	6	variance	variance	NOUN
cjfa-8193	121	7	is	be	AUX
cjfa-8193	121	8	:	:	PUNCT
cjfa-8193	121	9	�	�	PROPN
cjfa-8193	121	10	�	�	PROPN
cjfa-8193	121	11	�	�	PROPN
cjfa-8193	121	12	�	�	PROPN
cjfa-8193	121	13	�	�	PROPN
cjfa-8193	121	14	�	�	PROPN
cjfa-8193	121	15	�	�	PROPN
cjfa-8193	121	16	�	�	PROPN
cjfa-8193	121	17	�	�	PROPN
cjfa-8193	121	18	[	[	X
cjfa-8193	121	19	�	�	PROPN
cjfa-8193	121	20	�	�	PROPN
cjfa-8193	121	21	�	�	PROPN
cjfa-8193	121	22	�	�	PROPN
cjfa-8193	121	23	�	�	PROPN
cjfa-8193	121	24	�	�	PROPN
cjfa-8193	121	25	]	]	SYM
cjfa-8193	121	26	�	�	PROPN
cjfa-8193	121	27	�	�	PROPN
cjfa-8193	121	28	[	[	SYM
cjfa-8193	121	29	�	�	PROPN
cjfa-8193	121	30	�	�	PROPN
cjfa-8193	121	31	�	�	PROPN
cjfa-8193	121	32	�	�	PROPN
cjfa-8193	121	33	�	�	PROPN
cjfa-8193	121	34	�	�	PROPN
cjfa-8193	121	35	]	]	SYM
cjfa-8193	121	36	�	�	PROPN
cjfa-8193	121	37	�	�	PROPN
cjfa-8193	121	38	�	�	PROPN
cjfa-8193	121	39	�	�	PROPN
cjfa-8193	121	40	�	�	PROPN
cjfa-8193	121	41	�	�	PROPN
cjfa-8193	121	42	�	�	PROPN
cjfa-8193	121	43	[	[	X
cjfa-8193	121	44	3	3	NUM
cjfa-8193	121	45	]	]	PUNCT
cjfa-8193	121	46	where	where	SCONJ
cjfa-8193	121	47	�	�	PROPN
cjfa-8193	121	48	�	�	PROPN
cjfa-8193	121	49	�	�	PROPN
cjfa-8193	121	50	�	�	PROPN
cjfa-8193	121	51	�	�	PROPN
cjfa-8193	121	52	�	�	PROPN
cjfa-8193	121	53	�	�	PROPN
cjfa-8193	121	54	�	�	PROPN
cjfa-8193	121	55	�	�	PROPN
cjfa-8193	121	56	�	�	PROPN
cjfa-8193	121	57	�	�	PROPN
cjfa-8193	121	58	�	�	PROPN
cjfa-8193	121	59	�	�	PROPN
cjfa-8193	121	60	�	�	PROPN
cjfa-8193	121	61	�	�	PROPN
cjfa-8193	121	62	�	�	PROPN
cjfa-8193	121	63	�	�	PROPN
cjfa-8193	121	64	�	�	PROPN
cjfa-8193	121	65	�	�	PROPN
cjfa-8193	121	66	�	�	PROPN
cjfa-8193	121	67	�	�	PROPN
cjfa-8193	121	68	�	�	PROPN
cjfa-8193	121	69	�	�	PROPN
cjfa-8193	121	70	�	�	PROPN
cjfa-8193	121	71	[	[	X
cjfa-8193	121	72	|	|	PROPN
cjfa-8193	121	73	�	�	PROPN
cjfa-8193	121	74	�	�	PROPN
cjfa-8193	121	75	|	|	PROPN
cjfa-8193	121	76	�	�	PROPN
cjfa-8193	121	77	�	�	PROPN
cjfa-8193	121	78	|	|	PROPN
cjfa-8193	121	79	�	�	PROPN
cjfa-8193	121	80	�	�	PROPN
cjfa-8193	121	81	|	|	NOUN
cjfa-8193	121	82	]	]	SYM
cjfa-8193	121	83	�	�	PROPN
cjfa-8193	121	84	�	�	PROPN
cjfa-8193	121	85	�	�	PROPN
cjfa-8193	121	86	�	�	PROPN
cjfa-8193	121	87	�	�	PROPN
cjfa-8193	121	88	�	�	PROPN
cjfa-8193	121	89	�	�	PROPN
cjfa-8193	121	90	�	�	PROPN
cjfa-8193	121	91	�	�	PROPN
cjfa-8193	121	92	�	�	PROPN
cjfa-8193	121	93	�	�	PROPN
cjfa-8193	121	94	�	�	PROPN
cjfa-8193	121	95	�	�	PROPN
cjfa-8193	121	96	�	�	PROPN
cjfa-8193	121	97	�	�	PROPN
cjfa-8193	121	98	�	�	PROPN
cjfa-8193	121	99	�	�	PROPN
cjfa-8193	121	100	�	�	PROPN
cjfa-8193	121	101	�	�	PROPN
cjfa-8193	121	102	�	�	PROPN
cjfa-8193	121	103	�	�	PROPN
cjfa-8193	121	104	�	�	PROPN
cjfa-8193	121	105	�	�	PROPN
cjfa-8193	121	106	�	�	PROPN
cjfa-8193	121	107	�	�	PROPN
cjfa-8193	121	108	�	�	AUX
cjfa-8193	121	109	the	the	DET
cjfa-8193	121	110	log	log	NOUN
cjfa-8193	121	111	specification	specification	NOUN
cjfa-8193	121	112	implies	imply	VERB
cjfa-8193	121	113	that	that	SCONJ
cjfa-8193	121	114	the	the	DET
cjfa-8193	121	115	asymmetric	asymmetric	ADJ
cjfa-8193	121	116	effect	effect	NOUN
cjfa-8193	121	117	is	be	AUX
cjfa-8193	121	118	exponential	exponential	ADJ
cjfa-8193	121	119	,	,	PUNCT
cjfa-8193	121	120	rather	rather	ADV
cjfa-8193	121	121	than	than	ADP
cjfa-8193	121	122	quadratic	quadratic	ADJ
cjfa-8193	121	123	,	,	PUNCT
cjfa-8193	121	124	and	and	CCONJ
cjfa-8193	121	125	that	that	SCONJ
cjfa-8193	121	126	forecasts	forecast	NOUN
cjfa-8193	121	127	of	of	ADP
cjfa-8193	121	128	the	the	DET
cjfa-8193	121	129	conditional	conditional	ADJ
cjfa-8193	121	130	variance	variance	NOUN
cjfa-8193	121	131	that	that	PRON
cjfa-8193	121	132	are	be	AUX
cjfa-8193	121	133	generated	generate	VERB
cjfa-8193	121	134	are	be	AUX
cjfa-8193	121	135	nonnegative	nonnegative	ADJ
cjfa-8193	121	136	.	.	PUNCT
cjfa-8193	122	1	the	the	DET
cjfa-8193	122	2	presence	presence	NOUN
cjfa-8193	122	3	of	of	ADP
cjfa-8193	122	4	asymmetry	asymmetry	NOUN
cjfa-8193	122	5	effects	effect	NOUN
cjfa-8193	122	6	is	be	AUX
cjfa-8193	122	7	tested	test	VERB
cjfa-8193	122	8	in	in	ADP
cjfa-8193	122	9	terms	term	NOUN
cjfa-8193	122	10	of	of	ADP
cjfa-8193	122	11	the	the	DET
cjfa-8193	122	12	sign	sign	NOUN
cjfa-8193	122	13	and	and	CCONJ
cjfa-8193	122	14	magnitude	magnitude	NOUN
cjfa-8193	122	15	effects	effect	NOUN
cjfa-8193	122	16	identified	identify	VERB
cjfa-8193	122	17	above	above	ADV
cjfa-8193	122	18	.	.	PUNCT
cjfa-8193	123	1	(	(	PUNCT
cjfa-8193	123	2	iii	iii	X
cjfa-8193	123	3	)	)	PUNCT
cjfa-8193	123	4	gjr	gjr	NOUN
cjfa-8193	123	5	-	-	PUNCT
cjfa-8193	123	6	garch	garch	NOUN
cjfa-8193	123	7	]	]	X
cjfa-8193	123	8	2	2	NUM
cjfa-8193	123	9	[	[	PUNCT
cjfa-8193	123	10	1	1	NUM
cjfa-8193	123	11	2	2	NUM
cjfa-8193	123	12	1	1	NUM
cjfa-8193	123	13	22	22	NUM
cjfa-8193	123	14			PRON
cjfa-8193	123	15			NUM
cjfa-8193	123	16			PROPN
cjfa-8193	123	17			PROPN
cjfa-8193	123	18			PROPN
cjfa-8193	123	19			PUNCT
cjfa-8193	123	20	p	p	NOUN
cjfa-8193	123	21	j	j	PROPN
cjfa-8193	123	22	jtj	jtj	VERB
cjfa-8193	123	23	q	q	PROPN
cjfa-8193	124	1	i	i	PRON
cjfa-8193	124	2	itit	itit	VERB
cjfa-8193	124	3	u	u	PRON
cjfa-8193	124	4			NOUN
cjfa-8193	125	1	[	[	X
cjfa-8193	125	2	2	2	X
cjfa-8193	125	3	]	]	PUNCT
cjfa-8193	125	4	(	(	PUNCT
cjfa-8193	125	5	ii	ii	NOUN
cjfa-8193	125	6	)	)	PUNCT
cjfa-8193	125	7	 	 	SPACE
cjfa-8193	125	8	egarch	egarch	NOUN
cjfa-8193	125	9	it	it	PRON
cjfa-8193	125	10	is	be	AUX
cjfa-8193	125	11	often	often	ADV
cjfa-8193	125	12	observed	observe	VERB
cjfa-8193	125	13	that	that	SCONJ
cjfa-8193	125	14	volatilities	volatility	NOUN
cjfa-8193	125	15	associated	associate	VERB
cjfa-8193	125	16	with	with	ADP
cjfa-8193	125	17	downward	downward	ADJ
cjfa-8193	125	18	movements	movement	NOUN
cjfa-8193	125	19	in	in	ADP
cjfa-8193	125	20	financial	financial	ADJ
cjfa-8193	125	21	markets	market	NOUN
cjfa-8193	125	22	are	be	AUX
cjfa-8193	125	23	greater	great	ADJ
cjfa-8193	125	24	than	than	ADP
cjfa-8193	125	25	the	the	DET
cjfa-8193	125	26	volatilities	volatility	NOUN
cjfa-8193	125	27	observed	observe	VERB
cjfa-8193	125	28	by	by	ADP
cjfa-8193	125	29	upward	upward	ADJ
cjfa-8193	125	30	movements	movement	NOUN
cjfa-8193	125	31	of	of	ADP
cjfa-8193	125	32	the	the	DET
cjfa-8193	125	33	same	same	ADJ
cjfa-8193	125	34	magnitude	magnitude	NOUN
cjfa-8193	125	35	.	.	PUNCT
cjfa-8193	126	1	in	in	ADP
cjfa-8193	126	2	such	such	ADJ
cjfa-8193	126	3	circumstances	circumstance	NOUN
cjfa-8193	126	4	the	the	DET
cjfa-8193	126	5	symmetry	symmetry	NOUN
cjfa-8193	126	6	imposed	impose	VERB
cjfa-8193	126	7	on	on	ADP
cjfa-8193	126	8	the	the	DET
cjfa-8193	126	9	conditional	conditional	ADJ
cjfa-8193	126	10	variance	variance	NOUN
cjfa-8193	126	11	structure	structure	NOUN
cjfa-8193	126	12	in	in	ADP
cjfa-8193	126	13	the	the	DET
cjfa-8193	126	14	garch	garch	NOUN
cjfa-8193	126	15	model	model	NOUN
cjfa-8193	126	16	may	may	AUX
cjfa-8193	126	17	not	not	PART
cjfa-8193	126	18	be	be	AUX
cjfa-8193	126	19	appropriate	appropriate	ADJ
cjfa-8193	126	20	.	.	PUNCT
cjfa-8193	127	1	to	to	PART
cjfa-8193	127	2	address	address	VERB
cjfa-8193	127	3	this	this	DET
cjfa-8193	127	4	issue	issue	NOUN
cjfa-8193	127	5	,	,	PUNCT
cjfa-8193	127	6	nelson	nelson	PROPN
cjfa-8193	127	7	(	(	PUNCT
cjfa-8193	127	8	1991	1991	NUM
cjfa-8193	127	9	)	)	PUNCT
cjfa-8193	127	10	proposes	propose	VERB
cjfa-8193	127	11	the	the	DET
cjfa-8193	127	12	exponential	exponential	ADJ
cjfa-8193	127	13	garch	garch	NOUN
cjfa-8193	127	14	(	(	PUNCT
cjfa-8193	127	15	egarch	egarch	NOUN
cjfa-8193	127	16	)	)	PUNCT
cjfa-8193	127	17	model	model	NOUN
cjfa-8193	127	18	.	.	PUNCT
cjfa-8193	128	1	the	the	DET
cjfa-8193	128	2	specification	specification	NOUN
cjfa-8193	128	3	for	for	ADP
cjfa-8193	128	4	the	the	DET
cjfa-8193	128	5	conditional	conditional	ADJ
cjfa-8193	128	6	variance	variance	NOUN
cjfa-8193	128	7	is	be	AUX
cjfa-8193	128	8	:	:	PUNCT
cjfa-8193	128	9	the	the	DET
cjfa-8193	128	10	model	model	NOUN
cjfa-8193	128	11	specifications	specification	NOUN
cjfa-8193	128	12	and	and	CCONJ
cjfa-8193	128	13	the	the	DET
cjfa-8193	128	14	distributions	distribution	NOUN
cjfa-8193	128	15	tested	test	VERB
cjfa-8193	128	16	are	be	AUX
cjfa-8193	128	17	identified	identify	VERB
cjfa-8193	128	18	below	below	ADV
cjfa-8193	128	19	.	.	PUNCT
cjfa-8193	129	1	they	they	PRON
cjfa-8193	129	2	consist	consist	VERB
cjfa-8193	129	3	of	of	ADP
cjfa-8193	129	4	three	three	NUM
cjfa-8193	129	5	different	different	ADJ
cjfa-8193	129	6	conditional	conditional	ADJ
cjfa-8193	129	7	volatility	volatility	NOUN
cjfa-8193	129	8	specifications	specification	NOUN
cjfa-8193	129	9	and	and	CCONJ
cjfa-8193	129	10	four	four	NUM
cjfa-8193	129	11	different	different	ADJ
cjfa-8193	129	12	statistical	statistical	ADJ
cjfa-8193	129	13	distributions	distribution	NOUN
cjfa-8193	129	14	.	.	PUNCT
cjfa-8193	130	1	(	(	PUNCT
cjfa-8193	130	2	i	i	NOUN
cjfa-8193	130	3	)	)	PUNCT
cjfa-8193	130	4	garch	garch	VERB
cjfa-8193	130	5	the	the	DET
cjfa-8193	130	6	garch	garch	NOUN
cjfa-8193	130	7	model	model	NOUN
cjfa-8193	130	8	,	,	PUNCT
cjfa-8193	130	9	as	as	SCONJ
cjfa-8193	130	10	introduced	introduce	VERB
cjfa-8193	130	11	by	by	ADP
cjfa-8193	130	12	bollerslev	bollerslev	ADJ
cjfa-8193	130	13	(	(	PUNCT
cjfa-8193	130	14	1986	1986	NUM
cjfa-8193	130	15	)	)	PUNCT
cjfa-8193	130	16	,	,	PUNCT
cjfa-8193	130	17	is	be	AUX
cjfa-8193	130	18	a	a	DET
cjfa-8193	130	19	generalisation	generalisation	NOUN
cjfa-8193	130	20	of	of	ADP
cjfa-8193	130	21	the	the	DET
cjfa-8193	130	22	arch	arch	ADJ
cjfa-8193	130	23	specification	specification	NOUN
cjfa-8193	130	24	of	of	ADP
cjfa-8193	130	25	engle	engle	PROPN
cjfa-8193	130	26	(	(	PUNCT
cjfa-8193	130	27	1982	1982	NUM
cjfa-8193	130	28	)	)	PUNCT
cjfa-8193	130	29	.	.	PUNCT
cjfa-8193	131	1	the	the	DET
cjfa-8193	131	2	model	model	NOUN
cjfa-8193	131	3	specifies	specifie	NOUN
cjfa-8193	131	4	that	that	PRON
cjfa-8193	131	5	the	the	DET
cjfa-8193	131	6	conditional	conditional	ADJ
cjfa-8193	131	7	variance	variance	NOUN
cjfa-8193	131	8	is	be	AUX
cjfa-8193	131	9	a	a	DET
cjfa-8193	131	10	function	function	NOUN
cjfa-8193	131	11	of	of	ADP
cjfa-8193	131	12	the	the	DET
cjfa-8193	131	13	lagged	lag	VERB
cjfa-8193	131	14	squared	square	VERB
cjfa-8193	131	15	residuals	residual	NOUN
cjfa-8193	131	16	as	as	ADV
cjfa-8193	131	17	well	well	ADV
cjfa-8193	131	18	as	as	ADP
cjfa-8193	131	19	of	of	ADP
cjfa-8193	131	20	its	its	PRON
cjfa-8193	131	21	past	past	ADJ
cjfa-8193	131	22	conditional	conditional	ADJ
cjfa-8193	131	23	variances	variance	NOUN
cjfa-8193	131	24	.	.	PUNCT
cjfa-8193	132	1	although	although	SCONJ
cjfa-8193	132	2	the	the	DET
cjfa-8193	132	3	equation	equation	NOUN
cjfa-8193	132	4	may	may	AUX
cjfa-8193	132	5	be	be	AUX
cjfa-8193	132	6	specified	specify	VERB
cjfa-8193	132	7	with	with	ADP
cjfa-8193	132	8	a	a	DET
cjfa-8193	132	9	number	number	NOUN
cjfa-8193	132	10	of	of	ADP
cjfa-8193	132	11	lags	lag	NOUN
cjfa-8193	132	12	in	in	ADP
cjfa-8193	132	13	each	each	DET
cjfa-8193	132	14	term	term	NOUN
cjfa-8193	132	15	a	a	DET
cjfa-8193	132	16	single	single	ADJ
cjfa-8193	132	17	lag	lag	NOUN
cjfa-8193	132	18	in	in	ADP
cjfa-8193	132	19	each	each	PRON
cjfa-8193	132	20	is	be	AUX
cjfa-8193	132	21	usually	usually	ADV
cjfa-8193	132	22	adequate	adequate	ADJ
cjfa-8193	132	23	in	in	ADP
cjfa-8193	132	24	financial	financial	ADJ
cjfa-8193	132	25	market	market	NOUN
cjfa-8193	132	26	data	datum	NOUN
cjfa-8193	132	27	.	.	PUNCT
cjfa-8193	133	1	we	we	PRON
cjfa-8193	133	2	follow	follow	VERB
cjfa-8193	133	3	this	this	DET
cjfa-8193	133	4	conversion	conversion	NOUN
cjfa-8193	133	5	in	in	ADP
cjfa-8193	133	6	this	this	DET
cjfa-8193	133	7	paper	paper	NOUN
cjfa-8193	133	8	.	.	PUNCT
cjfa-8193	134	1	(	(	PUNCT
cjfa-8193	134	2	ii	ii	NOUN
cjfa-8193	134	3	)	)	PUNCT
cjfa-8193	134	4	egarch	egarch	NOUN
cjfa-8193	134	5	it	it	PRON
cjfa-8193	134	6	is	be	AUX
cjfa-8193	134	7	often	often	ADV
cjfa-8193	134	8	observed	observe	VERB
cjfa-8193	134	9	that	that	SCONJ
cjfa-8193	134	10	volatilities	volatility	NOUN
cjfa-8193	134	11	associated	associate	VERB
cjfa-8193	134	12	with	with	ADP
cjfa-8193	134	13	downward	downward	ADJ
cjfa-8193	134	14	movements	movement	NOUN
cjfa-8193	134	15	in	in	ADP
cjfa-8193	134	16	financial	financial	ADJ
cjfa-8193	134	17	markets	market	NOUN
cjfa-8193	134	18	are	be	AUX
cjfa-8193	134	19	greater	great	ADJ
cjfa-8193	134	20	than	than	ADP
cjfa-8193	134	21	the	the	DET
cjfa-8193	134	22	volatilities	volatility	NOUN
cjfa-8193	134	23	observed	observe	VERB
cjfa-8193	134	24	by	by	ADP
cjfa-8193	134	25	upward	upward	ADJ
cjfa-8193	134	26	movements	movement	NOUN
cjfa-8193	134	27	of	of	ADP
cjfa-8193	134	28	the	the	DET
cjfa-8193	134	29	same	same	ADJ
cjfa-8193	134	30	magnitude	magnitude	NOUN
cjfa-8193	134	31	.	.	PUNCT
cjfa-8193	135	1	in	in	ADP
cjfa-8193	135	2	such	such	ADJ
cjfa-8193	135	3	circumstances	circumstance	NOUN
cjfa-8193	135	4	the	the	DET
cjfa-8193	135	5	symmetry	symmetry	NOUN
cjfa-8193	135	6	imposed	impose	VERB
cjfa-8193	135	7	on	on	ADP
cjfa-8193	135	8	the	the	DET
cjfa-8193	135	9	conditional	conditional	ADJ
cjfa-8193	135	10	variance	variance	NOUN
cjfa-8193	135	11	structure	structure	NOUN
cjfa-8193	135	12	in	in	ADP
cjfa-8193	135	13	the	the	DET
cjfa-8193	135	14	garch	garch	NOUN
cjfa-8193	135	15	model	model	NOUN
cjfa-8193	135	16	may	may	AUX
cjfa-8193	135	17	not	not	PART
cjfa-8193	135	18	be	be	AUX
cjfa-8193	135	19	appropriate	appropriate	ADJ
cjfa-8193	135	20	.	.	PUNCT
cjfa-8193	136	1	to	to	PART
cjfa-8193	136	2	address	address	VERB
cjfa-8193	136	3	this	this	DET
cjfa-8193	136	4	issue	issue	NOUN
cjfa-8193	136	5	,	,	PUNCT
cjfa-8193	136	6	nelson	nelson	PROPN
cjfa-8193	136	7	(	(	PUNCT
cjfa-8193	136	8	1991	1991	NUM
cjfa-8193	136	9	)	)	PUNCT
cjfa-8193	136	10	proposes	propose	VERB
cjfa-8193	136	11	the	the	DET
cjfa-8193	136	12	exponential	exponential	ADJ
cjfa-8193	136	13	garch	garch	NOUN
cjfa-8193	136	14	(	(	PUNCT
cjfa-8193	136	15	egarch	egarch	NOUN
cjfa-8193	136	16	)	)	PUNCT
cjfa-8193	136	17	model	model	NOUN
cjfa-8193	136	18	.	.	PUNCT
cjfa-8193	137	1	the	the	DET
cjfa-8193	137	2	specification	specification	NOUN
cjfa-8193	137	3	for	for	ADP
cjfa-8193	137	4	the	the	DET
cjfa-8193	137	5	conditional	conditional	ADJ
cjfa-8193	137	6	variance	variance	NOUN
cjfa-8193	137	7	is	be	AUX
cjfa-8193	137	8	:	:	PUNCT
cjfa-8193	137	9	�	�	PROPN
cjfa-8193	137	10	�	�	PROPN
cjfa-8193	137	11	�	�	PROPN
cjfa-8193	137	12	�	�	PROPN
cjfa-8193	137	13	�	�	PROPN
cjfa-8193	137	14	�	�	PROPN
cjfa-8193	137	15	�	�	PROPN
cjfa-8193	137	16	�	�	PROPN
cjfa-8193	137	17	�	�	PROPN
cjfa-8193	137	18	[	[	X
cjfa-8193	137	19	�	�	PROPN
cjfa-8193	137	20	�	�	PROPN
cjfa-8193	137	21	�	�	PROPN
cjfa-8193	137	22	�	�	PROPN
cjfa-8193	137	23	�	�	PROPN
cjfa-8193	137	24	�	�	PROPN
cjfa-8193	137	25	]	]	SYM
cjfa-8193	137	26	�	�	PROPN
cjfa-8193	137	27	�	�	PROPN
cjfa-8193	137	28	[	[	SYM
cjfa-8193	137	29	�	�	PROPN
cjfa-8193	137	30	�	�	PROPN
cjfa-8193	137	31	�	�	PROPN
cjfa-8193	137	32	�	�	PROPN
cjfa-8193	137	33	�	�	PROPN
cjfa-8193	137	34	�	�	PROPN
cjfa-8193	137	35	]	]	SYM
cjfa-8193	137	36	�	�	PROPN
cjfa-8193	137	37	�	�	PROPN
cjfa-8193	137	38	�	�	PROPN
cjfa-8193	137	39	�	�	PROPN
cjfa-8193	137	40	�	�	PROPN
cjfa-8193	137	41	�	�	PROPN
cjfa-8193	137	42	�	�	PROPN
cjfa-8193	137	43	[	[	X
cjfa-8193	137	44	3	3	NUM
cjfa-8193	137	45	]	]	PUNCT
cjfa-8193	137	46	where	where	SCONJ
cjfa-8193	137	47	�	�	PROPN
cjfa-8193	137	48	�	�	PROPN
cjfa-8193	137	49	�	�	PROPN
cjfa-8193	137	50	�	�	PROPN
cjfa-8193	137	51	�	�	PROPN
cjfa-8193	137	52	�	�	PROPN
cjfa-8193	137	53	�	�	PROPN
cjfa-8193	137	54	�	�	PROPN
cjfa-8193	137	55	�	�	PROPN
cjfa-8193	137	56	�	�	PROPN
cjfa-8193	137	57	�	�	PROPN
cjfa-8193	137	58	�	�	PROPN
cjfa-8193	137	59	�	�	PROPN
cjfa-8193	137	60	�	�	PROPN
cjfa-8193	137	61	�	�	PROPN
cjfa-8193	137	62	�	�	PROPN
cjfa-8193	137	63	�	�	PROPN
cjfa-8193	137	64	�	�	PROPN
cjfa-8193	137	65	�	�	PROPN
cjfa-8193	137	66	�	�	PROPN
cjfa-8193	137	67	�	�	PROPN
cjfa-8193	137	68	�	�	PROPN
cjfa-8193	137	69	�	�	PROPN
cjfa-8193	137	70	�	�	PROPN
cjfa-8193	137	71	[	[	X
cjfa-8193	137	72	|	|	PROPN
cjfa-8193	137	73	�	�	PROPN
cjfa-8193	137	74	�	�	PROPN
cjfa-8193	137	75	|	|	PROPN
cjfa-8193	137	76	�	�	PROPN
cjfa-8193	137	77	�	�	PROPN
cjfa-8193	137	78	|	|	PROPN
cjfa-8193	137	79	�	�	PROPN
cjfa-8193	137	80	�	�	PROPN
cjfa-8193	137	81	|	|	NOUN
cjfa-8193	137	82	]	]	SYM
cjfa-8193	137	83	�	�	PROPN
cjfa-8193	137	84	�	�	PROPN
cjfa-8193	137	85	�	�	PROPN
cjfa-8193	137	86	�	�	PROPN
cjfa-8193	137	87	�	�	PROPN
cjfa-8193	137	88	�	�	PROPN
cjfa-8193	137	89	�	�	PROPN
cjfa-8193	137	90	�	�	PROPN
cjfa-8193	137	91	�	�	PROPN
cjfa-8193	137	92	�	�	PROPN
cjfa-8193	137	93	�	�	PROPN
cjfa-8193	137	94	�	�	PROPN
cjfa-8193	137	95	�	�	PROPN
cjfa-8193	137	96	�	�	PROPN
cjfa-8193	137	97	�	�	PROPN
cjfa-8193	137	98	�	�	PROPN
cjfa-8193	137	99	�	�	PROPN
cjfa-8193	137	100	�	�	PROPN
cjfa-8193	137	101	�	�	PROPN
cjfa-8193	137	102	�	�	PROPN
cjfa-8193	137	103	�	�	PROPN
cjfa-8193	137	104	�	�	PROPN
cjfa-8193	137	105	�	�	PROPN
cjfa-8193	137	106	�	�	PROPN
cjfa-8193	137	107	�	�	PROPN
cjfa-8193	137	108	�	�	AUX
cjfa-8193	137	109	the	the	DET
cjfa-8193	137	110	log	log	NOUN
cjfa-8193	137	111	specification	specification	NOUN
cjfa-8193	137	112	implies	imply	VERB
cjfa-8193	137	113	that	that	SCONJ
cjfa-8193	137	114	the	the	DET
cjfa-8193	137	115	asymmetric	asymmetric	ADJ
cjfa-8193	137	116	effect	effect	NOUN
cjfa-8193	137	117	is	be	AUX
cjfa-8193	137	118	exponential	exponential	ADJ
cjfa-8193	137	119	,	,	PUNCT
cjfa-8193	137	120	rather	rather	ADV
cjfa-8193	137	121	than	than	ADP
cjfa-8193	137	122	quadratic	quadratic	ADJ
cjfa-8193	137	123	,	,	PUNCT
cjfa-8193	137	124	and	and	CCONJ
cjfa-8193	137	125	that	that	SCONJ
cjfa-8193	137	126	forecasts	forecast	NOUN
cjfa-8193	137	127	of	of	ADP
cjfa-8193	137	128	the	the	DET
cjfa-8193	137	129	conditional	conditional	ADJ
cjfa-8193	137	130	variance	variance	NOUN
cjfa-8193	137	131	that	that	PRON
cjfa-8193	137	132	are	be	AUX
cjfa-8193	137	133	generated	generate	VERB
cjfa-8193	137	134	are	be	AUX
cjfa-8193	137	135	nonnegative	nonnegative	ADJ
cjfa-8193	137	136	.	.	PUNCT
cjfa-8193	138	1	the	the	DET
cjfa-8193	138	2	presence	presence	NOUN
cjfa-8193	138	3	of	of	ADP
cjfa-8193	138	4	asymmetry	asymmetry	NOUN
cjfa-8193	138	5	effects	effect	NOUN
cjfa-8193	138	6	is	be	AUX
cjfa-8193	138	7	tested	test	VERB
cjfa-8193	138	8	in	in	ADP
cjfa-8193	138	9	terms	term	NOUN
cjfa-8193	138	10	of	of	ADP
cjfa-8193	138	11	the	the	DET
cjfa-8193	138	12	sign	sign	NOUN
cjfa-8193	138	13	and	and	CCONJ
cjfa-8193	138	14	magnitude	magnitude	NOUN
cjfa-8193	138	15	effects	effect	NOUN
cjfa-8193	138	16	identified	identify	VERB
cjfa-8193	138	17	above	above	ADV
cjfa-8193	138	18	.	.	PUNCT
cjfa-8193	139	1	(	(	PUNCT
cjfa-8193	139	2	iii	iii	X
cjfa-8193	139	3	)	)	PUNCT
cjfa-8193	139	4	gjr	gjr	NOUN
cjfa-8193	139	5	-	-	PUNCT
cjfa-8193	139	6	garch	garch	NOUN
cjfa-8193	139	7	]	]	X
cjfa-8193	139	8	2	2	NUM
cjfa-8193	139	9	[	[	PUNCT
cjfa-8193	139	10	1	1	NUM
cjfa-8193	139	11	2	2	NUM
cjfa-8193	139	12	1	1	NUM
cjfa-8193	139	13	22	22	NUM
cjfa-8193	139	14			PRON
cjfa-8193	139	15			NUM
cjfa-8193	139	16			PROPN
cjfa-8193	139	17			PROPN
cjfa-8193	139	18			PROPN
cjfa-8193	139	19			PUNCT
cjfa-8193	139	20	p	p	NOUN
cjfa-8193	139	21	j	j	PROPN
cjfa-8193	139	22	jtj	jtj	VERB
cjfa-8193	139	23	q	q	PROPN
cjfa-8193	140	1	i	i	PRON
cjfa-8193	140	2	itit	itit	VERB
cjfa-8193	140	3	u	u	PRON
cjfa-8193	140	4			NOUN
cjfa-8193	141	1	[	[	X
cjfa-8193	141	2	3	3	X
cjfa-8193	141	3	]	]	PUNCT
cjfa-8193	141	4	the	the	DET
cjfa-8193	141	5	model	model	NOUN
cjfa-8193	141	6	specifications	specification	NOUN
cjfa-8193	141	7	and	and	CCONJ
cjfa-8193	141	8	the	the	DET
cjfa-8193	141	9	distributions	distribution	NOUN
cjfa-8193	141	10	tested	test	VERB
cjfa-8193	141	11	are	be	AUX
cjfa-8193	141	12	identified	identify	VERB
cjfa-8193	141	13	below	below	ADV
cjfa-8193	141	14	.	.	PUNCT
cjfa-8193	142	1	they	they	PRON
cjfa-8193	142	2	consist	consist	VERB
cjfa-8193	142	3	of	of	ADP
cjfa-8193	142	4	three	three	NUM
cjfa-8193	142	5	different	different	ADJ
cjfa-8193	142	6	conditional	conditional	ADJ
cjfa-8193	142	7	volatility	volatility	NOUN
cjfa-8193	142	8	specifications	specification	NOUN
cjfa-8193	142	9	and	and	CCONJ
cjfa-8193	142	10	four	four	NUM
cjfa-8193	142	11	different	different	ADJ
cjfa-8193	142	12	statistical	statistical	ADJ
cjfa-8193	142	13	distributions	distribution	NOUN
cjfa-8193	142	14	.	.	PUNCT
cjfa-8193	143	1	(	(	PUNCT
cjfa-8193	143	2	i	i	NOUN
cjfa-8193	143	3	)	)	PUNCT
cjfa-8193	143	4	garch	garch	VERB
cjfa-8193	143	5	the	the	DET
cjfa-8193	143	6	garch	garch	NOUN
cjfa-8193	143	7	model	model	NOUN
cjfa-8193	143	8	,	,	PUNCT
cjfa-8193	143	9	as	as	SCONJ
cjfa-8193	143	10	introduced	introduce	VERB
cjfa-8193	143	11	by	by	ADP
cjfa-8193	143	12	bollerslev	bollerslev	ADJ
cjfa-8193	143	13	(	(	PUNCT
cjfa-8193	143	14	1986	1986	NUM
cjfa-8193	143	15	)	)	PUNCT
cjfa-8193	143	16	,	,	PUNCT
cjfa-8193	143	17	is	be	AUX
cjfa-8193	143	18	a	a	DET
cjfa-8193	143	19	generalisation	generalisation	NOUN
cjfa-8193	143	20	of	of	ADP
cjfa-8193	143	21	the	the	DET
cjfa-8193	143	22	arch	arch	ADJ
cjfa-8193	143	23	specification	specification	NOUN
cjfa-8193	143	24	of	of	ADP
cjfa-8193	143	25	engle	engle	PROPN
cjfa-8193	143	26	(	(	PUNCT
cjfa-8193	143	27	1982	1982	NUM
cjfa-8193	143	28	)	)	PUNCT
cjfa-8193	143	29	.	.	PUNCT
cjfa-8193	144	1	the	the	DET
cjfa-8193	144	2	model	model	NOUN
cjfa-8193	144	3	specifies	specifie	NOUN
cjfa-8193	144	4	that	that	PRON
cjfa-8193	144	5	the	the	DET
cjfa-8193	144	6	conditional	conditional	ADJ
cjfa-8193	144	7	variance	variance	NOUN
cjfa-8193	144	8	is	be	AUX
cjfa-8193	144	9	a	a	DET
cjfa-8193	144	10	function	function	NOUN
cjfa-8193	144	11	of	of	ADP
cjfa-8193	144	12	the	the	DET
cjfa-8193	144	13	lagged	lag	VERB
cjfa-8193	144	14	squared	square	VERB
cjfa-8193	144	15	residuals	residual	NOUN
cjfa-8193	144	16	as	as	ADV
cjfa-8193	144	17	well	well	ADV
cjfa-8193	144	18	as	as	ADP
cjfa-8193	144	19	of	of	ADP
cjfa-8193	144	20	its	its	PRON
cjfa-8193	144	21	past	past	ADJ
cjfa-8193	144	22	conditional	conditional	ADJ
cjfa-8193	144	23	variances	variance	NOUN
cjfa-8193	144	24	.	.	PUNCT
cjfa-8193	145	1	although	although	SCONJ
cjfa-8193	145	2	the	the	DET
cjfa-8193	145	3	equation	equation	NOUN
cjfa-8193	145	4	may	may	AUX
cjfa-8193	145	5	be	be	AUX
cjfa-8193	145	6	specified	specify	VERB
cjfa-8193	145	7	with	with	ADP
cjfa-8193	145	8	a	a	DET
cjfa-8193	145	9	number	number	NOUN
cjfa-8193	145	10	of	of	ADP
cjfa-8193	145	11	lags	lag	NOUN
cjfa-8193	145	12	in	in	ADP
cjfa-8193	145	13	each	each	DET
cjfa-8193	145	14	term	term	NOUN
cjfa-8193	145	15	a	a	DET
cjfa-8193	145	16	single	single	ADJ
cjfa-8193	145	17	lag	lag	NOUN
cjfa-8193	145	18	in	in	ADP
cjfa-8193	145	19	each	each	PRON
cjfa-8193	145	20	is	be	AUX
cjfa-8193	145	21	usually	usually	ADV
cjfa-8193	145	22	adequate	adequate	ADJ
cjfa-8193	145	23	in	in	ADP
cjfa-8193	145	24	financial	financial	ADJ
cjfa-8193	145	25	market	market	NOUN
cjfa-8193	145	26	data	datum	NOUN
cjfa-8193	145	27	.	.	PUNCT
cjfa-8193	146	1	we	we	PRON
cjfa-8193	146	2	follow	follow	VERB
cjfa-8193	146	3	this	this	DET
cjfa-8193	146	4	conversion	conversion	NOUN
cjfa-8193	146	5	in	in	ADP
cjfa-8193	146	6	this	this	DET
cjfa-8193	146	7	paper	paper	NOUN
cjfa-8193	146	8	.	.	PUNCT
cjfa-8193	147	1	(	(	PUNCT
cjfa-8193	147	2	ii	ii	NOUN
cjfa-8193	147	3	)	)	PUNCT
cjfa-8193	147	4	egarch	egarch	NOUN
cjfa-8193	147	5	it	it	PRON
cjfa-8193	147	6	is	be	AUX
cjfa-8193	147	7	often	often	ADV
cjfa-8193	147	8	observed	observe	VERB
cjfa-8193	147	9	that	that	SCONJ
cjfa-8193	147	10	volatilities	volatility	NOUN
cjfa-8193	147	11	associated	associate	VERB
cjfa-8193	147	12	with	with	ADP
cjfa-8193	147	13	downward	downward	ADJ
cjfa-8193	147	14	movements	movement	NOUN
cjfa-8193	147	15	in	in	ADP
cjfa-8193	147	16	financial	financial	ADJ
cjfa-8193	147	17	markets	market	NOUN
cjfa-8193	147	18	are	be	AUX
cjfa-8193	147	19	greater	great	ADJ
cjfa-8193	147	20	than	than	ADP
cjfa-8193	147	21	the	the	DET
cjfa-8193	147	22	volatilities	volatility	NOUN
cjfa-8193	147	23	observed	observe	VERB
cjfa-8193	147	24	by	by	ADP
cjfa-8193	147	25	upward	upward	ADJ
cjfa-8193	147	26	movements	movement	NOUN
cjfa-8193	147	27	of	of	ADP
cjfa-8193	147	28	the	the	DET
cjfa-8193	147	29	same	same	ADJ
cjfa-8193	147	30	magnitude	magnitude	NOUN
cjfa-8193	147	31	.	.	PUNCT
cjfa-8193	148	1	in	in	ADP
cjfa-8193	148	2	such	such	ADJ
cjfa-8193	148	3	circumstances	circumstance	NOUN
cjfa-8193	148	4	the	the	DET
cjfa-8193	148	5	symmetry	symmetry	NOUN
cjfa-8193	148	6	imposed	impose	VERB
cjfa-8193	148	7	on	on	ADP
cjfa-8193	148	8	the	the	DET
cjfa-8193	148	9	conditional	conditional	ADJ
cjfa-8193	148	10	variance	variance	NOUN
cjfa-8193	148	11	structure	structure	NOUN
cjfa-8193	148	12	in	in	ADP
cjfa-8193	148	13	the	the	DET
cjfa-8193	148	14	garch	garch	NOUN
cjfa-8193	148	15	model	model	NOUN
cjfa-8193	148	16	may	may	AUX
cjfa-8193	148	17	not	not	PART
cjfa-8193	148	18	be	be	AUX
cjfa-8193	148	19	appropriate	appropriate	ADJ
cjfa-8193	148	20	.	.	PUNCT
cjfa-8193	149	1	to	to	PART
cjfa-8193	149	2	address	address	VERB
cjfa-8193	149	3	this	this	DET
cjfa-8193	149	4	issue	issue	NOUN
cjfa-8193	149	5	,	,	PUNCT
cjfa-8193	149	6	nelson	nelson	PROPN
cjfa-8193	149	7	(	(	PUNCT
cjfa-8193	149	8	1991	1991	NUM
cjfa-8193	149	9	)	)	PUNCT
cjfa-8193	149	10	proposes	propose	VERB
cjfa-8193	149	11	the	the	DET
cjfa-8193	149	12	exponential	exponential	ADJ
cjfa-8193	149	13	garch	garch	NOUN
cjfa-8193	149	14	(	(	PUNCT
cjfa-8193	149	15	egarch	egarch	NOUN
cjfa-8193	149	16	)	)	PUNCT
cjfa-8193	149	17	model	model	NOUN
cjfa-8193	149	18	.	.	PUNCT
cjfa-8193	150	1	the	the	DET
cjfa-8193	150	2	specification	specification	NOUN
cjfa-8193	150	3	for	for	ADP
cjfa-8193	150	4	the	the	DET
cjfa-8193	150	5	conditional	conditional	ADJ
cjfa-8193	150	6	variance	variance	NOUN
cjfa-8193	150	7	is	be	AUX
cjfa-8193	150	8	:	:	PUNCT
cjfa-8193	150	9	�	�	PROPN
cjfa-8193	150	10	�	�	PROPN
cjfa-8193	150	11	�	�	PROPN
cjfa-8193	150	12	�	�	PROPN
cjfa-8193	150	13	�	�	PROPN
cjfa-8193	150	14	�	�	PROPN
cjfa-8193	150	15	�	�	PROPN
cjfa-8193	150	16	�	�	PROPN
cjfa-8193	150	17	�	�	PROPN
cjfa-8193	150	18	[	[	X
cjfa-8193	150	19	�	�	PROPN
cjfa-8193	150	20	�	�	PROPN
cjfa-8193	150	21	�	�	PROPN
cjfa-8193	150	22	�	�	PROPN
cjfa-8193	150	23	�	�	PROPN
cjfa-8193	150	24	�	�	PROPN
cjfa-8193	150	25	]	]	SYM
cjfa-8193	150	26	�	�	PROPN
cjfa-8193	150	27	�	�	PROPN
cjfa-8193	150	28	[	[	SYM
cjfa-8193	150	29	�	�	PROPN
cjfa-8193	150	30	�	�	PROPN
cjfa-8193	150	31	�	�	PROPN
cjfa-8193	150	32	�	�	PROPN
cjfa-8193	150	33	�	�	PROPN
cjfa-8193	150	34	�	�	PROPN
cjfa-8193	150	35	]	]	SYM
cjfa-8193	150	36	�	�	PROPN
cjfa-8193	150	37	�	�	PROPN
cjfa-8193	150	38	�	�	PROPN
cjfa-8193	150	39	�	�	PROPN
cjfa-8193	150	40	�	�	PROPN
cjfa-8193	150	41	�	�	PROPN
cjfa-8193	150	42	�	�	PROPN
cjfa-8193	150	43	[	[	X
cjfa-8193	150	44	3	3	NUM
cjfa-8193	150	45	]	]	PUNCT
cjfa-8193	150	46	where	where	SCONJ
cjfa-8193	150	47	�	�	PROPN
cjfa-8193	150	48	�	�	PROPN
cjfa-8193	150	49	�	�	PROPN
cjfa-8193	150	50	�	�	PROPN
cjfa-8193	150	51	�	�	PROPN
cjfa-8193	150	52	�	�	PROPN
cjfa-8193	150	53	�	�	PROPN
cjfa-8193	150	54	�	�	PROPN
cjfa-8193	150	55	�	�	PROPN
cjfa-8193	150	56	�	�	PROPN
cjfa-8193	150	57	�	�	PROPN
cjfa-8193	150	58	�	�	PROPN
cjfa-8193	150	59	�	�	PROPN
cjfa-8193	150	60	�	�	PROPN
cjfa-8193	150	61	�	�	PROPN
cjfa-8193	150	62	�	�	PROPN
cjfa-8193	150	63	�	�	PROPN
cjfa-8193	150	64	�	�	PROPN
cjfa-8193	150	65	�	�	PROPN
cjfa-8193	150	66	�	�	PROPN
cjfa-8193	150	67	�	�	PROPN
cjfa-8193	150	68	�	�	PROPN
cjfa-8193	150	69	�	�	PROPN
cjfa-8193	150	70	�	�	PROPN
cjfa-8193	150	71	[	[	X
cjfa-8193	150	72	|	|	PROPN
cjfa-8193	150	73	�	�	PROPN
cjfa-8193	150	74	�	�	PROPN
cjfa-8193	150	75	|	|	PROPN
cjfa-8193	150	76	�	�	PROPN
cjfa-8193	150	77	�	�	PROPN
cjfa-8193	150	78	|	|	PROPN
cjfa-8193	150	79	�	�	PROPN
cjfa-8193	150	80	�	�	PROPN
cjfa-8193	150	81	|	|	NOUN
cjfa-8193	150	82	]	]	SYM
cjfa-8193	150	83	�	�	PROPN
cjfa-8193	150	84	�	�	PROPN
cjfa-8193	150	85	�	�	PROPN
cjfa-8193	150	86	�	�	PROPN
cjfa-8193	150	87	�	�	PROPN
cjfa-8193	150	88	�	�	PROPN
cjfa-8193	150	89	�	�	PROPN
cjfa-8193	150	90	�	�	PROPN
cjfa-8193	150	91	�	�	PROPN
cjfa-8193	150	92	�	�	PROPN
cjfa-8193	150	93	�	�	PROPN
cjfa-8193	150	94	�	�	PROPN
cjfa-8193	150	95	�	�	PROPN
cjfa-8193	150	96	�	�	PROPN
cjfa-8193	150	97	�	�	PROPN
cjfa-8193	150	98	�	�	PROPN
cjfa-8193	150	99	�	�	PROPN
cjfa-8193	150	100	�	�	PROPN
cjfa-8193	150	101	�	�	PROPN
cjfa-8193	150	102	�	�	PROPN
cjfa-8193	150	103	�	�	PROPN
cjfa-8193	150	104	�	�	PROPN
cjfa-8193	150	105	�	�	PROPN
cjfa-8193	150	106	�	�	PROPN
cjfa-8193	150	107	�	�	PROPN
cjfa-8193	150	108	�	�	AUX
cjfa-8193	150	109	the	the	DET
cjfa-8193	150	110	log	log	NOUN
cjfa-8193	150	111	specification	specification	NOUN
cjfa-8193	150	112	implies	imply	VERB
cjfa-8193	150	113	that	that	SCONJ
cjfa-8193	150	114	the	the	DET
cjfa-8193	150	115	asymmetric	asymmetric	ADJ
cjfa-8193	150	116	effect	effect	NOUN
cjfa-8193	150	117	is	be	AUX
cjfa-8193	150	118	exponential	exponential	ADJ
cjfa-8193	150	119	,	,	PUNCT
cjfa-8193	150	120	rather	rather	ADV
cjfa-8193	150	121	than	than	ADP
cjfa-8193	150	122	quadratic	quadratic	ADJ
cjfa-8193	150	123	,	,	PUNCT
cjfa-8193	150	124	and	and	CCONJ
cjfa-8193	150	125	that	that	SCONJ
cjfa-8193	150	126	forecasts	forecast	NOUN
cjfa-8193	150	127	of	of	ADP
cjfa-8193	150	128	the	the	DET
cjfa-8193	150	129	conditional	conditional	ADJ
cjfa-8193	150	130	variance	variance	NOUN
cjfa-8193	150	131	that	that	PRON
cjfa-8193	150	132	are	be	AUX
cjfa-8193	150	133	generated	generate	VERB
cjfa-8193	150	134	are	be	AUX
cjfa-8193	150	135	nonnegative	nonnegative	ADJ
cjfa-8193	150	136	.	.	PUNCT
cjfa-8193	151	1	the	the	DET
cjfa-8193	151	2	presence	presence	NOUN
cjfa-8193	151	3	of	of	ADP
cjfa-8193	151	4	asymmetry	asymmetry	NOUN
cjfa-8193	151	5	effects	effect	NOUN
cjfa-8193	151	6	is	be	AUX
cjfa-8193	151	7	tested	test	VERB
cjfa-8193	151	8	in	in	ADP
cjfa-8193	151	9	terms	term	NOUN
cjfa-8193	151	10	of	of	ADP
cjfa-8193	151	11	the	the	DET
cjfa-8193	151	12	sign	sign	NOUN
cjfa-8193	151	13	and	and	CCONJ
cjfa-8193	151	14	magnitude	magnitude	NOUN
cjfa-8193	151	15	effects	effect	NOUN
cjfa-8193	151	16	identified	identify	VERB
cjfa-8193	151	17	above	above	ADV
cjfa-8193	151	18	.	.	PUNCT
cjfa-8193	152	1	(	(	PUNCT
cjfa-8193	152	2	iii	iii	X
cjfa-8193	152	3	)	)	PUNCT
cjfa-8193	152	4	gjr	gjr	NOUN
cjfa-8193	152	5	-	-	PUNCT
cjfa-8193	152	6	garch	garch	NOUN
cjfa-8193	152	7	]	]	X
cjfa-8193	152	8	2	2	NUM
cjfa-8193	152	9	[	[	PUNCT
cjfa-8193	152	10	1	1	NUM
cjfa-8193	152	11	2	2	NUM
cjfa-8193	152	12	1	1	NUM
cjfa-8193	152	13	22	22	NUM
cjfa-8193	152	14			PRON
cjfa-8193	152	15			NUM
cjfa-8193	152	16			PROPN
cjfa-8193	152	17			PROPN
cjfa-8193	152	18			PROPN
cjfa-8193	152	19			PUNCT
cjfa-8193	152	20	p	p	NOUN
cjfa-8193	152	21	j	j	PROPN
cjfa-8193	152	22	jtj	jtj	VERB
cjfa-8193	152	23	q	q	PROPN
cjfa-8193	153	1	i	i	PRON
cjfa-8193	153	2	itit	itit	VERB
cjfa-8193	153	3	u	u	NOUN
cjfa-8193	153	4			VERB
cjfa-8193	153	5	the	the	DET
cjfa-8193	153	6	log	log	NOUN
cjfa-8193	153	7	specification	specification	NOUN
cjfa-8193	153	8	implies	imply	VERB
cjfa-8193	153	9	that	that	SCONJ
cjfa-8193	153	10	the	the	DET
cjfa-8193	153	11	asymmetric	asymmetric	ADJ
cjfa-8193	153	12	effect	effect	NOUN
cjfa-8193	153	13	is	be	AUX
cjfa-8193	153	14	exponential	exponential	ADJ
cjfa-8193	153	15	,	,	PUNCT
cjfa-8193	153	16	rather	rather	ADV
cjfa-8193	153	17	than	than	ADP
cjfa-8193	153	18	quadratic	quadratic	ADJ
cjfa-8193	153	19	,	,	PUNCT
cjfa-8193	153	20	and	and	CCONJ
cjfa-8193	153	21	that	that	SCONJ
cjfa-8193	153	22	forecasts	forecast	NOUN
cjfa-8193	153	23	of	of	ADP
cjfa-8193	153	24	the	the	DET
cjfa-8193	153	25	conditional	conditional	ADJ
cjfa-8193	153	26	variance	variance	NOUN
cjfa-8193	153	27	that	that	PRON
cjfa-8193	153	28	are	be	AUX
cjfa-8193	153	29	generated	generate	VERB
cjfa-8193	153	30	are	be	AUX
cjfa-8193	153	31	non	non	ADJ
cjfa-8193	153	32	-	-	ADJ
cjfa-8193	153	33	negative	negative	ADJ
cjfa-8193	153	34	.	.	PUNCT
cjfa-8193	154	1	the	the	DET
cjfa-8193	154	2	presence	presence	NOUN
cjfa-8193	154	3	of	of	ADP
cjfa-8193	154	4	asymmetry	asymmetry	NOUN
cjfa-8193	154	5	effects	effect	NOUN
cjfa-8193	154	6	is	be	AUX
cjfa-8193	154	7	tested	test	VERB
cjfa-8193	154	8	in	in	ADP
cjfa-8193	154	9	terms	term	NOUN
cjfa-8193	154	10	of	of	ADP
cjfa-8193	154	11	the	the	DET
cjfa-8193	154	12	sign	sign	NOUN
cjfa-8193	154	13	and	and	CCONJ
cjfa-8193	154	14	magnitude	magnitude	NOUN
cjfa-8193	154	15	effects	effect	NOUN
cjfa-8193	154	16	identified	identify	VERB
cjfa-8193	154	17	above	above	ADV
cjfa-8193	154	18	.	.	PUNCT
cjfa-8193	155	1	(	(	PUNCT
cjfa-8193	155	2	iii	iii	NOUN
cjfa-8193	155	3	)	)	PUNCT
cjfa-8193	155	4	 	 	SPACE
cjfa-8193	155	5	gjr	gjr	NOUN
cjfa-8193	155	6	-	-	PUNCT
cjfa-8193	155	7	garch	garch	NOUN
cjfa-8193	155	8	this	this	DET
cjfa-8193	155	9	variation	variation	NOUN
cjfa-8193	155	10	on	on	ADP
cjfa-8193	155	11	the	the	DET
cjfa-8193	155	12	garch	garch	NOUN
cjfa-8193	155	13	model	model	NOUN
cjfa-8193	155	14	was	be	AUX
cjfa-8193	155	15	proposed	propose	VERB
cjfa-8193	155	16	by	by	ADP
cjfa-8193	155	17	glosten	glosten	ADJ
cjfa-8193	155	18	,	,	PUNCT
cjfa-8193	155	19	jagannathan	jagannathan	NOUN
cjfa-8193	155	20	,	,	PUNCT
cjfa-8193	155	21	and	and	CCONJ
cjfa-8193	155	22	runkle	runkle	ADJ
cjfa-8193	155	23	(	(	PUNCT
cjfa-8193	155	24	1993	1993	NUM
cjfa-8193	155	25	)	)	PUNCT
cjfa-8193	155	26	as	as	ADP
cjfa-8193	155	27	an	an	DET
cjfa-8193	155	28	alternative	alternative	ADJ
cjfa-8193	155	29	way	way	NOUN
cjfa-8193	155	30	of	of	ADP
cjfa-8193	155	31	dealing	deal	VERB
cjfa-8193	155	32	with	with	ADP
cjfa-8193	155	33	asymmetric	asymmetric	ADJ
cjfa-8193	155	34	shocks	shock	NOUN
cjfa-8193	155	35	in	in	ADP
cjfa-8193	155	36	financial	financial	ADJ
cjfa-8193	155	37	series	series	NOUN
cjfa-8193	155	38	.	.	PUNCT
cjfa-8193	156	1	its	its	PRON
cjfa-8193	156	2	generalized	generalized	ADJ
cjfa-8193	156	3	version	version	NOUN
cjfa-8193	156	4	is	be	AUX
cjfa-8193	156	5	:	:	PUNCT
cjfa-8193	156	6	this	this	DET
cjfa-8193	156	7	variation	variation	NOUN
cjfa-8193	156	8	on	on	ADP
cjfa-8193	156	9	the	the	DET
cjfa-8193	156	10	garch	garch	NOUN
cjfa-8193	156	11	model	model	NOUN
cjfa-8193	156	12	was	be	AUX
cjfa-8193	156	13	proposed	propose	VERB
cjfa-8193	156	14	by	by	ADP
cjfa-8193	156	15	glosten	glosten	ADJ
cjfa-8193	156	16	,	,	PUNCT
cjfa-8193	156	17	jagannathan	jagannathan	NOUN
cjfa-8193	156	18	,	,	PUNCT
cjfa-8193	156	19	and	and	CCONJ
cjfa-8193	156	20	runkle	runkle	ADJ
cjfa-8193	156	21	(	(	PUNCT
cjfa-8193	156	22	1993	1993	NUM
cjfa-8193	156	23	)	)	PUNCT
cjfa-8193	156	24	as	as	ADP
cjfa-8193	156	25	an	an	DET
cjfa-8193	156	26	alternative	alternative	ADJ
cjfa-8193	156	27	way	way	NOUN
cjfa-8193	156	28	of	of	ADP
cjfa-8193	156	29	dealing	deal	VERB
cjfa-8193	156	30	with	with	ADP
cjfa-8193	156	31	asymmetric	asymmetric	ADJ
cjfa-8193	156	32	shocks	shock	NOUN
cjfa-8193	156	33	in	in	ADP
cjfa-8193	156	34	financial	financial	ADJ
cjfa-8193	156	35	series	series	NOUN
cjfa-8193	156	36	.	.	PUNCT
cjfa-8193	157	1	its	its	PRON
cjfa-8193	157	2	generalized	generalized	ADJ
cjfa-8193	157	3	version	version	NOUN
cjfa-8193	157	4	is	be	AUX
cjfa-8193	157	5	:	:	PUNCT
cjfa-8193	157	6	where	where	SCONJ
cjfa-8193	157	7	�	�	PROPN
cjfa-8193	157	8	�	�	PROPN
cjfa-8193	157	9	�	�	PROPN
cjfa-8193	157	10	is	be	AUX
cjfa-8193	157	11	a	a	DET
cjfa-8193	157	12	dummy	dummy	ADJ
cjfa-8193	157	13	variable	variable	NOUN
cjfa-8193	157	14	that	that	PRON
cjfa-8193	157	15	take	take	VERB
cjfa-8193	157	16	the	the	DET
cjfa-8193	157	17	value	value	NOUN
cjfa-8193	157	18	1	1	NUM
cjfa-8193	157	19	when	when	SCONJ
cjfa-8193	157	20	�	�	PROPN
cjfa-8193	157	21	�	�	PROPN
cjfa-8193	157	22	�	�	PROPN
cjfa-8193	157	23	�	�	PROPN
cjfa-8193	157	24	<	<	X
cjfa-8193	157	25	0	0	NUM
cjfa-8193	157	26	,	,	PUNCT
cjfa-8193	157	27	and	and	CCONJ
cjfa-8193	157	28	0	0	NUM
cjfa-8193	157	29	when	when	SCONJ
cjfa-8193	157	30	�	�	PROPN
cjfa-8193	157	31	�	�	PROPN
cjfa-8193	157	32	�	�	PROPN
cjfa-8193	157	33	�	�	PROPN
cjfa-8193	157	34	≥	≥	NUM
cjfa-8193	157	35	0	0	NUM
cjfa-8193	157	36	.	.	PUNCT
cjfa-8193	158	1	a	a	DET
cjfa-8193	158	2	feature	feature	NOUN
cjfa-8193	158	3	of	of	ADP
cjfa-8193	158	4	the	the	DET
cjfa-8193	158	5	gjr	gjr	NOUN
cjfa-8193	158	6	model	model	NOUN
cjfa-8193	158	7	is	be	AUX
cjfa-8193	158	8	that	that	SCONJ
cjfa-8193	158	9	the	the	DET
cjfa-8193	158	10	null	null	ADJ
cjfa-8193	158	11	hypothesis	hypothesis	NOUN
cjfa-8193	158	12	of	of	ADP
cjfa-8193	158	13	no	no	DET
cjfa-8193	158	14	leverage	leverage	NOUN
cjfa-8193	158	15	(	(	PUNCT
cjfa-8193	158	16	asymmetry	asymmetry	NOUN
cjfa-8193	158	17	)	)	PUNCT
cjfa-8193	158	18	effect	effect	NOUN
cjfa-8193	158	19	is	be	AUX
cjfa-8193	158	20	simple	simple	ADJ
cjfa-8193	158	21	to	to	PART
cjfa-8193	158	22	test	test	VERB
cjfa-8193	158	23	.	.	PUNCT
cjfa-8193	159	1	indeed	indeed	ADV
cjfa-8193	159	2	,	,	PUNCT
cjfa-8193	159	3	γ1	γ1	PROPN
cjfa-8193	159	4	=	=	SYM
cjfa-8193	159	5	…	…	PUNCT
cjfa-8193	159	6	=	=	SYM
cjfa-8193	159	7	γq	γq	ADP
cjfa-8193	159	8	=	=	SYM
cjfa-8193	159	9	0	0	NUM
cjfa-8193	159	10	implies	imply	VERB
cjfa-8193	159	11	that	that	SCONJ
cjfa-8193	159	12	the	the	DET
cjfa-8193	159	13	impact	impact	NOUN
cjfa-8193	159	14	of	of	ADP
cjfa-8193	159	15	a	a	DET
cjfa-8193	159	16	shock	shock	NOUN
cjfa-8193	159	17	is	be	AUX
cjfa-8193	159	18	symmetric	symmetric	ADJ
cjfa-8193	159	19	,	,	PUNCT
cjfa-8193	159	20	i.e.	i.e.	X
cjfa-8193	159	21	,	,	PUNCT
cjfa-8193	159	22	past	past	ADP
cjfa-8193	159	23	positive	positive	ADJ
cjfa-8193	159	24	shocks	shock	NOUN
cjfa-8193	159	25	have	have	VERB
cjfa-8193	159	26	the	the	DET
cjfa-8193	159	27	same	same	ADJ
cjfa-8193	159	28	impact	impact	NOUN
cjfa-8193	159	29	on	on	ADP
cjfa-8193	159	30	today	today	NOUN
cjfa-8193	159	31	’s	’s	PART
cjfa-8193	159	32	volatility	volatility	NOUN
cjfa-8193	159	33	as	as	ADP
cjfa-8193	159	34	past	past	ADP
cjfa-8193	159	35	negative	negative	ADJ
cjfa-8193	159	36	shocks	shock	NOUN
cjfa-8193	159	37	.	.	PUNCT
cjfa-8193	160	1	they	they	PRON
cjfa-8193	160	2	do	do	AUX
cjfa-8193	160	3	have	have	VERB
cjfa-8193	160	4	a	a	DET
cjfa-8193	160	5	drawback	drawback	NOUN
cjfa-8193	160	6	in	in	ADP
cjfa-8193	160	7	that	that	SCONJ
cjfa-8193	160	8	they	they	PRON
cjfa-8193	160	9	are	be	AUX
cjfa-8193	160	10	symmetric	symmetric	ADJ
cjfa-8193	160	11	.	.	PUNCT
cjfa-8193	161	1	our	our	PRON
cjfa-8193	161	2	preferred	preferred	ADJ
cjfa-8193	161	3	option	option	NOUN
cjfa-8193	161	4	is	be	AUX
cjfa-8193	161	5	therefore	therefore	ADV
cjfa-8193	161	6	the	the	DET
cjfa-8193	161	7	skewed	skewed	ADJ
cjfa-8193	161	8	-	-	PUNCT
cjfa-8193	161	9	student	student	NOUN
cjfa-8193	161	10	density	density	NOUN
cjfa-8193	161	11	proposed	propose	VERB
cjfa-8193	161	12	by	by	ADP
cjfa-8193	161	13	fernández	fernández	PROPN
cjfa-8193	161	14	and	and	CCONJ
cjfa-8193	161	15	steel	steel	NOUN
cjfa-8193	161	16	(	(	PUNCT
cjfa-8193	161	17	1998	1998	NUM
cjfa-8193	161	18	)	)	PUNCT
cjfa-8193	161	19	.	.	PUNCT
cjfa-8193	162	1	(	(	PUNCT
cjfa-8193	162	2	iv	iv	X
cjfa-8193	162	3	)	)	PUNCT
cjfa-8193	162	4	gaussian	gaussian	NOUN
cjfa-8193	162	5	(	(	PUNCT
cjfa-8193	162	6	normal	normal	ADJ
cjfa-8193	162	7	)	)	PUNCT
cjfa-8193	162	8	distribution	distribution	NOUN
cjfa-8193	162	9	where	where	SCONJ
cjfa-8193	162	10	the	the	DET
cjfa-8193	162	11	log	log	NOUN
cjfa-8193	162	12	-	-	PUNCT
cjfa-8193	162	13	likelihood	likelihood	NOUN
cjfa-8193	162	14	function	function	NOUN
cjfa-8193	162	15	of	of	ADP
cjfa-8193	162	16	the	the	DET
cjfa-8193	162	17	distribution	distribution	NOUN
cjfa-8193	162	18	is	be	AUX
cjfa-8193	162	19	:	:	PUNCT
cjfa-8193	162	20	(	(	PUNCT
cjfa-8193	162	21	v	v	NOUN
cjfa-8193	162	22	)	)	PUNCT
cjfa-8193	162	23	student	student	NOUN
cjfa-8193	162	24	-	-	PUNCT
cjfa-8193	162	25	t	t	NOUN
cjfa-8193	162	26	distribution	distribution	NOUN
cjfa-8193	162	27	where	where	SCONJ
cjfa-8193	162	28	the	the	DET
cjfa-8193	162	29	log	log	NOUN
cjfa-8193	162	30	-	-	PUNCT
cjfa-8193	162	31	likelihood	likelihood	NOUN
cjfa-8193	162	32	function	function	NOUN
cjfa-8193	162	33	of	of	ADP
cjfa-8193	162	34	the	the	DET
cjfa-8193	162	35	distribution	distribution	NOUN
cjfa-8193	162	36	is	be	AUX
cjfa-8193	162	37	:	:	PUNCT
cjfa-8193	162	38	(	(	PUNCT
cjfa-8193	162	39	vi	vi	NOUN
cjfa-8193	162	40	)	)	PUNCT
cjfa-8193	162	41	generalized	generalize	VERB
cjfa-8193	162	42	error	error	NOUN
cjfa-8193	162	43	distribution	distribution	NOUN
cjfa-8193	162	44	(	(	PUNCT
cjfa-8193	162	45	ged	ge	VERB
cjfa-8193	162	46	)	)	PUNCT
cjfa-8193	162	47	where	where	SCONJ
cjfa-8193	162	48	the	the	DET
cjfa-8193	162	49	log	log	NOUN
cjfa-8193	162	50	-	-	PUNCT
cjfa-8193	162	51	likelihood	likelihood	NOUN
cjfa-8193	162	52	function	function	NOUN
cjfa-8193	162	53	of	of	ADP
cjfa-8193	162	54	the	the	DET
cjfa-8193	162	55	distribution	distribution	NOUN
cjfa-8193	162	56	is	be	AUX
cjfa-8193	162	57	:	:	PUNCT
cjfa-8193	162	58	(	(	PUNCT
cjfa-8193	162	59	vii	vii	PROPN
cjfa-8193	162	60	)	)	PUNCT
cjfa-8193	162	61	standardized	standardized	ADJ
cjfa-8193	162	62	(	(	PUNCT
cjfa-8193	162	63	zero	zero	NUM
cjfa-8193	162	64	mean	mean	NOUN
cjfa-8193	162	65	and	and	CCONJ
cjfa-8193	162	66	unit	unit	NOUN
cjfa-8193	162	67	variance	variance	NOUN
cjfa-8193	162	68	)	)	PUNCT
cjfa-8193	162	69	skewed	skewed	ADJ
cjfa-8193	162	70	-	-	PUNCT
cjfa-8193	162	71	student	student	NOUN
cjfa-8193	162	72	distribution	distribution	NOUN
cjfa-8193	162	73	]	]	PUNCT
cjfa-8193	162	74	4	4	NUM
cjfa-8193	162	75	[	[	NOUN
cjfa-8193	162	76	)	)	PUNCT
cjfa-8193	162	77	(	(	PUNCT
cjfa-8193	162	78	2	2	NUM
cjfa-8193	162	79	1	1	NUM
cjfa-8193	162	80	2	2	NUM
cjfa-8193	162	81	1	1	NUM
cjfa-8193	162	82	22	22	NUM
cjfa-8193	162	83	jt	jt	PROPN
cjfa-8193	162	84	p	p	PROPN
cjfa-8193	162	85	j	j	PROPN
cjfa-8193	162	86	jititi	jititi	PROPN
cjfa-8193	162	87	q	q	PROPN
cjfa-8193	163	1	i	i	PRON
cjfa-8193	163	2	itit	itit	VERB
cjfa-8193	163	3	s	s	PART
cjfa-8193	163	4			PROPN
cjfa-8193	163	5			PROPN
cjfa-8193	163	6			PROPN
cjfa-8193	163	7			PROPN
cjfa-8193	163	8			PROPN
cjfa-8193	163	9			PROPN
cjfa-8193	163	10			PROPN
cjfa-8193	163	11			PRON
cjfa-8193	163	12			VERB
cjfa-8193	163	13			PROPN
cjfa-8193	163	14	]	]	SYM
cjfa-8193	163	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	163	16	(	(	PUNCT
cjfa-8193	163	17	2	2	NUM
cjfa-8193	163	18	1	1	NUM
cjfa-8193	163	19	2	2	NUM
cjfa-8193	163	20	1	1	NUM
cjfa-8193	163	21	2	2	NUM
cjfa-8193	163	22	t	t	NOUN
cjfa-8193	163	23	t	t	NOUN
cjfa-8193	163	24	t	t	NOUN
cjfa-8193	163	25	tnorm	tnorm	NOUN
cjfa-8193	164	1	zl	zl	PROPN
cjfa-8193	165	1			PROPN
cjfa-8193	165	2			NUM
cjfa-8193	165	3			NUM
cjfa-8193	165	4			VERB
cjfa-8193	165	5			PROPN
cjfa-8193	165	6			PROPN
cjfa-8193	165	7	]	]	SYM
cjfa-8193	165	8	6	6	NUM
cjfa-8193	165	9	[	[	SYM
cjfa-8193	165	10	2	2	NUM
cjfa-8193	165	11	1log)1()log	1log)1()log	NUM
cjfa-8193	165	12	(	(	PUNCT
cjfa-8193	165	13	2	2	NUM
cjfa-8193	165	14	1	1	NUM
cjfa-8193	165	15	)	)	PUNCT
cjfa-8193	165	16	2(log	2(log	NOUN
cjfa-8193	165	17	2	2	NUM
cjfa-8193	165	18	1	1	NUM
cjfa-8193	165	19	2	2	NUM
cjfa-8193	165	20	log	log	NOUN
cjfa-8193	165	21	2	2	NUM
cjfa-8193	165	22	1log	1log	NUM
cjfa-8193	165	23	1	1	NUM
cjfa-8193	165	24	2	2	NUM
cjfa-8193	165	25	2	2	NUM
cjfa-8193	165	26			ADJ
cjfa-8193	165	27			PROPN
cjfa-8193	165	28			PROPN
cjfa-8193	165	29			PRON
cjfa-8193	165	30			NOUN
cjfa-8193	165	31			VERB
cjfa-8193	165	32			PROPN
cjfa-8193	165	33			NOUN
cjfa-8193	165	34			NOUN
cjfa-8193	165	35			PROPN
cjfa-8193	165	36			PROPN
cjfa-8193	165	37			PROPN
cjfa-8193	165	38			NOUN
cjfa-8193	165	39			PROPN
cjfa-8193	165	40			PROPN
cjfa-8193	165	41			PROPN
cjfa-8193	165	42			PROPN
cjfa-8193	166	1			PROPN
cjfa-8193	166	2			INTJ
cjfa-8193	166	3			NUM
cjfa-8193	166	4			ADV
cjfa-8193	166	5			VERB
cjfa-8193	166	6			NOUN
cjfa-8193	166	7			PRON
cjfa-8193	166	8			PROPN
cjfa-8193	166	9			PROPN
cjfa-8193	166	10			NOUN
cjfa-8193	166	11			NUM
cjfa-8193	166	12			PRON
cjfa-8193	166	13			PROPN
cjfa-8193	166	14			PROPN
cjfa-8193	166	15			NOUN
cjfa-8193	166	16			PUNCT
cjfa-8193	167	1	t	t	PROPN
cjfa-8193	167	2	t	t	PROPN
cjfa-8193	167	3	t	t	PROPN
cjfa-8193	167	4	t	t	PROPN
cjfa-8193	167	5	stud	stud	NOUN
cjfa-8193	167	6	v	v	ADP
cjfa-8193	167	7	z	z	PROPN
cjfa-8193	167	8	tl	tl	PROPN
cjfa-8193	167	9			PROPN
cjfa-8193	167	10			NOUN
cjfa-8193	167	11	]	]	PUNCT
cjfa-8193	167	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	167	13	1	1	NUM
cjfa-8193	167	14	21	21	NUM
cjfa-8193	167	15			PROPN
cjfa-8193	167	16			NOUN
cjfa-8193	167	17			NOUN
cjfa-8193	167	18			PROPN
cjfa-8193	167	19			PROPN
cjfa-8193	167	20			X
cjfa-8193	167	21			NOUN
cjfa-8193	167	22			NOUN
cjfa-8193	167	23			NOUN
cjfa-8193	168	1			PROPN
cjfa-8193	168	2			NOUN
cjfa-8193	168	3			NOUN
cjfa-8193	168	4			PRON
cjfa-8193	168	5			PROPN
cjfa-8193	169	1			PROPN
cjfa-8193	169	2			NOUN
cjfa-8193	169	3			NOUN
cjfa-8193	169	4			PROPN
cjfa-8193	169	5			PROPN
cjfa-8193	169	6			PROPN
cjfa-8193	169	7			NOUN
cjfa-8193	170	1			PROPN
cjfa-8193	170	2	t	t	PROPN
cjfa-8193	170	3	t	t	PROPN
cjfa-8193	170	4	t	t	PROPN
cjfa-8193	170	5	t	t	PROPN
cjfa-8193	170	6	ged	ge	VERB
cjfa-8193	170	7	zl	zl	PROPN
cjfa-8193	170	8			PROPN
cjfa-8193	170	9			ADJ
cjfa-8193	170	10			NOUN
cjfa-8193	170	11			NOUN
cjfa-8193	170	12			ADJ
cjfa-8193	170	13			ADJ
cjfa-8193	170	14			NOUN
cjfa-8193	170	15	[	[	X
cjfa-8193	170	16	4	4	NUM
cjfa-8193	170	17	]	]	PUNCT
cjfa-8193	170	18	where	where	SCONJ
cjfa-8193	170	19	this	this	DET
cjfa-8193	170	20	variation	variation	NOUN
cjfa-8193	170	21	on	on	ADP
cjfa-8193	170	22	the	the	DET
cjfa-8193	170	23	garch	garch	NOUN
cjfa-8193	170	24	model	model	NOUN
cjfa-8193	170	25	was	be	AUX
cjfa-8193	170	26	proposed	propose	VERB
cjfa-8193	170	27	by	by	ADP
cjfa-8193	170	28	glosten	glosten	ADJ
cjfa-8193	170	29	,	,	PUNCT
cjfa-8193	170	30	jagannathan	jagannathan	NOUN
cjfa-8193	170	31	,	,	PUNCT
cjfa-8193	170	32	and	and	CCONJ
cjfa-8193	170	33	runkle	runkle	ADJ
cjfa-8193	170	34	(	(	PUNCT
cjfa-8193	170	35	1993	1993	NUM
cjfa-8193	170	36	)	)	PUNCT
cjfa-8193	170	37	as	as	ADP
cjfa-8193	170	38	an	an	DET
cjfa-8193	170	39	alternative	alternative	ADJ
cjfa-8193	170	40	way	way	NOUN
cjfa-8193	170	41	of	of	ADP
cjfa-8193	170	42	dealing	deal	VERB
cjfa-8193	170	43	with	with	ADP
cjfa-8193	170	44	asymmetric	asymmetric	ADJ
cjfa-8193	170	45	shocks	shock	NOUN
cjfa-8193	170	46	in	in	ADP
cjfa-8193	170	47	financial	financial	ADJ
cjfa-8193	170	48	series	series	NOUN
cjfa-8193	170	49	.	.	PUNCT
cjfa-8193	171	1	its	its	PRON
cjfa-8193	171	2	generalized	generalized	ADJ
cjfa-8193	171	3	version	version	NOUN
cjfa-8193	171	4	is	be	AUX
cjfa-8193	171	5	:	:	PUNCT
cjfa-8193	171	6	where	where	SCONJ
cjfa-8193	171	7	�	�	PROPN
cjfa-8193	171	8	�	�	PROPN
cjfa-8193	171	9	�	�	PROPN
cjfa-8193	171	10	is	be	AUX
cjfa-8193	171	11	a	a	DET
cjfa-8193	171	12	dummy	dummy	ADJ
cjfa-8193	171	13	variable	variable	NOUN
cjfa-8193	171	14	that	that	PRON
cjfa-8193	171	15	take	take	VERB
cjfa-8193	171	16	the	the	DET
cjfa-8193	171	17	value	value	NOUN
cjfa-8193	171	18	1	1	NUM
cjfa-8193	171	19	when	when	SCONJ
cjfa-8193	171	20	�	�	PROPN
cjfa-8193	171	21	�	�	PROPN
cjfa-8193	171	22	�	�	PROPN
cjfa-8193	171	23	�	�	PROPN
cjfa-8193	171	24	<	<	X
cjfa-8193	171	25	0	0	NUM
cjfa-8193	171	26	,	,	PUNCT
cjfa-8193	171	27	and	and	CCONJ
cjfa-8193	171	28	0	0	NUM
cjfa-8193	171	29	when	when	SCONJ
cjfa-8193	171	30	�	�	PROPN
cjfa-8193	171	31	�	�	PROPN
cjfa-8193	171	32	�	�	PROPN
cjfa-8193	171	33	�	�	PROPN
cjfa-8193	171	34	≥	≥	NUM
cjfa-8193	171	35	0	0	NUM
cjfa-8193	171	36	.	.	PUNCT
cjfa-8193	172	1	a	a	DET
cjfa-8193	172	2	feature	feature	NOUN
cjfa-8193	172	3	of	of	ADP
cjfa-8193	172	4	the	the	DET
cjfa-8193	172	5	gjr	gjr	NOUN
cjfa-8193	172	6	model	model	NOUN
cjfa-8193	172	7	is	be	AUX
cjfa-8193	172	8	that	that	SCONJ
cjfa-8193	172	9	the	the	DET
cjfa-8193	172	10	null	null	ADJ
cjfa-8193	172	11	hypothesis	hypothesis	NOUN
cjfa-8193	172	12	of	of	ADP
cjfa-8193	172	13	no	no	DET
cjfa-8193	172	14	leverage	leverage	NOUN
cjfa-8193	172	15	(	(	PUNCT
cjfa-8193	172	16	asymmetry	asymmetry	NOUN
cjfa-8193	172	17	)	)	PUNCT
cjfa-8193	172	18	effect	effect	NOUN
cjfa-8193	172	19	is	be	AUX
cjfa-8193	172	20	simple	simple	ADJ
cjfa-8193	172	21	to	to	PART
cjfa-8193	172	22	test	test	VERB
cjfa-8193	172	23	.	.	PUNCT
cjfa-8193	173	1	indeed	indeed	ADV
cjfa-8193	173	2	,	,	PUNCT
cjfa-8193	173	3	γ1	γ1	PROPN
cjfa-8193	173	4	=	=	SYM
cjfa-8193	173	5	…	…	PUNCT
cjfa-8193	173	6	=	=	SYM
cjfa-8193	173	7	γq	γq	ADP
cjfa-8193	173	8	=	=	SYM
cjfa-8193	173	9	0	0	NUM
cjfa-8193	173	10	implies	imply	VERB
cjfa-8193	173	11	that	that	SCONJ
cjfa-8193	173	12	the	the	DET
cjfa-8193	173	13	impact	impact	NOUN
cjfa-8193	173	14	of	of	ADP
cjfa-8193	173	15	a	a	DET
cjfa-8193	173	16	shock	shock	NOUN
cjfa-8193	173	17	is	be	AUX
cjfa-8193	173	18	symmetric	symmetric	ADJ
cjfa-8193	173	19	,	,	PUNCT
cjfa-8193	173	20	i.e.	i.e.	X
cjfa-8193	173	21	,	,	PUNCT
cjfa-8193	173	22	past	past	ADP
cjfa-8193	173	23	positive	positive	ADJ
cjfa-8193	173	24	shocks	shock	NOUN
cjfa-8193	173	25	have	have	VERB
cjfa-8193	173	26	the	the	DET
cjfa-8193	173	27	same	same	ADJ
cjfa-8193	173	28	impact	impact	NOUN
cjfa-8193	173	29	on	on	ADP
cjfa-8193	173	30	today	today	NOUN
cjfa-8193	173	31	’s	’s	PART
cjfa-8193	173	32	volatility	volatility	NOUN
cjfa-8193	173	33	as	as	ADP
cjfa-8193	173	34	past	past	ADP
cjfa-8193	173	35	negative	negative	ADJ
cjfa-8193	173	36	shocks	shock	NOUN
cjfa-8193	173	37	.	.	PUNCT
cjfa-8193	174	1	they	they	PRON
cjfa-8193	174	2	do	do	AUX
cjfa-8193	174	3	have	have	VERB
cjfa-8193	174	4	a	a	DET
cjfa-8193	174	5	drawback	drawback	NOUN
cjfa-8193	174	6	in	in	ADP
cjfa-8193	174	7	that	that	SCONJ
cjfa-8193	174	8	they	they	PRON
cjfa-8193	174	9	are	be	AUX
cjfa-8193	174	10	symmetric	symmetric	ADJ
cjfa-8193	174	11	.	.	PUNCT
cjfa-8193	175	1	our	our	PRON
cjfa-8193	175	2	preferred	preferred	ADJ
cjfa-8193	175	3	option	option	NOUN
cjfa-8193	175	4	is	be	AUX
cjfa-8193	175	5	therefore	therefore	ADV
cjfa-8193	175	6	the	the	DET
cjfa-8193	175	7	skewed	skewed	ADJ
cjfa-8193	175	8	-	-	PUNCT
cjfa-8193	175	9	student	student	NOUN
cjfa-8193	175	10	density	density	NOUN
cjfa-8193	175	11	proposed	propose	VERB
cjfa-8193	175	12	by	by	ADP
cjfa-8193	175	13	fernández	fernández	PROPN
cjfa-8193	175	14	and	and	CCONJ
cjfa-8193	175	15	steel	steel	NOUN
cjfa-8193	175	16	(	(	PUNCT
cjfa-8193	175	17	1998	1998	NUM
cjfa-8193	175	18	)	)	PUNCT
cjfa-8193	175	19	.	.	PUNCT
cjfa-8193	176	1	(	(	PUNCT
cjfa-8193	176	2	iv	iv	X
cjfa-8193	176	3	)	)	PUNCT
cjfa-8193	176	4	gaussian	gaussian	NOUN
cjfa-8193	176	5	(	(	PUNCT
cjfa-8193	176	6	normal	normal	ADJ
cjfa-8193	176	7	)	)	PUNCT
cjfa-8193	176	8	distribution	distribution	NOUN
cjfa-8193	176	9	where	where	SCONJ
cjfa-8193	176	10	the	the	DET
cjfa-8193	176	11	log	log	NOUN
cjfa-8193	176	12	-	-	PUNCT
cjfa-8193	176	13	likelihood	likelihood	NOUN
cjfa-8193	176	14	function	function	NOUN
cjfa-8193	176	15	of	of	ADP
cjfa-8193	176	16	the	the	DET
cjfa-8193	176	17	distribution	distribution	NOUN
cjfa-8193	176	18	is	be	AUX
cjfa-8193	176	19	:	:	PUNCT
cjfa-8193	176	20	(	(	PUNCT
cjfa-8193	176	21	v	v	NOUN
cjfa-8193	176	22	)	)	PUNCT
cjfa-8193	176	23	student	student	NOUN
cjfa-8193	176	24	-	-	PUNCT
cjfa-8193	176	25	t	t	NOUN
cjfa-8193	176	26	distribution	distribution	NOUN
cjfa-8193	176	27	where	where	SCONJ
cjfa-8193	176	28	the	the	DET
cjfa-8193	176	29	log	log	NOUN
cjfa-8193	176	30	-	-	PUNCT
cjfa-8193	176	31	likelihood	likelihood	NOUN
cjfa-8193	176	32	function	function	NOUN
cjfa-8193	176	33	of	of	ADP
cjfa-8193	176	34	the	the	DET
cjfa-8193	176	35	distribution	distribution	NOUN
cjfa-8193	176	36	is	be	AUX
cjfa-8193	176	37	:	:	PUNCT
cjfa-8193	176	38	(	(	PUNCT
cjfa-8193	176	39	vi	vi	NOUN
cjfa-8193	176	40	)	)	PUNCT
cjfa-8193	176	41	generalized	generalize	VERB
cjfa-8193	176	42	error	error	NOUN
cjfa-8193	176	43	distribution	distribution	NOUN
cjfa-8193	176	44	(	(	PUNCT
cjfa-8193	176	45	ged	ge	VERB
cjfa-8193	176	46	)	)	PUNCT
cjfa-8193	176	47	where	where	SCONJ
cjfa-8193	176	48	the	the	DET
cjfa-8193	176	49	log	log	NOUN
cjfa-8193	176	50	-	-	PUNCT
cjfa-8193	176	51	likelihood	likelihood	NOUN
cjfa-8193	176	52	function	function	NOUN
cjfa-8193	176	53	of	of	ADP
cjfa-8193	176	54	the	the	DET
cjfa-8193	176	55	distribution	distribution	NOUN
cjfa-8193	176	56	is	be	AUX
cjfa-8193	176	57	:	:	PUNCT
cjfa-8193	176	58	(	(	PUNCT
cjfa-8193	176	59	vii	vii	PROPN
cjfa-8193	176	60	)	)	PUNCT
cjfa-8193	176	61	standardized	standardized	ADJ
cjfa-8193	176	62	(	(	PUNCT
cjfa-8193	176	63	zero	zero	NUM
cjfa-8193	176	64	mean	mean	NOUN
cjfa-8193	176	65	and	and	CCONJ
cjfa-8193	176	66	unit	unit	NOUN
cjfa-8193	176	67	variance	variance	NOUN
cjfa-8193	176	68	)	)	PUNCT
cjfa-8193	176	69	skewed	skewed	ADJ
cjfa-8193	176	70	-	-	PUNCT
cjfa-8193	176	71	student	student	NOUN
cjfa-8193	176	72	distribution	distribution	NOUN
cjfa-8193	176	73	]	]	PUNCT
cjfa-8193	176	74	4	4	NUM
cjfa-8193	176	75	[	[	NOUN
cjfa-8193	176	76	)	)	PUNCT
cjfa-8193	176	77	(	(	PUNCT
cjfa-8193	176	78	2	2	NUM
cjfa-8193	176	79	1	1	NUM
cjfa-8193	176	80	2	2	NUM
cjfa-8193	176	81	1	1	NUM
cjfa-8193	176	82	22	22	NUM
cjfa-8193	176	83	jt	jt	PROPN
cjfa-8193	176	84	p	p	PROPN
cjfa-8193	176	85	j	j	PROPN
cjfa-8193	176	86	jititi	jititi	PROPN
cjfa-8193	176	87	q	q	PROPN
cjfa-8193	177	1	i	i	PRON
cjfa-8193	177	2	itit	itit	VERB
cjfa-8193	177	3	s	s	PART
cjfa-8193	177	4			PROPN
cjfa-8193	177	5			PROPN
cjfa-8193	177	6			PROPN
cjfa-8193	177	7			PROPN
cjfa-8193	177	8			PROPN
cjfa-8193	177	9			PROPN
cjfa-8193	177	10			PROPN
cjfa-8193	177	11			PRON
cjfa-8193	177	12			VERB
cjfa-8193	177	13			PROPN
cjfa-8193	177	14	]	]	SYM
cjfa-8193	177	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	177	16	(	(	PUNCT
cjfa-8193	177	17	2	2	NUM
cjfa-8193	177	18	1	1	NUM
cjfa-8193	177	19	2	2	NUM
cjfa-8193	177	20	1	1	NUM
cjfa-8193	177	21	2	2	NUM
cjfa-8193	177	22	t	t	NOUN
cjfa-8193	177	23	t	t	NOUN
cjfa-8193	177	24	t	t	NOUN
cjfa-8193	177	25	tnorm	tnorm	NOUN
cjfa-8193	178	1	zl	zl	PROPN
cjfa-8193	179	1			PROPN
cjfa-8193	179	2			NUM
cjfa-8193	179	3			NUM
cjfa-8193	179	4			VERB
cjfa-8193	179	5			PROPN
cjfa-8193	179	6			PROPN
cjfa-8193	179	7	]	]	SYM
cjfa-8193	179	8	6	6	NUM
cjfa-8193	179	9	[	[	SYM
cjfa-8193	179	10	2	2	NUM
cjfa-8193	179	11	1log)1()log	1log)1()log	NUM
cjfa-8193	179	12	(	(	PUNCT
cjfa-8193	179	13	2	2	NUM
cjfa-8193	179	14	1	1	NUM
cjfa-8193	179	15	)	)	PUNCT
cjfa-8193	179	16	2(log	2(log	NOUN
cjfa-8193	179	17	2	2	NUM
cjfa-8193	179	18	1	1	NUM
cjfa-8193	179	19	2	2	NUM
cjfa-8193	179	20	log	log	NOUN
cjfa-8193	179	21	2	2	NUM
cjfa-8193	179	22	1log	1log	NUM
cjfa-8193	179	23	1	1	NUM
cjfa-8193	179	24	2	2	NUM
cjfa-8193	179	25	2	2	NUM
cjfa-8193	179	26			ADJ
cjfa-8193	179	27			PROPN
cjfa-8193	179	28			PROPN
cjfa-8193	179	29			PRON
cjfa-8193	179	30			NOUN
cjfa-8193	179	31			VERB
cjfa-8193	179	32			PROPN
cjfa-8193	179	33			NOUN
cjfa-8193	179	34			NOUN
cjfa-8193	179	35			PROPN
cjfa-8193	179	36			PROPN
cjfa-8193	179	37			PROPN
cjfa-8193	179	38			NOUN
cjfa-8193	179	39			PROPN
cjfa-8193	179	40			PROPN
cjfa-8193	179	41			PROPN
cjfa-8193	179	42			PROPN
cjfa-8193	180	1			PROPN
cjfa-8193	180	2			INTJ
cjfa-8193	180	3			NUM
cjfa-8193	180	4			ADV
cjfa-8193	180	5			VERB
cjfa-8193	180	6			NOUN
cjfa-8193	180	7			PRON
cjfa-8193	180	8			PROPN
cjfa-8193	180	9			PROPN
cjfa-8193	180	10			NOUN
cjfa-8193	180	11			NUM
cjfa-8193	180	12			PRON
cjfa-8193	180	13			PROPN
cjfa-8193	180	14			PROPN
cjfa-8193	180	15			NOUN
cjfa-8193	180	16			PUNCT
cjfa-8193	181	1	t	t	PROPN
cjfa-8193	181	2	t	t	PROPN
cjfa-8193	181	3	t	t	PROPN
cjfa-8193	181	4	t	t	PROPN
cjfa-8193	181	5	stud	stud	NOUN
cjfa-8193	181	6	v	v	ADP
cjfa-8193	181	7	z	z	PROPN
cjfa-8193	181	8	tl	tl	PROPN
cjfa-8193	181	9			PROPN
cjfa-8193	181	10			NOUN
cjfa-8193	181	11	]	]	PUNCT
cjfa-8193	181	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	181	13	1	1	NUM
cjfa-8193	181	14	21	21	NUM
cjfa-8193	181	15			PROPN
cjfa-8193	181	16			NOUN
cjfa-8193	181	17			NOUN
cjfa-8193	181	18			PROPN
cjfa-8193	181	19			PROPN
cjfa-8193	181	20			X
cjfa-8193	181	21			NOUN
cjfa-8193	181	22			NOUN
cjfa-8193	181	23			NOUN
cjfa-8193	182	1			PROPN
cjfa-8193	182	2			NOUN
cjfa-8193	182	3			NOUN
cjfa-8193	182	4			PRON
cjfa-8193	182	5			PROPN
cjfa-8193	183	1			PROPN
cjfa-8193	183	2			NOUN
cjfa-8193	183	3			NOUN
cjfa-8193	183	4			PROPN
cjfa-8193	183	5			PROPN
cjfa-8193	183	6			PROPN
cjfa-8193	183	7			NOUN
cjfa-8193	184	1			PROPN
cjfa-8193	184	2	t	t	PROPN
cjfa-8193	184	3	t	t	PROPN
cjfa-8193	184	4	t	t	PROPN
cjfa-8193	184	5	t	t	PROPN
cjfa-8193	184	6	ged	ge	VERB
cjfa-8193	184	7	zl	zl	PROPN
cjfa-8193	184	8			PROPN
cjfa-8193	184	9			ADJ
cjfa-8193	184	10			NOUN
cjfa-8193	184	11			NOUN
cjfa-8193	184	12			ADJ
cjfa-8193	184	13			NOUN
cjfa-8193	184	14			NOUN
cjfa-8193	184	15	is	be	AUX
cjfa-8193	184	16	a	a	DET
cjfa-8193	184	17	dummy	dummy	ADJ
cjfa-8193	184	18	variable	variable	NOUN
cjfa-8193	184	19	that	that	PRON
cjfa-8193	184	20	take	take	VERB
cjfa-8193	184	21	the	the	DET
cjfa-8193	184	22	value	value	NOUN
cjfa-8193	184	23	1	1	NUM
cjfa-8193	184	24	when	when	SCONJ
cjfa-8193	184	25	this	this	DET
cjfa-8193	184	26	variation	variation	NOUN
cjfa-8193	184	27	on	on	ADP
cjfa-8193	184	28	the	the	DET
cjfa-8193	184	29	garch	garch	NOUN
cjfa-8193	184	30	model	model	NOUN
cjfa-8193	184	31	was	be	AUX
cjfa-8193	184	32	proposed	propose	VERB
cjfa-8193	184	33	by	by	ADP
cjfa-8193	184	34	glosten	glosten	ADJ
cjfa-8193	184	35	,	,	PUNCT
cjfa-8193	184	36	jagannathan	jagannathan	NOUN
cjfa-8193	184	37	,	,	PUNCT
cjfa-8193	184	38	and	and	CCONJ
cjfa-8193	184	39	runkle	runkle	ADJ
cjfa-8193	184	40	(	(	PUNCT
cjfa-8193	184	41	1993	1993	NUM
cjfa-8193	184	42	)	)	PUNCT
cjfa-8193	184	43	as	as	ADP
cjfa-8193	184	44	an	an	DET
cjfa-8193	184	45	alternative	alternative	ADJ
cjfa-8193	184	46	way	way	NOUN
cjfa-8193	184	47	of	of	ADP
cjfa-8193	184	48	dealing	deal	VERB
cjfa-8193	184	49	with	with	ADP
cjfa-8193	184	50	asymmetric	asymmetric	ADJ
cjfa-8193	184	51	shocks	shock	NOUN
cjfa-8193	184	52	in	in	ADP
cjfa-8193	184	53	financial	financial	ADJ
cjfa-8193	184	54	series	series	NOUN
cjfa-8193	184	55	.	.	PUNCT
cjfa-8193	185	1	its	its	PRON
cjfa-8193	185	2	generalized	generalized	ADJ
cjfa-8193	185	3	version	version	NOUN
cjfa-8193	185	4	is	be	AUX
cjfa-8193	185	5	:	:	PUNCT
cjfa-8193	185	6	where	where	SCONJ
cjfa-8193	185	7	�	�	PROPN
cjfa-8193	185	8	�	�	PROPN
cjfa-8193	185	9	�	�	PROPN
cjfa-8193	185	10	is	be	AUX
cjfa-8193	185	11	a	a	DET
cjfa-8193	185	12	dummy	dummy	ADJ
cjfa-8193	185	13	variable	variable	NOUN
cjfa-8193	185	14	that	that	PRON
cjfa-8193	185	15	take	take	VERB
cjfa-8193	185	16	the	the	DET
cjfa-8193	185	17	value	value	NOUN
cjfa-8193	185	18	1	1	NUM
cjfa-8193	185	19	when	when	SCONJ
cjfa-8193	185	20	�	�	PROPN
cjfa-8193	185	21	�	�	PROPN
cjfa-8193	185	22	�	�	PROPN
cjfa-8193	185	23	�	�	PROPN
cjfa-8193	185	24	<	<	X
cjfa-8193	185	25	0	0	NUM
cjfa-8193	185	26	,	,	PUNCT
cjfa-8193	185	27	and	and	CCONJ
cjfa-8193	185	28	0	0	NUM
cjfa-8193	185	29	when	when	SCONJ
cjfa-8193	185	30	�	�	PROPN
cjfa-8193	185	31	�	�	PROPN
cjfa-8193	185	32	�	�	PROPN
cjfa-8193	185	33	�	�	PROPN
cjfa-8193	185	34	≥	≥	NUM
cjfa-8193	185	35	0	0	NUM
cjfa-8193	185	36	.	.	PUNCT
cjfa-8193	186	1	a	a	DET
cjfa-8193	186	2	feature	feature	NOUN
cjfa-8193	186	3	of	of	ADP
cjfa-8193	186	4	the	the	DET
cjfa-8193	186	5	gjr	gjr	NOUN
cjfa-8193	186	6	model	model	NOUN
cjfa-8193	186	7	is	be	AUX
cjfa-8193	186	8	that	that	SCONJ
cjfa-8193	186	9	the	the	DET
cjfa-8193	186	10	null	null	ADJ
cjfa-8193	186	11	hypothesis	hypothesis	NOUN
cjfa-8193	186	12	of	of	ADP
cjfa-8193	186	13	no	no	DET
cjfa-8193	186	14	leverage	leverage	NOUN
cjfa-8193	186	15	(	(	PUNCT
cjfa-8193	186	16	asymmetry	asymmetry	NOUN
cjfa-8193	186	17	)	)	PUNCT
cjfa-8193	186	18	effect	effect	NOUN
cjfa-8193	186	19	is	be	AUX
cjfa-8193	186	20	simple	simple	ADJ
cjfa-8193	186	21	to	to	PART
cjfa-8193	186	22	test	test	VERB
cjfa-8193	186	23	.	.	PUNCT
cjfa-8193	187	1	indeed	indeed	ADV
cjfa-8193	187	2	,	,	PUNCT
cjfa-8193	187	3	γ1	γ1	PROPN
cjfa-8193	187	4	=	=	SYM
cjfa-8193	187	5	…	…	PUNCT
cjfa-8193	187	6	=	=	SYM
cjfa-8193	187	7	γq	γq	ADP
cjfa-8193	187	8	=	=	SYM
cjfa-8193	187	9	0	0	NUM
cjfa-8193	187	10	implies	imply	VERB
cjfa-8193	187	11	that	that	SCONJ
cjfa-8193	187	12	the	the	DET
cjfa-8193	187	13	impact	impact	NOUN
cjfa-8193	187	14	of	of	ADP
cjfa-8193	187	15	a	a	DET
cjfa-8193	187	16	shock	shock	NOUN
cjfa-8193	187	17	is	be	AUX
cjfa-8193	187	18	symmetric	symmetric	ADJ
cjfa-8193	187	19	,	,	PUNCT
cjfa-8193	187	20	i.e.	i.e.	X
cjfa-8193	187	21	,	,	PUNCT
cjfa-8193	187	22	past	past	ADP
cjfa-8193	187	23	positive	positive	ADJ
cjfa-8193	187	24	shocks	shock	NOUN
cjfa-8193	187	25	have	have	VERB
cjfa-8193	187	26	the	the	DET
cjfa-8193	187	27	same	same	ADJ
cjfa-8193	187	28	impact	impact	NOUN
cjfa-8193	187	29	on	on	ADP
cjfa-8193	187	30	today	today	NOUN
cjfa-8193	187	31	’s	’s	PART
cjfa-8193	187	32	volatility	volatility	NOUN
cjfa-8193	187	33	as	as	ADP
cjfa-8193	187	34	past	past	ADP
cjfa-8193	187	35	negative	negative	ADJ
cjfa-8193	187	36	shocks	shock	NOUN
cjfa-8193	187	37	.	.	PUNCT
cjfa-8193	188	1	they	they	PRON
cjfa-8193	188	2	do	do	AUX
cjfa-8193	188	3	have	have	VERB
cjfa-8193	188	4	a	a	DET
cjfa-8193	188	5	drawback	drawback	NOUN
cjfa-8193	188	6	in	in	ADP
cjfa-8193	188	7	that	that	SCONJ
cjfa-8193	188	8	they	they	PRON
cjfa-8193	188	9	are	be	AUX
cjfa-8193	188	10	symmetric	symmetric	ADJ
cjfa-8193	188	11	.	.	PUNCT
cjfa-8193	189	1	our	our	PRON
cjfa-8193	189	2	preferred	preferred	ADJ
cjfa-8193	189	3	option	option	NOUN
cjfa-8193	189	4	is	be	AUX
cjfa-8193	189	5	therefore	therefore	ADV
cjfa-8193	189	6	the	the	DET
cjfa-8193	189	7	skewed	skewed	ADJ
cjfa-8193	189	8	-	-	PUNCT
cjfa-8193	189	9	student	student	NOUN
cjfa-8193	189	10	density	density	NOUN
cjfa-8193	189	11	proposed	propose	VERB
cjfa-8193	189	12	by	by	ADP
cjfa-8193	189	13	fernández	fernández	PROPN
cjfa-8193	189	14	and	and	CCONJ
cjfa-8193	189	15	steel	steel	NOUN
cjfa-8193	189	16	(	(	PUNCT
cjfa-8193	189	17	1998	1998	NUM
cjfa-8193	189	18	)	)	PUNCT
cjfa-8193	189	19	.	.	PUNCT
cjfa-8193	190	1	(	(	PUNCT
cjfa-8193	190	2	iv	iv	X
cjfa-8193	190	3	)	)	PUNCT
cjfa-8193	190	4	gaussian	gaussian	NOUN
cjfa-8193	190	5	(	(	PUNCT
cjfa-8193	190	6	normal	normal	ADJ
cjfa-8193	190	7	)	)	PUNCT
cjfa-8193	190	8	distribution	distribution	NOUN
cjfa-8193	190	9	where	where	SCONJ
cjfa-8193	190	10	the	the	DET
cjfa-8193	190	11	log	log	NOUN
cjfa-8193	190	12	-	-	PUNCT
cjfa-8193	190	13	likelihood	likelihood	NOUN
cjfa-8193	190	14	function	function	NOUN
cjfa-8193	190	15	of	of	ADP
cjfa-8193	190	16	the	the	DET
cjfa-8193	190	17	distribution	distribution	NOUN
cjfa-8193	190	18	is	be	AUX
cjfa-8193	190	19	:	:	PUNCT
cjfa-8193	190	20	(	(	PUNCT
cjfa-8193	190	21	v	v	NOUN
cjfa-8193	190	22	)	)	PUNCT
cjfa-8193	190	23	student	student	NOUN
cjfa-8193	190	24	-	-	PUNCT
cjfa-8193	190	25	t	t	NOUN
cjfa-8193	190	26	distribution	distribution	NOUN
cjfa-8193	190	27	where	where	SCONJ
cjfa-8193	190	28	the	the	DET
cjfa-8193	190	29	log	log	NOUN
cjfa-8193	190	30	-	-	PUNCT
cjfa-8193	190	31	likelihood	likelihood	NOUN
cjfa-8193	190	32	function	function	NOUN
cjfa-8193	190	33	of	of	ADP
cjfa-8193	190	34	the	the	DET
cjfa-8193	190	35	distribution	distribution	NOUN
cjfa-8193	190	36	is	be	AUX
cjfa-8193	190	37	:	:	PUNCT
cjfa-8193	190	38	(	(	PUNCT
cjfa-8193	190	39	vi	vi	NOUN
cjfa-8193	190	40	)	)	PUNCT
cjfa-8193	190	41	generalized	generalize	VERB
cjfa-8193	190	42	error	error	NOUN
cjfa-8193	190	43	distribution	distribution	NOUN
cjfa-8193	190	44	(	(	PUNCT
cjfa-8193	190	45	ged	ge	VERB
cjfa-8193	190	46	)	)	PUNCT
cjfa-8193	190	47	where	where	SCONJ
cjfa-8193	190	48	the	the	DET
cjfa-8193	190	49	log	log	NOUN
cjfa-8193	190	50	-	-	PUNCT
cjfa-8193	190	51	likelihood	likelihood	NOUN
cjfa-8193	190	52	function	function	NOUN
cjfa-8193	190	53	of	of	ADP
cjfa-8193	190	54	the	the	DET
cjfa-8193	190	55	distribution	distribution	NOUN
cjfa-8193	190	56	is	be	AUX
cjfa-8193	190	57	:	:	PUNCT
cjfa-8193	190	58	(	(	PUNCT
cjfa-8193	190	59	vii	vii	PROPN
cjfa-8193	190	60	)	)	PUNCT
cjfa-8193	190	61	standardized	standardized	ADJ
cjfa-8193	190	62	(	(	PUNCT
cjfa-8193	190	63	zero	zero	NUM
cjfa-8193	190	64	mean	mean	NOUN
cjfa-8193	190	65	and	and	CCONJ
cjfa-8193	190	66	unit	unit	NOUN
cjfa-8193	190	67	variance	variance	NOUN
cjfa-8193	190	68	)	)	PUNCT
cjfa-8193	190	69	skewed	skewed	ADJ
cjfa-8193	190	70	-	-	PUNCT
cjfa-8193	190	71	student	student	NOUN
cjfa-8193	190	72	distribution	distribution	NOUN
cjfa-8193	190	73	]	]	PUNCT
cjfa-8193	190	74	4	4	NUM
cjfa-8193	190	75	[	[	NOUN
cjfa-8193	190	76	)	)	PUNCT
cjfa-8193	190	77	(	(	PUNCT
cjfa-8193	190	78	2	2	NUM
cjfa-8193	190	79	1	1	NUM
cjfa-8193	190	80	2	2	NUM
cjfa-8193	190	81	1	1	NUM
cjfa-8193	190	82	22	22	NUM
cjfa-8193	190	83	jt	jt	PROPN
cjfa-8193	190	84	p	p	PROPN
cjfa-8193	190	85	j	j	PROPN
cjfa-8193	190	86	jititi	jititi	PROPN
cjfa-8193	190	87	q	q	PROPN
cjfa-8193	191	1	i	i	PRON
cjfa-8193	191	2	itit	itit	VERB
cjfa-8193	191	3	s	s	PART
cjfa-8193	191	4			PROPN
cjfa-8193	191	5			PROPN
cjfa-8193	191	6			PROPN
cjfa-8193	191	7			PROPN
cjfa-8193	191	8			PROPN
cjfa-8193	191	9			PROPN
cjfa-8193	191	10			PROPN
cjfa-8193	191	11			PRON
cjfa-8193	191	12			VERB
cjfa-8193	191	13			PROPN
cjfa-8193	191	14	]	]	SYM
cjfa-8193	191	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	191	16	(	(	PUNCT
cjfa-8193	191	17	2	2	NUM
cjfa-8193	191	18	1	1	NUM
cjfa-8193	191	19	2	2	NUM
cjfa-8193	191	20	1	1	NUM
cjfa-8193	191	21	2	2	NUM
cjfa-8193	191	22	t	t	NOUN
cjfa-8193	191	23	t	t	NOUN
cjfa-8193	191	24	t	t	NOUN
cjfa-8193	191	25	tnorm	tnorm	NOUN
cjfa-8193	192	1	zl	zl	PROPN
cjfa-8193	193	1			PROPN
cjfa-8193	193	2			NUM
cjfa-8193	193	3			NUM
cjfa-8193	193	4			VERB
cjfa-8193	193	5			PROPN
cjfa-8193	193	6			PROPN
cjfa-8193	193	7	]	]	SYM
cjfa-8193	193	8	6	6	NUM
cjfa-8193	193	9	[	[	SYM
cjfa-8193	193	10	2	2	NUM
cjfa-8193	193	11	1log)1()log	1log)1()log	NUM
cjfa-8193	193	12	(	(	PUNCT
cjfa-8193	193	13	2	2	NUM
cjfa-8193	193	14	1	1	NUM
cjfa-8193	193	15	)	)	PUNCT
cjfa-8193	193	16	2(log	2(log	NOUN
cjfa-8193	193	17	2	2	NUM
cjfa-8193	193	18	1	1	NUM
cjfa-8193	193	19	2	2	NUM
cjfa-8193	193	20	log	log	NOUN
cjfa-8193	193	21	2	2	NUM
cjfa-8193	193	22	1log	1log	NUM
cjfa-8193	193	23	1	1	NUM
cjfa-8193	193	24	2	2	NUM
cjfa-8193	193	25	2	2	NUM
cjfa-8193	193	26			ADJ
cjfa-8193	193	27			PROPN
cjfa-8193	193	28			PROPN
cjfa-8193	193	29			PRON
cjfa-8193	193	30			NOUN
cjfa-8193	193	31			VERB
cjfa-8193	193	32			PROPN
cjfa-8193	193	33			NOUN
cjfa-8193	193	34			NOUN
cjfa-8193	193	35			PROPN
cjfa-8193	193	36			PROPN
cjfa-8193	193	37			PROPN
cjfa-8193	193	38			NOUN
cjfa-8193	193	39			PROPN
cjfa-8193	193	40			PROPN
cjfa-8193	193	41			PROPN
cjfa-8193	193	42			PROPN
cjfa-8193	194	1			PROPN
cjfa-8193	194	2			INTJ
cjfa-8193	194	3			NUM
cjfa-8193	194	4			ADV
cjfa-8193	194	5			VERB
cjfa-8193	194	6			NOUN
cjfa-8193	194	7			PRON
cjfa-8193	194	8			PROPN
cjfa-8193	194	9			PROPN
cjfa-8193	194	10			NOUN
cjfa-8193	194	11			NUM
cjfa-8193	194	12			PRON
cjfa-8193	194	13			PROPN
cjfa-8193	194	14			PROPN
cjfa-8193	194	15			NOUN
cjfa-8193	194	16			PUNCT
cjfa-8193	195	1	t	t	PROPN
cjfa-8193	195	2	t	t	PROPN
cjfa-8193	195	3	t	t	PROPN
cjfa-8193	195	4	t	t	PROPN
cjfa-8193	195	5	stud	stud	NOUN
cjfa-8193	195	6	v	v	ADP
cjfa-8193	195	7	z	z	PROPN
cjfa-8193	195	8	tl	tl	PROPN
cjfa-8193	195	9			PROPN
cjfa-8193	195	10			NOUN
cjfa-8193	195	11	]	]	PUNCT
cjfa-8193	195	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	195	13	1	1	NUM
cjfa-8193	195	14	21	21	NUM
cjfa-8193	195	15			PROPN
cjfa-8193	195	16			NOUN
cjfa-8193	195	17			NOUN
cjfa-8193	195	18			PROPN
cjfa-8193	195	19			PROPN
cjfa-8193	195	20			X
cjfa-8193	195	21			NOUN
cjfa-8193	195	22			NOUN
cjfa-8193	195	23			NOUN
cjfa-8193	196	1			PROPN
cjfa-8193	196	2			NOUN
cjfa-8193	196	3			NOUN
cjfa-8193	196	4			PRON
cjfa-8193	196	5			PROPN
cjfa-8193	197	1			PROPN
cjfa-8193	197	2			NOUN
cjfa-8193	197	3			NOUN
cjfa-8193	197	4			PROPN
cjfa-8193	197	5			PROPN
cjfa-8193	197	6			PROPN
cjfa-8193	197	7			NOUN
cjfa-8193	198	1			PROPN
cjfa-8193	198	2	t	t	PROPN
cjfa-8193	198	3	t	t	PROPN
cjfa-8193	198	4	t	t	PROPN
cjfa-8193	198	5	t	t	PROPN
cjfa-8193	198	6	ged	ge	VERB
cjfa-8193	198	7	zl	zl	PROPN
cjfa-8193	198	8			PROPN
cjfa-8193	198	9			ADJ
cjfa-8193	198	10			NOUN
cjfa-8193	198	11			NOUN
cjfa-8193	198	12			ADJ
cjfa-8193	198	13			ADJ
cjfa-8193	198	14			NOUN
cjfa-8193	198	15	,	,	PUNCT
cjfa-8193	198	16	and	and	CCONJ
cjfa-8193	198	17	0	0	NUM
cjfa-8193	198	18	when	when	SCONJ
cjfa-8193	198	19	this	this	DET
cjfa-8193	198	20	variation	variation	NOUN
cjfa-8193	198	21	on	on	ADP
cjfa-8193	198	22	the	the	DET
cjfa-8193	198	23	garch	garch	NOUN
cjfa-8193	198	24	model	model	NOUN
cjfa-8193	198	25	was	be	AUX
cjfa-8193	198	26	proposed	propose	VERB
cjfa-8193	198	27	by	by	ADP
cjfa-8193	198	28	glosten	glosten	ADJ
cjfa-8193	198	29	,	,	PUNCT
cjfa-8193	198	30	jagannathan	jagannathan	NOUN
cjfa-8193	198	31	,	,	PUNCT
cjfa-8193	198	32	and	and	CCONJ
cjfa-8193	198	33	runkle	runkle	ADJ
cjfa-8193	198	34	(	(	PUNCT
cjfa-8193	198	35	1993	1993	NUM
cjfa-8193	198	36	)	)	PUNCT
cjfa-8193	198	37	as	as	ADP
cjfa-8193	198	38	an	an	DET
cjfa-8193	198	39	alternative	alternative	ADJ
cjfa-8193	198	40	way	way	NOUN
cjfa-8193	198	41	of	of	ADP
cjfa-8193	198	42	dealing	deal	VERB
cjfa-8193	198	43	with	with	ADP
cjfa-8193	198	44	asymmetric	asymmetric	ADJ
cjfa-8193	198	45	shocks	shock	NOUN
cjfa-8193	198	46	in	in	ADP
cjfa-8193	198	47	financial	financial	ADJ
cjfa-8193	198	48	series	series	NOUN
cjfa-8193	198	49	.	.	PUNCT
cjfa-8193	199	1	its	its	PRON
cjfa-8193	199	2	generalized	generalized	ADJ
cjfa-8193	199	3	version	version	NOUN
cjfa-8193	199	4	is	be	AUX
cjfa-8193	199	5	:	:	PUNCT
cjfa-8193	199	6	where	where	SCONJ
cjfa-8193	199	7	�	�	PROPN
cjfa-8193	199	8	�	�	PROPN
cjfa-8193	199	9	�	�	PROPN
cjfa-8193	199	10	is	be	AUX
cjfa-8193	199	11	a	a	DET
cjfa-8193	199	12	dummy	dummy	ADJ
cjfa-8193	199	13	variable	variable	NOUN
cjfa-8193	199	14	that	that	PRON
cjfa-8193	199	15	take	take	VERB
cjfa-8193	199	16	the	the	DET
cjfa-8193	199	17	value	value	NOUN
cjfa-8193	199	18	1	1	NUM
cjfa-8193	199	19	when	when	SCONJ
cjfa-8193	199	20	�	�	PROPN
cjfa-8193	199	21	�	�	PROPN
cjfa-8193	199	22	�	�	PROPN
cjfa-8193	199	23	�	�	PROPN
cjfa-8193	199	24	<	<	X
cjfa-8193	199	25	0	0	NUM
cjfa-8193	199	26	,	,	PUNCT
cjfa-8193	199	27	and	and	CCONJ
cjfa-8193	199	28	0	0	NUM
cjfa-8193	199	29	when	when	SCONJ
cjfa-8193	199	30	�	�	PROPN
cjfa-8193	199	31	�	�	PROPN
cjfa-8193	199	32	�	�	PROPN
cjfa-8193	199	33	�	�	PROPN
cjfa-8193	199	34	≥	≥	NUM
cjfa-8193	199	35	0	0	NUM
cjfa-8193	199	36	.	.	PUNCT
cjfa-8193	200	1	a	a	DET
cjfa-8193	200	2	feature	feature	NOUN
cjfa-8193	200	3	of	of	ADP
cjfa-8193	200	4	the	the	DET
cjfa-8193	200	5	gjr	gjr	NOUN
cjfa-8193	200	6	model	model	NOUN
cjfa-8193	200	7	is	be	AUX
cjfa-8193	200	8	that	that	SCONJ
cjfa-8193	200	9	the	the	DET
cjfa-8193	200	10	null	null	ADJ
cjfa-8193	200	11	hypothesis	hypothesis	NOUN
cjfa-8193	200	12	of	of	ADP
cjfa-8193	200	13	no	no	DET
cjfa-8193	200	14	leverage	leverage	NOUN
cjfa-8193	200	15	(	(	PUNCT
cjfa-8193	200	16	asymmetry	asymmetry	NOUN
cjfa-8193	200	17	)	)	PUNCT
cjfa-8193	200	18	effect	effect	NOUN
cjfa-8193	200	19	is	be	AUX
cjfa-8193	200	20	simple	simple	ADJ
cjfa-8193	200	21	to	to	PART
cjfa-8193	200	22	test	test	VERB
cjfa-8193	200	23	.	.	PUNCT
cjfa-8193	201	1	indeed	indeed	ADV
cjfa-8193	201	2	,	,	PUNCT
cjfa-8193	201	3	γ1	γ1	PROPN
cjfa-8193	201	4	=	=	SYM
cjfa-8193	201	5	…	…	PUNCT
cjfa-8193	201	6	=	=	SYM
cjfa-8193	201	7	γq	γq	ADP
cjfa-8193	201	8	=	=	SYM
cjfa-8193	201	9	0	0	NUM
cjfa-8193	201	10	implies	imply	VERB
cjfa-8193	201	11	that	that	SCONJ
cjfa-8193	201	12	the	the	DET
cjfa-8193	201	13	impact	impact	NOUN
cjfa-8193	201	14	of	of	ADP
cjfa-8193	201	15	a	a	DET
cjfa-8193	201	16	shock	shock	NOUN
cjfa-8193	201	17	is	be	AUX
cjfa-8193	201	18	symmetric	symmetric	ADJ
cjfa-8193	201	19	,	,	PUNCT
cjfa-8193	201	20	i.e.	i.e.	X
cjfa-8193	201	21	,	,	PUNCT
cjfa-8193	201	22	past	past	ADP
cjfa-8193	201	23	positive	positive	ADJ
cjfa-8193	201	24	shocks	shock	NOUN
cjfa-8193	201	25	have	have	VERB
cjfa-8193	201	26	the	the	DET
cjfa-8193	201	27	same	same	ADJ
cjfa-8193	201	28	impact	impact	NOUN
cjfa-8193	201	29	on	on	ADP
cjfa-8193	201	30	today	today	NOUN
cjfa-8193	201	31	’s	’s	PART
cjfa-8193	201	32	volatility	volatility	NOUN
cjfa-8193	201	33	as	as	ADP
cjfa-8193	201	34	past	past	ADP
cjfa-8193	201	35	negative	negative	ADJ
cjfa-8193	201	36	shocks	shock	NOUN
cjfa-8193	201	37	.	.	PUNCT
cjfa-8193	202	1	they	they	PRON
cjfa-8193	202	2	do	do	AUX
cjfa-8193	202	3	have	have	VERB
cjfa-8193	202	4	a	a	DET
cjfa-8193	202	5	drawback	drawback	NOUN
cjfa-8193	202	6	in	in	ADP
cjfa-8193	202	7	that	that	SCONJ
cjfa-8193	202	8	they	they	PRON
cjfa-8193	202	9	are	be	AUX
cjfa-8193	202	10	symmetric	symmetric	ADJ
cjfa-8193	202	11	.	.	PUNCT
cjfa-8193	203	1	our	our	PRON
cjfa-8193	203	2	preferred	preferred	ADJ
cjfa-8193	203	3	option	option	NOUN
cjfa-8193	203	4	is	be	AUX
cjfa-8193	203	5	therefore	therefore	ADV
cjfa-8193	203	6	the	the	DET
cjfa-8193	203	7	skewed	skewed	ADJ
cjfa-8193	203	8	-	-	PUNCT
cjfa-8193	203	9	student	student	NOUN
cjfa-8193	203	10	density	density	NOUN
cjfa-8193	203	11	proposed	propose	VERB
cjfa-8193	203	12	by	by	ADP
cjfa-8193	203	13	fernández	fernández	PROPN
cjfa-8193	203	14	and	and	CCONJ
cjfa-8193	203	15	steel	steel	NOUN
cjfa-8193	203	16	(	(	PUNCT
cjfa-8193	203	17	1998	1998	NUM
cjfa-8193	203	18	)	)	PUNCT
cjfa-8193	203	19	.	.	PUNCT
cjfa-8193	204	1	(	(	PUNCT
cjfa-8193	204	2	iv	iv	X
cjfa-8193	204	3	)	)	PUNCT
cjfa-8193	204	4	gaussian	gaussian	NOUN
cjfa-8193	204	5	(	(	PUNCT
cjfa-8193	204	6	normal	normal	ADJ
cjfa-8193	204	7	)	)	PUNCT
cjfa-8193	204	8	distribution	distribution	NOUN
cjfa-8193	204	9	where	where	SCONJ
cjfa-8193	204	10	the	the	DET
cjfa-8193	204	11	log	log	NOUN
cjfa-8193	204	12	-	-	PUNCT
cjfa-8193	204	13	likelihood	likelihood	NOUN
cjfa-8193	204	14	function	function	NOUN
cjfa-8193	204	15	of	of	ADP
cjfa-8193	204	16	the	the	DET
cjfa-8193	204	17	distribution	distribution	NOUN
cjfa-8193	204	18	is	be	AUX
cjfa-8193	204	19	:	:	PUNCT
cjfa-8193	204	20	(	(	PUNCT
cjfa-8193	204	21	v	v	NOUN
cjfa-8193	204	22	)	)	PUNCT
cjfa-8193	204	23	student	student	NOUN
cjfa-8193	204	24	-	-	PUNCT
cjfa-8193	204	25	t	t	NOUN
cjfa-8193	204	26	distribution	distribution	NOUN
cjfa-8193	204	27	where	where	SCONJ
cjfa-8193	204	28	the	the	DET
cjfa-8193	204	29	log	log	NOUN
cjfa-8193	204	30	-	-	PUNCT
cjfa-8193	204	31	likelihood	likelihood	NOUN
cjfa-8193	204	32	function	function	NOUN
cjfa-8193	204	33	of	of	ADP
cjfa-8193	204	34	the	the	DET
cjfa-8193	204	35	distribution	distribution	NOUN
cjfa-8193	204	36	is	be	AUX
cjfa-8193	204	37	:	:	PUNCT
cjfa-8193	204	38	(	(	PUNCT
cjfa-8193	204	39	vi	vi	NOUN
cjfa-8193	204	40	)	)	PUNCT
cjfa-8193	204	41	generalized	generalize	VERB
cjfa-8193	204	42	error	error	NOUN
cjfa-8193	204	43	distribution	distribution	NOUN
cjfa-8193	204	44	(	(	PUNCT
cjfa-8193	204	45	ged	ge	VERB
cjfa-8193	204	46	)	)	PUNCT
cjfa-8193	204	47	where	where	SCONJ
cjfa-8193	204	48	the	the	DET
cjfa-8193	204	49	log	log	NOUN
cjfa-8193	204	50	-	-	PUNCT
cjfa-8193	204	51	likelihood	likelihood	NOUN
cjfa-8193	204	52	function	function	NOUN
cjfa-8193	204	53	of	of	ADP
cjfa-8193	204	54	the	the	DET
cjfa-8193	204	55	distribution	distribution	NOUN
cjfa-8193	204	56	is	be	AUX
cjfa-8193	204	57	:	:	PUNCT
cjfa-8193	204	58	(	(	PUNCT
cjfa-8193	204	59	vii	vii	PROPN
cjfa-8193	204	60	)	)	PUNCT
cjfa-8193	204	61	standardized	standardized	ADJ
cjfa-8193	204	62	(	(	PUNCT
cjfa-8193	204	63	zero	zero	NUM
cjfa-8193	204	64	mean	mean	NOUN
cjfa-8193	204	65	and	and	CCONJ
cjfa-8193	204	66	unit	unit	NOUN
cjfa-8193	204	67	variance	variance	NOUN
cjfa-8193	204	68	)	)	PUNCT
cjfa-8193	204	69	skewed	skewed	ADJ
cjfa-8193	204	70	-	-	PUNCT
cjfa-8193	204	71	student	student	NOUN
cjfa-8193	204	72	distribution	distribution	NOUN
cjfa-8193	204	73	]	]	PUNCT
cjfa-8193	204	74	4	4	NUM
cjfa-8193	204	75	[	[	NOUN
cjfa-8193	204	76	)	)	PUNCT
cjfa-8193	204	77	(	(	PUNCT
cjfa-8193	204	78	2	2	NUM
cjfa-8193	204	79	1	1	NUM
cjfa-8193	204	80	2	2	NUM
cjfa-8193	204	81	1	1	NUM
cjfa-8193	204	82	22	22	NUM
cjfa-8193	204	83	jt	jt	PROPN
cjfa-8193	204	84	p	p	PROPN
cjfa-8193	204	85	j	j	PROPN
cjfa-8193	204	86	jititi	jititi	PROPN
cjfa-8193	204	87	q	q	PROPN
cjfa-8193	205	1	i	i	PRON
cjfa-8193	205	2	itit	itit	VERB
cjfa-8193	205	3	s	s	PART
cjfa-8193	205	4			PROPN
cjfa-8193	205	5			PROPN
cjfa-8193	205	6			PROPN
cjfa-8193	205	7			PROPN
cjfa-8193	205	8			PROPN
cjfa-8193	205	9			PROPN
cjfa-8193	205	10			PROPN
cjfa-8193	205	11			PRON
cjfa-8193	205	12			VERB
cjfa-8193	205	13			PROPN
cjfa-8193	205	14	]	]	SYM
cjfa-8193	205	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	205	16	(	(	PUNCT
cjfa-8193	205	17	2	2	NUM
cjfa-8193	205	18	1	1	NUM
cjfa-8193	205	19	2	2	NUM
cjfa-8193	205	20	1	1	NUM
cjfa-8193	205	21	2	2	NUM
cjfa-8193	205	22	t	t	NOUN
cjfa-8193	205	23	t	t	NOUN
cjfa-8193	205	24	t	t	NOUN
cjfa-8193	205	25	tnorm	tnorm	NOUN
cjfa-8193	206	1	zl	zl	PROPN
cjfa-8193	207	1			PROPN
cjfa-8193	207	2			NUM
cjfa-8193	207	3			NUM
cjfa-8193	207	4			VERB
cjfa-8193	207	5			PROPN
cjfa-8193	207	6			PROPN
cjfa-8193	207	7	]	]	SYM
cjfa-8193	207	8	6	6	NUM
cjfa-8193	207	9	[	[	SYM
cjfa-8193	207	10	2	2	NUM
cjfa-8193	207	11	1log)1()log	1log)1()log	NUM
cjfa-8193	207	12	(	(	PUNCT
cjfa-8193	207	13	2	2	NUM
cjfa-8193	207	14	1	1	NUM
cjfa-8193	207	15	)	)	PUNCT
cjfa-8193	207	16	2(log	2(log	NOUN
cjfa-8193	207	17	2	2	NUM
cjfa-8193	207	18	1	1	NUM
cjfa-8193	207	19	2	2	NUM
cjfa-8193	207	20	log	log	NOUN
cjfa-8193	207	21	2	2	NUM
cjfa-8193	207	22	1log	1log	NUM
cjfa-8193	207	23	1	1	NUM
cjfa-8193	207	24	2	2	NUM
cjfa-8193	207	25	2	2	NUM
cjfa-8193	207	26			ADJ
cjfa-8193	207	27			PROPN
cjfa-8193	207	28			PROPN
cjfa-8193	207	29			PRON
cjfa-8193	207	30			NOUN
cjfa-8193	207	31			VERB
cjfa-8193	207	32			PROPN
cjfa-8193	207	33			NOUN
cjfa-8193	207	34			NOUN
cjfa-8193	207	35			PROPN
cjfa-8193	207	36			PROPN
cjfa-8193	207	37			PROPN
cjfa-8193	207	38			NOUN
cjfa-8193	207	39			PROPN
cjfa-8193	207	40			PROPN
cjfa-8193	207	41			PROPN
cjfa-8193	207	42			PROPN
cjfa-8193	208	1			PROPN
cjfa-8193	208	2			INTJ
cjfa-8193	208	3			NUM
cjfa-8193	208	4			ADV
cjfa-8193	208	5			VERB
cjfa-8193	208	6			NOUN
cjfa-8193	208	7			PRON
cjfa-8193	208	8			PROPN
cjfa-8193	208	9			PROPN
cjfa-8193	208	10			NOUN
cjfa-8193	208	11			NUM
cjfa-8193	208	12			PRON
cjfa-8193	208	13			PROPN
cjfa-8193	208	14			PROPN
cjfa-8193	208	15			NOUN
cjfa-8193	208	16			PUNCT
cjfa-8193	209	1	t	t	PROPN
cjfa-8193	209	2	t	t	PROPN
cjfa-8193	209	3	t	t	PROPN
cjfa-8193	209	4	t	t	PROPN
cjfa-8193	209	5	stud	stud	NOUN
cjfa-8193	209	6	v	v	ADP
cjfa-8193	209	7	z	z	PROPN
cjfa-8193	209	8	tl	tl	PROPN
cjfa-8193	209	9			PROPN
cjfa-8193	209	10			NOUN
cjfa-8193	209	11	]	]	PUNCT
cjfa-8193	209	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	209	13	1	1	NUM
cjfa-8193	209	14	21	21	NUM
cjfa-8193	209	15			PROPN
cjfa-8193	209	16			NOUN
cjfa-8193	209	17			NOUN
cjfa-8193	209	18			PROPN
cjfa-8193	209	19			PROPN
cjfa-8193	209	20			X
cjfa-8193	209	21			NOUN
cjfa-8193	209	22			NOUN
cjfa-8193	209	23			NOUN
cjfa-8193	210	1			PROPN
cjfa-8193	210	2			NOUN
cjfa-8193	210	3			NOUN
cjfa-8193	210	4			PRON
cjfa-8193	210	5			PROPN
cjfa-8193	211	1			PROPN
cjfa-8193	211	2			NOUN
cjfa-8193	211	3			NOUN
cjfa-8193	211	4			PROPN
cjfa-8193	211	5			PROPN
cjfa-8193	211	6			PROPN
cjfa-8193	211	7			NOUN
cjfa-8193	212	1			PROPN
cjfa-8193	212	2	t	t	PROPN
cjfa-8193	212	3	t	t	PROPN
cjfa-8193	212	4	t	t	PROPN
cjfa-8193	212	5	t	t	PROPN
cjfa-8193	212	6	ged	ge	VERB
cjfa-8193	212	7	zl	zl	PROPN
cjfa-8193	212	8			PROPN
cjfa-8193	212	9			ADJ
cjfa-8193	212	10			NOUN
cjfa-8193	212	11			NOUN
cjfa-8193	212	12			ADJ
cjfa-8193	212	13			NOUN
cjfa-8193	212	14			VERB
cjfa-8193	212	15	a	a	DET
cjfa-8193	212	16	feature	feature	NOUN
cjfa-8193	212	17	of	of	ADP
cjfa-8193	212	18	the	the	DET
cjfa-8193	212	19	gjr	gjr	NOUN
cjfa-8193	212	20	model	model	NOUN
cjfa-8193	212	21	is	be	AUX
cjfa-8193	212	22	that	that	SCONJ
cjfa-8193	212	23	the	the	DET
cjfa-8193	212	24	null	null	ADJ
cjfa-8193	212	25	hypothesis	hypothesis	NOUN
cjfa-8193	212	26	of	of	ADP
cjfa-8193	212	27	no	no	DET
cjfa-8193	212	28	lever	lever	NOUN
cjfa-8193	212	29	forecasting	forecast	VERB
cjfa-8193	212	30	the	the	DET
cjfa-8193	212	31	jordanian	jordanian	ADJ
cjfa-8193	212	32	stock	stock	NOUN
cjfa-8193	212	33	index	index	PROPN
cjfa-8193	212	34	…	…	SYM
cjfa-8193	212	35	17	17	NUM
cjfa-8193	212	36	age	age	NOUN
cjfa-8193	212	37	(	(	PUNCT
cjfa-8193	212	38	asymmetry	asymmetry	NOUN
cjfa-8193	212	39	)	)	PUNCT
cjfa-8193	212	40	effect	effect	NOUN
cjfa-8193	212	41	is	be	AUX
cjfa-8193	212	42	simple	simple	ADJ
cjfa-8193	212	43	to	to	PART
cjfa-8193	212	44	test	test	VERB
cjfa-8193	212	45	.	.	PUNCT
cjfa-8193	213	1	indeed	indeed	ADV
cjfa-8193	213	2	,	,	PUNCT
cjfa-8193	213	3	γ1	γ1	PROPN
cjfa-8193	213	4	=	=	SYM
cjfa-8193	213	5	…	…	PUNCT
cjfa-8193	213	6	=	=	SYM
cjfa-8193	213	7	γq	γq	ADP
cjfa-8193	213	8	=	=	SYM
cjfa-8193	213	9	0	0	NUM
cjfa-8193	213	10	implies	imply	VERB
cjfa-8193	213	11	that	that	SCONJ
cjfa-8193	213	12	the	the	DET
cjfa-8193	213	13	impact	impact	NOUN
cjfa-8193	213	14	of	of	ADP
cjfa-8193	213	15	a	a	DET
cjfa-8193	213	16	shock	shock	NOUN
cjfa-8193	213	17	is	be	AUX
cjfa-8193	213	18	symmetric	symmetric	ADJ
cjfa-8193	213	19	,	,	PUNCT
cjfa-8193	213	20	i.e.	i.e.	X
cjfa-8193	213	21	,	,	PUNCT
cjfa-8193	213	22	past	past	ADP
cjfa-8193	213	23	positive	positive	ADJ
cjfa-8193	213	24	shocks	shock	NOUN
cjfa-8193	213	25	have	have	VERB
cjfa-8193	213	26	the	the	DET
cjfa-8193	213	27	same	same	ADJ
cjfa-8193	213	28	impact	impact	NOUN
cjfa-8193	213	29	on	on	ADP
cjfa-8193	213	30	today	today	NOUN
cjfa-8193	213	31	’s	’s	PART
cjfa-8193	213	32	volatility	volatility	NOUN
cjfa-8193	213	33	as	as	ADP
cjfa-8193	213	34	past	past	ADP
cjfa-8193	213	35	negative	negative	ADJ
cjfa-8193	213	36	shocks	shock	NOUN
cjfa-8193	213	37	.	.	PUNCT
cjfa-8193	214	1	four	four	NUM
cjfa-8193	214	2	different	different	ADJ
cjfa-8193	214	3	statistical	statistical	ADJ
cjfa-8193	214	4	density	density	NOUN
cjfa-8193	214	5	functions	function	NOUN
cjfa-8193	214	6	are	be	AUX
cjfa-8193	214	7	tested	test	VERB
cjfa-8193	214	8	.	.	PUNCT
cjfa-8193	215	1	the	the	DET
cjfa-8193	215	2	use	use	NOUN
cjfa-8193	215	3	the	the	DET
cjfa-8193	215	4	gaussian	gaussian	NOUN
cjfa-8193	215	5	or	or	CCONJ
cjfa-8193	215	6	normal	normal	ADJ
cjfa-8193	215	7	distribution	distribution	NOUN
cjfa-8193	215	8	is	be	AUX
cjfa-8193	215	9	potentially	potentially	ADV
cjfa-8193	215	10	appropriate	appropriate	ADJ
cjfa-8193	215	11	as	as	SCONJ
cjfa-8193	215	12	the	the	DET
cjfa-8193	215	13	conditional	conditional	ADJ
cjfa-8193	215	14	distribution	distribution	NOUN
cjfa-8193	215	15	of	of	ADP
cjfa-8193	215	16	the	the	DET
cjfa-8193	215	17	residuals	residual	NOUN
cjfa-8193	215	18	would	would	AUX
cjfa-8193	215	19	account	account	VERB
cjfa-8193	215	20	for	for	ADP
cjfa-8193	215	21	some	some	DET
cjfa-8193	215	22	non	non	ADJ
cjfa-8193	215	23	-	-	NOUN
cjfa-8193	215	24	normality	normality	ADJ
cjfa-8193	215	25	in	in	ADP
cjfa-8193	215	26	returns	return	NOUN
cjfa-8193	215	27	.	.	PUNCT
cjfa-8193	216	1	the	the	DET
cjfa-8193	216	2	second	second	ADJ
cjfa-8193	216	3	and	and	CCONJ
cjfa-8193	216	4	third	third	ADJ
cjfa-8193	216	5	density	density	NOUN
cjfa-8193	216	6	functions	function	NOUN
cjfa-8193	216	7	can	can	AUX
cjfa-8193	216	8	more	more	ADV
cjfa-8193	216	9	fully	fully	ADV
cjfa-8193	216	10	account	account	VERB
cjfa-8193	216	11	for	for	ADP
cjfa-8193	216	12	‘	'	PUNCT
cjfa-8193	216	13	fat	fat	ADJ
cjfa-8193	216	14	-	-	PUNCT
cjfa-8193	216	15	tail	tail	NOUN
cjfa-8193	216	16	’	'	PUNCT
cjfa-8193	216	17	effects	effect	NOUN
cjfa-8193	216	18	;	;	PUNCT
cjfa-8193	216	19	however	however	ADV
cjfa-8193	216	20	,	,	PUNCT
cjfa-8193	216	21	they	they	PRON
cjfa-8193	216	22	do	do	AUX
cjfa-8193	216	23	have	have	VERB
cjfa-8193	216	24	a	a	DET
cjfa-8193	216	25	drawback	drawback	NOUN
cjfa-8193	216	26	in	in	ADP
cjfa-8193	216	27	that	that	SCONJ
cjfa-8193	216	28	they	they	PRON
cjfa-8193	216	29	are	be	AUX
cjfa-8193	216	30	symmetric	symmetric	ADJ
cjfa-8193	216	31	.	.	PUNCT
cjfa-8193	217	1	our	our	PRON
cjfa-8193	217	2	preferred	preferred	ADJ
cjfa-8193	217	3	option	option	NOUN
cjfa-8193	217	4	is	be	AUX
cjfa-8193	217	5	therefore	therefore	ADV
cjfa-8193	217	6	the	the	DET
cjfa-8193	217	7	skewed	skewed	ADJ
cjfa-8193	217	8	-	-	PUNCT
cjfa-8193	217	9	student	student	NOUN
cjfa-8193	217	10	density	density	NOUN
cjfa-8193	217	11	proposed	propose	VERB
cjfa-8193	217	12	by	by	ADP
cjfa-8193	217	13	fernández	fernández	PROPN
cjfa-8193	217	14	and	and	CCONJ
cjfa-8193	217	15	steel	steel	NOUN
cjfa-8193	217	16	(	(	PUNCT
cjfa-8193	217	17	1998	1998	NUM
cjfa-8193	217	18	)	)	PUNCT
cjfa-8193	217	19	.	.	PUNCT
cjfa-8193	218	1	(	(	PUNCT
cjfa-8193	218	2	iv	iv	X
cjfa-8193	218	3	)	)	PUNCT
cjfa-8193	218	4	 	 	SPACE
cjfa-8193	218	5	gaussian	gaussian	NOUN
cjfa-8193	218	6	(	(	PUNCT
cjfa-8193	218	7	normal	normal	ADJ
cjfa-8193	218	8	)	)	PUNCT
cjfa-8193	218	9	distribution	distribution	NOUN
cjfa-8193	218	10	where	where	SCONJ
cjfa-8193	218	11	the	the	DET
cjfa-8193	218	12	log	log	NOUN
cjfa-8193	218	13	-	-	PUNCT
cjfa-8193	218	14	likelihood	likelihood	NOUN
cjfa-8193	218	15	function	function	NOUN
cjfa-8193	218	16	of	of	ADP
cjfa-8193	218	17	the	the	DET
cjfa-8193	218	18	distribution	distribution	NOUN
cjfa-8193	218	19	is	be	AUX
cjfa-8193	218	20	:	:	PUNCT
cjfa-8193	218	21	this	this	DET
cjfa-8193	218	22	variation	variation	NOUN
cjfa-8193	218	23	on	on	ADP
cjfa-8193	218	24	the	the	DET
cjfa-8193	218	25	garch	garch	NOUN
cjfa-8193	218	26	model	model	NOUN
cjfa-8193	218	27	was	be	AUX
cjfa-8193	218	28	proposed	propose	VERB
cjfa-8193	218	29	by	by	ADP
cjfa-8193	218	30	glosten	glosten	ADJ
cjfa-8193	218	31	,	,	PUNCT
cjfa-8193	218	32	jagannathan	jagannathan	NOUN
cjfa-8193	218	33	,	,	PUNCT
cjfa-8193	218	34	and	and	CCONJ
cjfa-8193	218	35	runkle	runkle	ADJ
cjfa-8193	218	36	(	(	PUNCT
cjfa-8193	218	37	1993	1993	NUM
cjfa-8193	218	38	)	)	PUNCT
cjfa-8193	218	39	as	as	ADP
cjfa-8193	218	40	an	an	DET
cjfa-8193	218	41	alternative	alternative	ADJ
cjfa-8193	218	42	way	way	NOUN
cjfa-8193	218	43	of	of	ADP
cjfa-8193	218	44	dealing	deal	VERB
cjfa-8193	218	45	with	with	ADP
cjfa-8193	218	46	asymmetric	asymmetric	ADJ
cjfa-8193	218	47	shocks	shock	NOUN
cjfa-8193	218	48	in	in	ADP
cjfa-8193	218	49	financial	financial	ADJ
cjfa-8193	218	50	series	series	NOUN
cjfa-8193	218	51	.	.	PUNCT
cjfa-8193	219	1	its	its	PRON
cjfa-8193	219	2	generalized	generalized	ADJ
cjfa-8193	219	3	version	version	NOUN
cjfa-8193	219	4	is	be	AUX
cjfa-8193	219	5	:	:	PUNCT
cjfa-8193	219	6	where	where	SCONJ
cjfa-8193	219	7	�	�	PROPN
cjfa-8193	219	8	�	�	PROPN
cjfa-8193	219	9	�	�	PROPN
cjfa-8193	219	10	is	be	AUX
cjfa-8193	219	11	a	a	DET
cjfa-8193	219	12	dummy	dummy	ADJ
cjfa-8193	219	13	variable	variable	NOUN
cjfa-8193	219	14	that	that	PRON
cjfa-8193	219	15	take	take	VERB
cjfa-8193	219	16	the	the	DET
cjfa-8193	219	17	value	value	NOUN
cjfa-8193	219	18	1	1	NUM
cjfa-8193	219	19	when	when	SCONJ
cjfa-8193	219	20	�	�	PROPN
cjfa-8193	219	21	�	�	PROPN
cjfa-8193	219	22	�	�	PROPN
cjfa-8193	219	23	�	�	PROPN
cjfa-8193	219	24	<	<	X
cjfa-8193	219	25	0	0	NUM
cjfa-8193	219	26	,	,	PUNCT
cjfa-8193	219	27	and	and	CCONJ
cjfa-8193	219	28	0	0	NUM
cjfa-8193	219	29	when	when	SCONJ
cjfa-8193	219	30	�	�	PROPN
cjfa-8193	219	31	�	�	PROPN
cjfa-8193	219	32	�	�	PROPN
cjfa-8193	219	33	�	�	PROPN
cjfa-8193	219	34	≥	≥	NUM
cjfa-8193	219	35	0	0	NUM
cjfa-8193	219	36	.	.	PUNCT
cjfa-8193	220	1	a	a	DET
cjfa-8193	220	2	feature	feature	NOUN
cjfa-8193	220	3	of	of	ADP
cjfa-8193	220	4	the	the	DET
cjfa-8193	220	5	gjr	gjr	NOUN
cjfa-8193	220	6	model	model	NOUN
cjfa-8193	220	7	is	be	AUX
cjfa-8193	220	8	that	that	SCONJ
cjfa-8193	220	9	the	the	DET
cjfa-8193	220	10	null	null	ADJ
cjfa-8193	220	11	hypothesis	hypothesis	NOUN
cjfa-8193	220	12	of	of	ADP
cjfa-8193	220	13	no	no	DET
cjfa-8193	220	14	leverage	leverage	NOUN
cjfa-8193	220	15	(	(	PUNCT
cjfa-8193	220	16	asymmetry	asymmetry	NOUN
cjfa-8193	220	17	)	)	PUNCT
cjfa-8193	220	18	effect	effect	NOUN
cjfa-8193	220	19	is	be	AUX
cjfa-8193	220	20	simple	simple	ADJ
cjfa-8193	220	21	to	to	PART
cjfa-8193	220	22	test	test	VERB
cjfa-8193	220	23	.	.	PUNCT
cjfa-8193	221	1	indeed	indeed	ADV
cjfa-8193	221	2	,	,	PUNCT
cjfa-8193	221	3	γ1	γ1	PROPN
cjfa-8193	221	4	=	=	SYM
cjfa-8193	221	5	…	…	PUNCT
cjfa-8193	221	6	=	=	SYM
cjfa-8193	221	7	γq	γq	ADP
cjfa-8193	221	8	=	=	SYM
cjfa-8193	221	9	0	0	NUM
cjfa-8193	221	10	implies	imply	VERB
cjfa-8193	221	11	that	that	SCONJ
cjfa-8193	221	12	the	the	DET
cjfa-8193	221	13	impact	impact	NOUN
cjfa-8193	221	14	of	of	ADP
cjfa-8193	221	15	a	a	DET
cjfa-8193	221	16	shock	shock	NOUN
cjfa-8193	221	17	is	be	AUX
cjfa-8193	221	18	symmetric	symmetric	ADJ
cjfa-8193	221	19	,	,	PUNCT
cjfa-8193	221	20	i.e.	i.e.	X
cjfa-8193	221	21	,	,	PUNCT
cjfa-8193	221	22	past	past	ADP
cjfa-8193	221	23	positive	positive	ADJ
cjfa-8193	221	24	shocks	shock	NOUN
cjfa-8193	221	25	have	have	VERB
cjfa-8193	221	26	the	the	DET
cjfa-8193	221	27	same	same	ADJ
cjfa-8193	221	28	impact	impact	NOUN
cjfa-8193	221	29	on	on	ADP
cjfa-8193	221	30	today	today	NOUN
cjfa-8193	221	31	’s	’s	PART
cjfa-8193	221	32	volatility	volatility	NOUN
cjfa-8193	221	33	as	as	ADP
cjfa-8193	221	34	past	past	ADP
cjfa-8193	221	35	negative	negative	ADJ
cjfa-8193	221	36	shocks	shock	NOUN
cjfa-8193	221	37	.	.	PUNCT
cjfa-8193	222	1	they	they	PRON
cjfa-8193	222	2	do	do	AUX
cjfa-8193	222	3	have	have	VERB
cjfa-8193	222	4	a	a	DET
cjfa-8193	222	5	drawback	drawback	NOUN
cjfa-8193	222	6	in	in	ADP
cjfa-8193	222	7	that	that	SCONJ
cjfa-8193	222	8	they	they	PRON
cjfa-8193	222	9	are	be	AUX
cjfa-8193	222	10	symmetric	symmetric	ADJ
cjfa-8193	222	11	.	.	PUNCT
cjfa-8193	223	1	our	our	PRON
cjfa-8193	223	2	preferred	preferred	ADJ
cjfa-8193	223	3	option	option	NOUN
cjfa-8193	223	4	is	be	AUX
cjfa-8193	223	5	therefore	therefore	ADV
cjfa-8193	223	6	the	the	DET
cjfa-8193	223	7	skewed	skewed	ADJ
cjfa-8193	223	8	-	-	PUNCT
cjfa-8193	223	9	student	student	NOUN
cjfa-8193	223	10	density	density	NOUN
cjfa-8193	223	11	proposed	propose	VERB
cjfa-8193	223	12	by	by	ADP
cjfa-8193	223	13	fernández	fernández	PROPN
cjfa-8193	223	14	and	and	CCONJ
cjfa-8193	223	15	steel	steel	NOUN
cjfa-8193	223	16	(	(	PUNCT
cjfa-8193	223	17	1998	1998	NUM
cjfa-8193	223	18	)	)	PUNCT
cjfa-8193	223	19	.	.	PUNCT
cjfa-8193	224	1	(	(	PUNCT
cjfa-8193	224	2	iv	iv	X
cjfa-8193	224	3	)	)	PUNCT
cjfa-8193	224	4	gaussian	gaussian	NOUN
cjfa-8193	224	5	(	(	PUNCT
cjfa-8193	224	6	normal	normal	ADJ
cjfa-8193	224	7	)	)	PUNCT
cjfa-8193	224	8	distribution	distribution	NOUN
cjfa-8193	224	9	where	where	SCONJ
cjfa-8193	224	10	the	the	DET
cjfa-8193	224	11	log	log	NOUN
cjfa-8193	224	12	-	-	PUNCT
cjfa-8193	224	13	likelihood	likelihood	NOUN
cjfa-8193	224	14	function	function	NOUN
cjfa-8193	224	15	of	of	ADP
cjfa-8193	224	16	the	the	DET
cjfa-8193	224	17	distribution	distribution	NOUN
cjfa-8193	224	18	is	be	AUX
cjfa-8193	224	19	:	:	PUNCT
cjfa-8193	224	20	(	(	PUNCT
cjfa-8193	224	21	v	v	NOUN
cjfa-8193	224	22	)	)	PUNCT
cjfa-8193	224	23	student	student	NOUN
cjfa-8193	224	24	-	-	PUNCT
cjfa-8193	224	25	t	t	NOUN
cjfa-8193	224	26	distribution	distribution	NOUN
cjfa-8193	224	27	where	where	SCONJ
cjfa-8193	224	28	the	the	DET
cjfa-8193	224	29	log	log	NOUN
cjfa-8193	224	30	-	-	PUNCT
cjfa-8193	224	31	likelihood	likelihood	NOUN
cjfa-8193	224	32	function	function	NOUN
cjfa-8193	224	33	of	of	ADP
cjfa-8193	224	34	the	the	DET
cjfa-8193	224	35	distribution	distribution	NOUN
cjfa-8193	224	36	is	be	AUX
cjfa-8193	224	37	:	:	PUNCT
cjfa-8193	224	38	(	(	PUNCT
cjfa-8193	224	39	vi	vi	NOUN
cjfa-8193	224	40	)	)	PUNCT
cjfa-8193	224	41	generalized	generalize	VERB
cjfa-8193	224	42	error	error	NOUN
cjfa-8193	224	43	distribution	distribution	NOUN
cjfa-8193	224	44	(	(	PUNCT
cjfa-8193	224	45	ged	ge	VERB
cjfa-8193	224	46	)	)	PUNCT
cjfa-8193	224	47	where	where	SCONJ
cjfa-8193	224	48	the	the	DET
cjfa-8193	224	49	log	log	NOUN
cjfa-8193	224	50	-	-	PUNCT
cjfa-8193	224	51	likelihood	likelihood	NOUN
cjfa-8193	224	52	function	function	NOUN
cjfa-8193	224	53	of	of	ADP
cjfa-8193	224	54	the	the	DET
cjfa-8193	224	55	distribution	distribution	NOUN
cjfa-8193	224	56	is	be	AUX
cjfa-8193	224	57	:	:	PUNCT
cjfa-8193	224	58	(	(	PUNCT
cjfa-8193	224	59	vii	vii	PROPN
cjfa-8193	224	60	)	)	PUNCT
cjfa-8193	224	61	standardized	standardized	ADJ
cjfa-8193	224	62	(	(	PUNCT
cjfa-8193	224	63	zero	zero	NUM
cjfa-8193	224	64	mean	mean	NOUN
cjfa-8193	224	65	and	and	CCONJ
cjfa-8193	224	66	unit	unit	NOUN
cjfa-8193	224	67	variance	variance	NOUN
cjfa-8193	224	68	)	)	PUNCT
cjfa-8193	224	69	skewed	skewed	ADJ
cjfa-8193	224	70	-	-	PUNCT
cjfa-8193	224	71	student	student	NOUN
cjfa-8193	224	72	distribution	distribution	NOUN
cjfa-8193	224	73	]	]	PUNCT
cjfa-8193	224	74	4	4	NUM
cjfa-8193	224	75	[	[	NOUN
cjfa-8193	224	76	)	)	PUNCT
cjfa-8193	224	77	(	(	PUNCT
cjfa-8193	224	78	2	2	NUM
cjfa-8193	224	79	1	1	NUM
cjfa-8193	224	80	2	2	NUM
cjfa-8193	224	81	1	1	NUM
cjfa-8193	224	82	22	22	NUM
cjfa-8193	224	83	jt	jt	PROPN
cjfa-8193	224	84	p	p	PROPN
cjfa-8193	224	85	j	j	PROPN
cjfa-8193	224	86	jititi	jititi	PROPN
cjfa-8193	224	87	q	q	PROPN
cjfa-8193	225	1	i	i	PRON
cjfa-8193	225	2	itit	itit	VERB
cjfa-8193	225	3	s	s	PART
cjfa-8193	225	4			PROPN
cjfa-8193	225	5			PROPN
cjfa-8193	225	6			PROPN
cjfa-8193	225	7			PROPN
cjfa-8193	225	8			PROPN
cjfa-8193	225	9			PROPN
cjfa-8193	225	10			PROPN
cjfa-8193	225	11			PRON
cjfa-8193	225	12			VERB
cjfa-8193	225	13			PROPN
cjfa-8193	225	14	]	]	SYM
cjfa-8193	225	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	225	16	(	(	PUNCT
cjfa-8193	225	17	2	2	NUM
cjfa-8193	225	18	1	1	NUM
cjfa-8193	225	19	2	2	NUM
cjfa-8193	225	20	1	1	NUM
cjfa-8193	225	21	2	2	NUM
cjfa-8193	225	22	t	t	NOUN
cjfa-8193	225	23	t	t	NOUN
cjfa-8193	225	24	t	t	NOUN
cjfa-8193	225	25	tnorm	tnorm	NOUN
cjfa-8193	226	1	zl	zl	PROPN
cjfa-8193	227	1			PROPN
cjfa-8193	227	2			NUM
cjfa-8193	227	3			NUM
cjfa-8193	227	4			VERB
cjfa-8193	227	5			PROPN
cjfa-8193	227	6			PROPN
cjfa-8193	227	7	]	]	SYM
cjfa-8193	227	8	6	6	NUM
cjfa-8193	227	9	[	[	SYM
cjfa-8193	227	10	2	2	NUM
cjfa-8193	227	11	1log)1()log	1log)1()log	NUM
cjfa-8193	227	12	(	(	PUNCT
cjfa-8193	227	13	2	2	NUM
cjfa-8193	227	14	1	1	NUM
cjfa-8193	227	15	)	)	PUNCT
cjfa-8193	227	16	2(log	2(log	NOUN
cjfa-8193	227	17	2	2	NUM
cjfa-8193	227	18	1	1	NUM
cjfa-8193	227	19	2	2	NUM
cjfa-8193	227	20	log	log	NOUN
cjfa-8193	227	21	2	2	NUM
cjfa-8193	227	22	1log	1log	NUM
cjfa-8193	227	23	1	1	NUM
cjfa-8193	227	24	2	2	NUM
cjfa-8193	227	25	2	2	NUM
cjfa-8193	227	26			ADJ
cjfa-8193	227	27			PROPN
cjfa-8193	227	28			PROPN
cjfa-8193	227	29			PRON
cjfa-8193	227	30			NOUN
cjfa-8193	227	31			VERB
cjfa-8193	227	32			PROPN
cjfa-8193	227	33			NOUN
cjfa-8193	227	34			NOUN
cjfa-8193	227	35			PROPN
cjfa-8193	227	36			PROPN
cjfa-8193	227	37			PROPN
cjfa-8193	227	38			NOUN
cjfa-8193	227	39			PROPN
cjfa-8193	227	40			PROPN
cjfa-8193	227	41			PROPN
cjfa-8193	227	42			PROPN
cjfa-8193	228	1			PROPN
cjfa-8193	228	2			INTJ
cjfa-8193	228	3			NUM
cjfa-8193	228	4			ADV
cjfa-8193	228	5			VERB
cjfa-8193	228	6			NOUN
cjfa-8193	228	7			PRON
cjfa-8193	228	8			PROPN
cjfa-8193	228	9			PROPN
cjfa-8193	228	10			NOUN
cjfa-8193	228	11			NUM
cjfa-8193	228	12			PRON
cjfa-8193	228	13			PROPN
cjfa-8193	228	14			PROPN
cjfa-8193	228	15			NOUN
cjfa-8193	228	16			PUNCT
cjfa-8193	229	1	t	t	PROPN
cjfa-8193	229	2	t	t	PROPN
cjfa-8193	229	3	t	t	PROPN
cjfa-8193	229	4	t	t	PROPN
cjfa-8193	229	5	stud	stud	NOUN
cjfa-8193	229	6	v	v	ADP
cjfa-8193	229	7	z	z	PROPN
cjfa-8193	229	8	tl	tl	PROPN
cjfa-8193	229	9			PROPN
cjfa-8193	229	10			NOUN
cjfa-8193	229	11	]	]	PUNCT
cjfa-8193	229	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	229	13	1	1	NUM
cjfa-8193	229	14	21	21	NUM
cjfa-8193	229	15			PROPN
cjfa-8193	229	16			NOUN
cjfa-8193	229	17			NOUN
cjfa-8193	229	18			PROPN
cjfa-8193	229	19			PROPN
cjfa-8193	229	20			X
cjfa-8193	229	21			NOUN
cjfa-8193	229	22			NOUN
cjfa-8193	229	23			NOUN
cjfa-8193	230	1			PROPN
cjfa-8193	230	2			NOUN
cjfa-8193	230	3			NOUN
cjfa-8193	230	4			PRON
cjfa-8193	230	5			PROPN
cjfa-8193	231	1			PROPN
cjfa-8193	231	2			NOUN
cjfa-8193	231	3			NOUN
cjfa-8193	231	4			PROPN
cjfa-8193	231	5			PROPN
cjfa-8193	231	6			PROPN
cjfa-8193	231	7			NOUN
cjfa-8193	232	1			PROPN
cjfa-8193	232	2	t	t	PROPN
cjfa-8193	232	3	t	t	PROPN
cjfa-8193	232	4	t	t	PROPN
cjfa-8193	232	5	t	t	PROPN
cjfa-8193	232	6	ged	ge	VERB
cjfa-8193	232	7	zl	zl	PROPN
cjfa-8193	232	8			PROPN
cjfa-8193	232	9			ADJ
cjfa-8193	232	10			NOUN
cjfa-8193	232	11			NOUN
cjfa-8193	232	12			ADJ
cjfa-8193	232	13			NOUN
cjfa-8193	232	14			NOUN
cjfa-8193	232	15	]	]	PUNCT
cjfa-8193	233	1	[	[	X
cjfa-8193	233	2	5	5	NUM
cjfa-8193	233	3	]	]	PUNCT
cjfa-8193	233	4	(	(	PUNCT
cjfa-8193	233	5	v	v	NOUN
cjfa-8193	233	6	)	)	PUNCT
cjfa-8193	233	7	 	 	SPACE
cjfa-8193	233	8	student	student	NOUN
cjfa-8193	233	9	-	-	PUNCT
cjfa-8193	233	10	t	t	NOUN
cjfa-8193	233	11	distribution	distribution	NOUN
cjfa-8193	233	12	where	where	SCONJ
cjfa-8193	233	13	the	the	DET
cjfa-8193	233	14	log	log	NOUN
cjfa-8193	233	15	-	-	PUNCT
cjfa-8193	233	16	likelihood	likelihood	NOUN
cjfa-8193	233	17	function	function	NOUN
cjfa-8193	233	18	of	of	ADP
cjfa-8193	233	19	the	the	DET
cjfa-8193	233	20	distribution	distribution	NOUN
cjfa-8193	233	21	is	be	AUX
cjfa-8193	233	22	:	:	PUNCT
cjfa-8193	233	23	this	this	DET
cjfa-8193	233	24	variation	variation	NOUN
cjfa-8193	233	25	on	on	ADP
cjfa-8193	233	26	the	the	DET
cjfa-8193	233	27	garch	garch	NOUN
cjfa-8193	233	28	model	model	NOUN
cjfa-8193	233	29	was	be	AUX
cjfa-8193	233	30	proposed	propose	VERB
cjfa-8193	233	31	by	by	ADP
cjfa-8193	233	32	glosten	glosten	ADJ
cjfa-8193	233	33	,	,	PUNCT
cjfa-8193	233	34	jagannathan	jagannathan	NOUN
cjfa-8193	233	35	,	,	PUNCT
cjfa-8193	233	36	and	and	CCONJ
cjfa-8193	233	37	runkle	runkle	ADJ
cjfa-8193	233	38	(	(	PUNCT
cjfa-8193	233	39	1993	1993	NUM
cjfa-8193	233	40	)	)	PUNCT
cjfa-8193	233	41	as	as	ADP
cjfa-8193	233	42	an	an	DET
cjfa-8193	233	43	alternative	alternative	ADJ
cjfa-8193	233	44	way	way	NOUN
cjfa-8193	233	45	of	of	ADP
cjfa-8193	233	46	dealing	deal	VERB
cjfa-8193	233	47	with	with	ADP
cjfa-8193	233	48	asymmetric	asymmetric	ADJ
cjfa-8193	233	49	shocks	shock	NOUN
cjfa-8193	233	50	in	in	ADP
cjfa-8193	233	51	financial	financial	ADJ
cjfa-8193	233	52	series	series	NOUN
cjfa-8193	233	53	.	.	PUNCT
cjfa-8193	234	1	its	its	PRON
cjfa-8193	234	2	generalized	generalized	ADJ
cjfa-8193	234	3	version	version	NOUN
cjfa-8193	234	4	is	be	AUX
cjfa-8193	234	5	:	:	PUNCT
cjfa-8193	234	6	where	where	SCONJ
cjfa-8193	234	7	�	�	PROPN
cjfa-8193	234	8	�	�	PROPN
cjfa-8193	234	9	�	�	PROPN
cjfa-8193	234	10	is	be	AUX
cjfa-8193	234	11	a	a	DET
cjfa-8193	234	12	dummy	dummy	ADJ
cjfa-8193	234	13	variable	variable	NOUN
cjfa-8193	234	14	that	that	PRON
cjfa-8193	234	15	take	take	VERB
cjfa-8193	234	16	the	the	DET
cjfa-8193	234	17	value	value	NOUN
cjfa-8193	234	18	1	1	NUM
cjfa-8193	234	19	when	when	SCONJ
cjfa-8193	234	20	�	�	PROPN
cjfa-8193	234	21	�	�	PROPN
cjfa-8193	234	22	�	�	PROPN
cjfa-8193	234	23	�	�	PROPN
cjfa-8193	234	24	<	<	X
cjfa-8193	234	25	0	0	NUM
cjfa-8193	234	26	,	,	PUNCT
cjfa-8193	234	27	and	and	CCONJ
cjfa-8193	234	28	0	0	NUM
cjfa-8193	234	29	when	when	SCONJ
cjfa-8193	234	30	�	�	PROPN
cjfa-8193	234	31	�	�	PROPN
cjfa-8193	234	32	�	�	PROPN
cjfa-8193	234	33	�	�	PROPN
cjfa-8193	234	34	≥	≥	NUM
cjfa-8193	234	35	0	0	NUM
cjfa-8193	234	36	.	.	PUNCT
cjfa-8193	235	1	a	a	DET
cjfa-8193	235	2	feature	feature	NOUN
cjfa-8193	235	3	of	of	ADP
cjfa-8193	235	4	the	the	DET
cjfa-8193	235	5	gjr	gjr	NOUN
cjfa-8193	235	6	model	model	NOUN
cjfa-8193	235	7	is	be	AUX
cjfa-8193	235	8	that	that	SCONJ
cjfa-8193	235	9	the	the	DET
cjfa-8193	235	10	null	null	ADJ
cjfa-8193	235	11	hypothesis	hypothesis	NOUN
cjfa-8193	235	12	of	of	ADP
cjfa-8193	235	13	no	no	DET
cjfa-8193	235	14	leverage	leverage	NOUN
cjfa-8193	235	15	(	(	PUNCT
cjfa-8193	235	16	asymmetry	asymmetry	NOUN
cjfa-8193	235	17	)	)	PUNCT
cjfa-8193	235	18	effect	effect	NOUN
cjfa-8193	235	19	is	be	AUX
cjfa-8193	235	20	simple	simple	ADJ
cjfa-8193	235	21	to	to	PART
cjfa-8193	235	22	test	test	VERB
cjfa-8193	235	23	.	.	PUNCT
cjfa-8193	236	1	indeed	indeed	ADV
cjfa-8193	236	2	,	,	PUNCT
cjfa-8193	236	3	γ1	γ1	PROPN
cjfa-8193	236	4	=	=	SYM
cjfa-8193	236	5	…	…	PUNCT
cjfa-8193	236	6	=	=	SYM
cjfa-8193	236	7	γq	γq	ADP
cjfa-8193	236	8	=	=	SYM
cjfa-8193	236	9	0	0	NUM
cjfa-8193	236	10	implies	imply	VERB
cjfa-8193	236	11	that	that	SCONJ
cjfa-8193	236	12	the	the	DET
cjfa-8193	236	13	impact	impact	NOUN
cjfa-8193	236	14	of	of	ADP
cjfa-8193	236	15	a	a	DET
cjfa-8193	236	16	shock	shock	NOUN
cjfa-8193	236	17	is	be	AUX
cjfa-8193	236	18	symmetric	symmetric	ADJ
cjfa-8193	236	19	,	,	PUNCT
cjfa-8193	236	20	i.e.	i.e.	X
cjfa-8193	236	21	,	,	PUNCT
cjfa-8193	236	22	past	past	ADP
cjfa-8193	236	23	positive	positive	ADJ
cjfa-8193	236	24	shocks	shock	NOUN
cjfa-8193	236	25	have	have	VERB
cjfa-8193	236	26	the	the	DET
cjfa-8193	236	27	same	same	ADJ
cjfa-8193	236	28	impact	impact	NOUN
cjfa-8193	236	29	on	on	ADP
cjfa-8193	236	30	today	today	NOUN
cjfa-8193	236	31	’s	’s	PART
cjfa-8193	236	32	volatility	volatility	NOUN
cjfa-8193	236	33	as	as	ADP
cjfa-8193	236	34	past	past	ADP
cjfa-8193	236	35	negative	negative	ADJ
cjfa-8193	236	36	shocks	shock	NOUN
cjfa-8193	236	37	.	.	PUNCT
cjfa-8193	237	1	they	they	PRON
cjfa-8193	237	2	do	do	AUX
cjfa-8193	237	3	have	have	VERB
cjfa-8193	237	4	a	a	DET
cjfa-8193	237	5	drawback	drawback	NOUN
cjfa-8193	237	6	in	in	ADP
cjfa-8193	237	7	that	that	SCONJ
cjfa-8193	237	8	they	they	PRON
cjfa-8193	237	9	are	be	AUX
cjfa-8193	237	10	symmetric	symmetric	ADJ
cjfa-8193	237	11	.	.	PUNCT
cjfa-8193	238	1	our	our	PRON
cjfa-8193	238	2	preferred	preferred	ADJ
cjfa-8193	238	3	option	option	NOUN
cjfa-8193	238	4	is	be	AUX
cjfa-8193	238	5	therefore	therefore	ADV
cjfa-8193	238	6	the	the	DET
cjfa-8193	238	7	skewed	skewed	ADJ
cjfa-8193	238	8	-	-	PUNCT
cjfa-8193	238	9	student	student	NOUN
cjfa-8193	238	10	density	density	NOUN
cjfa-8193	238	11	proposed	propose	VERB
cjfa-8193	238	12	by	by	ADP
cjfa-8193	238	13	fernández	fernández	PROPN
cjfa-8193	238	14	and	and	CCONJ
cjfa-8193	238	15	steel	steel	NOUN
cjfa-8193	238	16	(	(	PUNCT
cjfa-8193	238	17	1998	1998	NUM
cjfa-8193	238	18	)	)	PUNCT
cjfa-8193	238	19	.	.	PUNCT
cjfa-8193	239	1	(	(	PUNCT
cjfa-8193	239	2	iv	iv	X
cjfa-8193	239	3	)	)	PUNCT
cjfa-8193	239	4	gaussian	gaussian	NOUN
cjfa-8193	239	5	(	(	PUNCT
cjfa-8193	239	6	normal	normal	ADJ
cjfa-8193	239	7	)	)	PUNCT
cjfa-8193	239	8	distribution	distribution	NOUN
cjfa-8193	239	9	where	where	SCONJ
cjfa-8193	239	10	the	the	DET
cjfa-8193	239	11	log	log	NOUN
cjfa-8193	239	12	-	-	PUNCT
cjfa-8193	239	13	likelihood	likelihood	NOUN
cjfa-8193	239	14	function	function	NOUN
cjfa-8193	239	15	of	of	ADP
cjfa-8193	239	16	the	the	DET
cjfa-8193	239	17	distribution	distribution	NOUN
cjfa-8193	239	18	is	be	AUX
cjfa-8193	239	19	:	:	PUNCT
cjfa-8193	239	20	(	(	PUNCT
cjfa-8193	239	21	v	v	NOUN
cjfa-8193	239	22	)	)	PUNCT
cjfa-8193	239	23	student	student	NOUN
cjfa-8193	239	24	-	-	PUNCT
cjfa-8193	239	25	t	t	NOUN
cjfa-8193	239	26	distribution	distribution	NOUN
cjfa-8193	239	27	where	where	SCONJ
cjfa-8193	239	28	the	the	DET
cjfa-8193	239	29	log	log	NOUN
cjfa-8193	239	30	-	-	PUNCT
cjfa-8193	239	31	likelihood	likelihood	NOUN
cjfa-8193	239	32	function	function	NOUN
cjfa-8193	239	33	of	of	ADP
cjfa-8193	239	34	the	the	DET
cjfa-8193	239	35	distribution	distribution	NOUN
cjfa-8193	239	36	is	be	AUX
cjfa-8193	239	37	:	:	PUNCT
cjfa-8193	239	38	(	(	PUNCT
cjfa-8193	239	39	vi	vi	NOUN
cjfa-8193	239	40	)	)	PUNCT
cjfa-8193	239	41	generalized	generalize	VERB
cjfa-8193	239	42	error	error	NOUN
cjfa-8193	239	43	distribution	distribution	NOUN
cjfa-8193	239	44	(	(	PUNCT
cjfa-8193	239	45	ged	ge	VERB
cjfa-8193	239	46	)	)	PUNCT
cjfa-8193	239	47	where	where	SCONJ
cjfa-8193	239	48	the	the	DET
cjfa-8193	239	49	log	log	NOUN
cjfa-8193	239	50	-	-	PUNCT
cjfa-8193	239	51	likelihood	likelihood	NOUN
cjfa-8193	239	52	function	function	NOUN
cjfa-8193	239	53	of	of	ADP
cjfa-8193	239	54	the	the	DET
cjfa-8193	239	55	distribution	distribution	NOUN
cjfa-8193	239	56	is	be	AUX
cjfa-8193	239	57	:	:	PUNCT
cjfa-8193	239	58	(	(	PUNCT
cjfa-8193	239	59	vii	vii	PROPN
cjfa-8193	239	60	)	)	PUNCT
cjfa-8193	239	61	standardized	standardized	ADJ
cjfa-8193	239	62	(	(	PUNCT
cjfa-8193	239	63	zero	zero	NUM
cjfa-8193	239	64	mean	mean	NOUN
cjfa-8193	239	65	and	and	CCONJ
cjfa-8193	239	66	unit	unit	NOUN
cjfa-8193	239	67	variance	variance	NOUN
cjfa-8193	239	68	)	)	PUNCT
cjfa-8193	239	69	skewed	skewed	ADJ
cjfa-8193	239	70	-	-	PUNCT
cjfa-8193	239	71	student	student	NOUN
cjfa-8193	239	72	distribution	distribution	NOUN
cjfa-8193	239	73	]	]	PUNCT
cjfa-8193	239	74	4	4	NUM
cjfa-8193	239	75	[	[	NOUN
cjfa-8193	239	76	)	)	PUNCT
cjfa-8193	239	77	(	(	PUNCT
cjfa-8193	239	78	2	2	NUM
cjfa-8193	239	79	1	1	NUM
cjfa-8193	239	80	2	2	NUM
cjfa-8193	239	81	1	1	NUM
cjfa-8193	239	82	22	22	NUM
cjfa-8193	239	83	jt	jt	PROPN
cjfa-8193	239	84	p	p	PROPN
cjfa-8193	239	85	j	j	PROPN
cjfa-8193	239	86	jititi	jititi	PROPN
cjfa-8193	239	87	q	q	PROPN
cjfa-8193	240	1	i	i	PRON
cjfa-8193	240	2	itit	itit	VERB
cjfa-8193	240	3	s	s	PART
cjfa-8193	240	4			PROPN
cjfa-8193	240	5			PROPN
cjfa-8193	240	6			PROPN
cjfa-8193	240	7			PROPN
cjfa-8193	240	8			PROPN
cjfa-8193	240	9			PROPN
cjfa-8193	240	10			PROPN
cjfa-8193	240	11			PRON
cjfa-8193	240	12			VERB
cjfa-8193	240	13			PROPN
cjfa-8193	240	14	]	]	SYM
cjfa-8193	240	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	240	16	(	(	PUNCT
cjfa-8193	240	17	2	2	NUM
cjfa-8193	240	18	1	1	NUM
cjfa-8193	240	19	2	2	NUM
cjfa-8193	240	20	1	1	NUM
cjfa-8193	240	21	2	2	NUM
cjfa-8193	240	22	t	t	NOUN
cjfa-8193	240	23	t	t	NOUN
cjfa-8193	240	24	t	t	NOUN
cjfa-8193	240	25	tnorm	tnorm	NOUN
cjfa-8193	241	1	zl	zl	PROPN
cjfa-8193	242	1			PROPN
cjfa-8193	242	2			NUM
cjfa-8193	242	3			NUM
cjfa-8193	242	4			VERB
cjfa-8193	242	5			PROPN
cjfa-8193	242	6			PROPN
cjfa-8193	242	7	]	]	SYM
cjfa-8193	242	8	6	6	NUM
cjfa-8193	242	9	[	[	SYM
cjfa-8193	242	10	2	2	NUM
cjfa-8193	242	11	1log)1()log	1log)1()log	NUM
cjfa-8193	242	12	(	(	PUNCT
cjfa-8193	242	13	2	2	NUM
cjfa-8193	242	14	1	1	NUM
cjfa-8193	242	15	)	)	PUNCT
cjfa-8193	242	16	2(log	2(log	NOUN
cjfa-8193	242	17	2	2	NUM
cjfa-8193	242	18	1	1	NUM
cjfa-8193	242	19	2	2	NUM
cjfa-8193	242	20	log	log	NOUN
cjfa-8193	242	21	2	2	NUM
cjfa-8193	242	22	1log	1log	NUM
cjfa-8193	242	23	1	1	NUM
cjfa-8193	242	24	2	2	NUM
cjfa-8193	242	25	2	2	NUM
cjfa-8193	242	26			ADJ
cjfa-8193	242	27			PROPN
cjfa-8193	242	28			PROPN
cjfa-8193	242	29			PRON
cjfa-8193	242	30			NOUN
cjfa-8193	242	31			VERB
cjfa-8193	242	32			PROPN
cjfa-8193	242	33			NOUN
cjfa-8193	242	34			NOUN
cjfa-8193	242	35			PROPN
cjfa-8193	242	36			PROPN
cjfa-8193	242	37			PROPN
cjfa-8193	242	38			NOUN
cjfa-8193	242	39			PROPN
cjfa-8193	242	40			PROPN
cjfa-8193	242	41			PROPN
cjfa-8193	242	42			PROPN
cjfa-8193	243	1			PROPN
cjfa-8193	243	2			INTJ
cjfa-8193	243	3			NUM
cjfa-8193	243	4			ADV
cjfa-8193	243	5			VERB
cjfa-8193	243	6			NOUN
cjfa-8193	243	7			PRON
cjfa-8193	243	8			PROPN
cjfa-8193	243	9			PROPN
cjfa-8193	243	10			NOUN
cjfa-8193	243	11			NUM
cjfa-8193	243	12			PRON
cjfa-8193	243	13			PROPN
cjfa-8193	243	14			PROPN
cjfa-8193	243	15			NOUN
cjfa-8193	243	16			PUNCT
cjfa-8193	244	1	t	t	PROPN
cjfa-8193	244	2	t	t	PROPN
cjfa-8193	244	3	t	t	PROPN
cjfa-8193	244	4	t	t	PROPN
cjfa-8193	244	5	stud	stud	NOUN
cjfa-8193	244	6	v	v	ADP
cjfa-8193	244	7	z	z	PROPN
cjfa-8193	244	8	tl	tl	PROPN
cjfa-8193	244	9			PROPN
cjfa-8193	244	10			NOUN
cjfa-8193	244	11	]	]	PUNCT
cjfa-8193	244	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	244	13	1	1	NUM
cjfa-8193	244	14	21	21	NUM
cjfa-8193	244	15			PROPN
cjfa-8193	244	16			NOUN
cjfa-8193	244	17			NOUN
cjfa-8193	244	18			PROPN
cjfa-8193	244	19			PROPN
cjfa-8193	244	20			X
cjfa-8193	244	21			NOUN
cjfa-8193	244	22			NOUN
cjfa-8193	244	23			NOUN
cjfa-8193	245	1			PROPN
cjfa-8193	245	2			NOUN
cjfa-8193	245	3			NOUN
cjfa-8193	245	4			PRON
cjfa-8193	245	5			PROPN
cjfa-8193	246	1			PROPN
cjfa-8193	246	2			NOUN
cjfa-8193	246	3			NOUN
cjfa-8193	246	4			PROPN
cjfa-8193	246	5			PROPN
cjfa-8193	246	6			PROPN
cjfa-8193	246	7			NOUN
cjfa-8193	247	1			PROPN
cjfa-8193	247	2	t	t	PROPN
cjfa-8193	247	3	t	t	PROPN
cjfa-8193	247	4	t	t	PROPN
cjfa-8193	247	5	t	t	PROPN
cjfa-8193	247	6	ged	ge	VERB
cjfa-8193	247	7	zl	zl	PROPN
cjfa-8193	247	8			PROPN
cjfa-8193	247	9			ADJ
cjfa-8193	247	10			NOUN
cjfa-8193	247	11			NOUN
cjfa-8193	247	12			ADJ
cjfa-8193	247	13			NOUN
cjfa-8193	247	14			NOUN
cjfa-8193	247	15	this	this	DET
cjfa-8193	247	16	variation	variation	NOUN
cjfa-8193	247	17	on	on	ADP
cjfa-8193	247	18	the	the	DET
cjfa-8193	247	19	garch	garch	NOUN
cjfa-8193	247	20	model	model	NOUN
cjfa-8193	247	21	was	be	AUX
cjfa-8193	247	22	proposed	propose	VERB
cjfa-8193	247	23	by	by	ADP
cjfa-8193	247	24	glosten	glosten	ADJ
cjfa-8193	247	25	,	,	PUNCT
cjfa-8193	247	26	jagannathan	jagannathan	NOUN
cjfa-8193	247	27	,	,	PUNCT
cjfa-8193	247	28	and	and	CCONJ
cjfa-8193	247	29	runkle	runkle	ADJ
cjfa-8193	247	30	(	(	PUNCT
cjfa-8193	247	31	1993	1993	NUM
cjfa-8193	247	32	)	)	PUNCT
cjfa-8193	247	33	as	as	ADP
cjfa-8193	247	34	an	an	DET
cjfa-8193	247	35	alternative	alternative	ADJ
cjfa-8193	247	36	way	way	NOUN
cjfa-8193	247	37	of	of	ADP
cjfa-8193	247	38	dealing	deal	VERB
cjfa-8193	247	39	with	with	ADP
cjfa-8193	247	40	asymmetric	asymmetric	ADJ
cjfa-8193	247	41	shocks	shock	NOUN
cjfa-8193	247	42	in	in	ADP
cjfa-8193	247	43	financial	financial	ADJ
cjfa-8193	247	44	series	series	NOUN
cjfa-8193	247	45	.	.	PUNCT
cjfa-8193	248	1	its	its	PRON
cjfa-8193	248	2	generalized	generalized	ADJ
cjfa-8193	248	3	version	version	NOUN
cjfa-8193	248	4	is	be	AUX
cjfa-8193	248	5	:	:	PUNCT
cjfa-8193	248	6	where	where	SCONJ
cjfa-8193	248	7	�	�	PROPN
cjfa-8193	248	8	�	�	PROPN
cjfa-8193	248	9	�	�	PROPN
cjfa-8193	248	10	is	be	AUX
cjfa-8193	248	11	a	a	DET
cjfa-8193	248	12	dummy	dummy	ADJ
cjfa-8193	248	13	variable	variable	NOUN
cjfa-8193	248	14	that	that	PRON
cjfa-8193	248	15	take	take	VERB
cjfa-8193	248	16	the	the	DET
cjfa-8193	248	17	value	value	NOUN
cjfa-8193	248	18	1	1	NUM
cjfa-8193	248	19	when	when	SCONJ
cjfa-8193	248	20	�	�	PROPN
cjfa-8193	248	21	�	�	PROPN
cjfa-8193	248	22	�	�	PROPN
cjfa-8193	248	23	�	�	PROPN
cjfa-8193	248	24	<	<	X
cjfa-8193	248	25	0	0	NUM
cjfa-8193	248	26	,	,	PUNCT
cjfa-8193	248	27	and	and	CCONJ
cjfa-8193	248	28	0	0	NUM
cjfa-8193	248	29	when	when	SCONJ
cjfa-8193	248	30	�	�	PROPN
cjfa-8193	248	31	�	�	PROPN
cjfa-8193	248	32	�	�	PROPN
cjfa-8193	248	33	�	�	PROPN
cjfa-8193	248	34	≥	≥	NUM
cjfa-8193	248	35	0	0	NUM
cjfa-8193	248	36	.	.	PUNCT
cjfa-8193	249	1	a	a	DET
cjfa-8193	249	2	feature	feature	NOUN
cjfa-8193	249	3	of	of	ADP
cjfa-8193	249	4	the	the	DET
cjfa-8193	249	5	gjr	gjr	NOUN
cjfa-8193	249	6	model	model	NOUN
cjfa-8193	249	7	is	be	AUX
cjfa-8193	249	8	that	that	SCONJ
cjfa-8193	249	9	the	the	DET
cjfa-8193	249	10	null	null	ADJ
cjfa-8193	249	11	hypothesis	hypothesis	NOUN
cjfa-8193	249	12	of	of	ADP
cjfa-8193	249	13	no	no	DET
cjfa-8193	249	14	leverage	leverage	NOUN
cjfa-8193	249	15	(	(	PUNCT
cjfa-8193	249	16	asymmetry	asymmetry	NOUN
cjfa-8193	249	17	)	)	PUNCT
cjfa-8193	249	18	effect	effect	NOUN
cjfa-8193	249	19	is	be	AUX
cjfa-8193	249	20	simple	simple	ADJ
cjfa-8193	249	21	to	to	PART
cjfa-8193	249	22	test	test	VERB
cjfa-8193	249	23	.	.	PUNCT
cjfa-8193	250	1	indeed	indeed	ADV
cjfa-8193	250	2	,	,	PUNCT
cjfa-8193	250	3	γ1	γ1	PROPN
cjfa-8193	250	4	=	=	SYM
cjfa-8193	250	5	…	…	PUNCT
cjfa-8193	250	6	=	=	SYM
cjfa-8193	250	7	γq	γq	ADP
cjfa-8193	250	8	=	=	SYM
cjfa-8193	250	9	0	0	NUM
cjfa-8193	250	10	implies	imply	VERB
cjfa-8193	250	11	that	that	SCONJ
cjfa-8193	250	12	the	the	DET
cjfa-8193	250	13	impact	impact	NOUN
cjfa-8193	250	14	of	of	ADP
cjfa-8193	250	15	a	a	DET
cjfa-8193	250	16	shock	shock	NOUN
cjfa-8193	250	17	is	be	AUX
cjfa-8193	250	18	symmetric	symmetric	ADJ
cjfa-8193	250	19	,	,	PUNCT
cjfa-8193	250	20	i.e.	i.e.	X
cjfa-8193	250	21	,	,	PUNCT
cjfa-8193	250	22	past	past	ADP
cjfa-8193	250	23	positive	positive	ADJ
cjfa-8193	250	24	shocks	shock	NOUN
cjfa-8193	250	25	have	have	VERB
cjfa-8193	250	26	the	the	DET
cjfa-8193	250	27	same	same	ADJ
cjfa-8193	250	28	impact	impact	NOUN
cjfa-8193	250	29	on	on	ADP
cjfa-8193	250	30	today	today	NOUN
cjfa-8193	250	31	’s	’s	PART
cjfa-8193	250	32	volatility	volatility	NOUN
cjfa-8193	250	33	as	as	ADP
cjfa-8193	250	34	past	past	ADP
cjfa-8193	250	35	negative	negative	ADJ
cjfa-8193	250	36	shocks	shock	NOUN
cjfa-8193	250	37	.	.	PUNCT
cjfa-8193	251	1	they	they	PRON
cjfa-8193	251	2	do	do	AUX
cjfa-8193	251	3	have	have	VERB
cjfa-8193	251	4	a	a	DET
cjfa-8193	251	5	drawback	drawback	NOUN
cjfa-8193	251	6	in	in	ADP
cjfa-8193	251	7	that	that	SCONJ
cjfa-8193	251	8	they	they	PRON
cjfa-8193	251	9	are	be	AUX
cjfa-8193	251	10	symmetric	symmetric	ADJ
cjfa-8193	251	11	.	.	PUNCT
cjfa-8193	252	1	our	our	PRON
cjfa-8193	252	2	preferred	preferred	ADJ
cjfa-8193	252	3	option	option	NOUN
cjfa-8193	252	4	is	be	AUX
cjfa-8193	252	5	therefore	therefore	ADV
cjfa-8193	252	6	the	the	DET
cjfa-8193	252	7	skewed	skewed	ADJ
cjfa-8193	252	8	-	-	PUNCT
cjfa-8193	252	9	student	student	NOUN
cjfa-8193	252	10	density	density	NOUN
cjfa-8193	252	11	proposed	propose	VERB
cjfa-8193	252	12	by	by	ADP
cjfa-8193	252	13	fernández	fernández	PROPN
cjfa-8193	252	14	and	and	CCONJ
cjfa-8193	252	15	steel	steel	NOUN
cjfa-8193	252	16	(	(	PUNCT
cjfa-8193	252	17	1998	1998	NUM
cjfa-8193	252	18	)	)	PUNCT
cjfa-8193	252	19	.	.	PUNCT
cjfa-8193	253	1	(	(	PUNCT
cjfa-8193	253	2	iv	iv	X
cjfa-8193	253	3	)	)	PUNCT
cjfa-8193	253	4	gaussian	gaussian	NOUN
cjfa-8193	253	5	(	(	PUNCT
cjfa-8193	253	6	normal	normal	ADJ
cjfa-8193	253	7	)	)	PUNCT
cjfa-8193	253	8	distribution	distribution	NOUN
cjfa-8193	253	9	where	where	SCONJ
cjfa-8193	253	10	the	the	DET
cjfa-8193	253	11	log	log	NOUN
cjfa-8193	253	12	-	-	PUNCT
cjfa-8193	253	13	likelihood	likelihood	NOUN
cjfa-8193	253	14	function	function	NOUN
cjfa-8193	253	15	of	of	ADP
cjfa-8193	253	16	the	the	DET
cjfa-8193	253	17	distribution	distribution	NOUN
cjfa-8193	253	18	is	be	AUX
cjfa-8193	253	19	:	:	PUNCT
cjfa-8193	253	20	(	(	PUNCT
cjfa-8193	253	21	v	v	NOUN
cjfa-8193	253	22	)	)	PUNCT
cjfa-8193	253	23	student	student	NOUN
cjfa-8193	253	24	-	-	PUNCT
cjfa-8193	253	25	t	t	NOUN
cjfa-8193	253	26	distribution	distribution	NOUN
cjfa-8193	253	27	where	where	SCONJ
cjfa-8193	253	28	the	the	DET
cjfa-8193	253	29	log	log	NOUN
cjfa-8193	253	30	-	-	PUNCT
cjfa-8193	253	31	likelihood	likelihood	NOUN
cjfa-8193	253	32	function	function	NOUN
cjfa-8193	253	33	of	of	ADP
cjfa-8193	253	34	the	the	DET
cjfa-8193	253	35	distribution	distribution	NOUN
cjfa-8193	253	36	is	be	AUX
cjfa-8193	253	37	:	:	PUNCT
cjfa-8193	253	38	(	(	PUNCT
cjfa-8193	253	39	vi	vi	NOUN
cjfa-8193	253	40	)	)	PUNCT
cjfa-8193	253	41	generalized	generalize	VERB
cjfa-8193	253	42	error	error	NOUN
cjfa-8193	253	43	distribution	distribution	NOUN
cjfa-8193	253	44	(	(	PUNCT
cjfa-8193	253	45	ged	ge	VERB
cjfa-8193	253	46	)	)	PUNCT
cjfa-8193	253	47	where	where	SCONJ
cjfa-8193	253	48	the	the	DET
cjfa-8193	253	49	log	log	NOUN
cjfa-8193	253	50	-	-	PUNCT
cjfa-8193	253	51	likelihood	likelihood	NOUN
cjfa-8193	253	52	function	function	NOUN
cjfa-8193	253	53	of	of	ADP
cjfa-8193	253	54	the	the	DET
cjfa-8193	253	55	distribution	distribution	NOUN
cjfa-8193	253	56	is	be	AUX
cjfa-8193	253	57	:	:	PUNCT
cjfa-8193	253	58	(	(	PUNCT
cjfa-8193	253	59	vii	vii	PROPN
cjfa-8193	253	60	)	)	PUNCT
cjfa-8193	253	61	standardized	standardized	ADJ
cjfa-8193	253	62	(	(	PUNCT
cjfa-8193	253	63	zero	zero	NUM
cjfa-8193	253	64	mean	mean	NOUN
cjfa-8193	253	65	and	and	CCONJ
cjfa-8193	253	66	unit	unit	NOUN
cjfa-8193	253	67	variance	variance	NOUN
cjfa-8193	253	68	)	)	PUNCT
cjfa-8193	253	69	skewed	skewed	ADJ
cjfa-8193	253	70	-	-	PUNCT
cjfa-8193	253	71	student	student	NOUN
cjfa-8193	253	72	distribution	distribution	NOUN
cjfa-8193	253	73	]	]	PUNCT
cjfa-8193	253	74	4	4	NUM
cjfa-8193	253	75	[	[	NOUN
cjfa-8193	253	76	)	)	PUNCT
cjfa-8193	253	77	(	(	PUNCT
cjfa-8193	253	78	2	2	NUM
cjfa-8193	253	79	1	1	NUM
cjfa-8193	253	80	2	2	NUM
cjfa-8193	253	81	1	1	NUM
cjfa-8193	253	82	22	22	NUM
cjfa-8193	253	83	jt	jt	PROPN
cjfa-8193	253	84	p	p	PROPN
cjfa-8193	253	85	j	j	PROPN
cjfa-8193	253	86	jititi	jititi	PROPN
cjfa-8193	253	87	q	q	PROPN
cjfa-8193	254	1	i	i	PRON
cjfa-8193	254	2	itit	itit	VERB
cjfa-8193	254	3	s	s	PART
cjfa-8193	254	4			PROPN
cjfa-8193	254	5			PROPN
cjfa-8193	254	6			PROPN
cjfa-8193	254	7			PROPN
cjfa-8193	254	8			PROPN
cjfa-8193	254	9			PROPN
cjfa-8193	254	10			PROPN
cjfa-8193	254	11			PRON
cjfa-8193	254	12			VERB
cjfa-8193	254	13			PROPN
cjfa-8193	254	14	]	]	SYM
cjfa-8193	254	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	254	16	(	(	PUNCT
cjfa-8193	254	17	2	2	NUM
cjfa-8193	254	18	1	1	NUM
cjfa-8193	254	19	2	2	NUM
cjfa-8193	254	20	1	1	NUM
cjfa-8193	254	21	2	2	NUM
cjfa-8193	254	22	t	t	NOUN
cjfa-8193	254	23	t	t	NOUN
cjfa-8193	254	24	t	t	NOUN
cjfa-8193	254	25	tnorm	tnorm	NOUN
cjfa-8193	255	1	zl	zl	PROPN
cjfa-8193	256	1			PROPN
cjfa-8193	256	2			NUM
cjfa-8193	256	3			NUM
cjfa-8193	256	4			VERB
cjfa-8193	256	5			PROPN
cjfa-8193	256	6			PROPN
cjfa-8193	256	7	]	]	SYM
cjfa-8193	256	8	6	6	NUM
cjfa-8193	256	9	[	[	SYM
cjfa-8193	256	10	2	2	NUM
cjfa-8193	256	11	1log)1()log	1log)1()log	NUM
cjfa-8193	256	12	(	(	PUNCT
cjfa-8193	256	13	2	2	NUM
cjfa-8193	256	14	1	1	NUM
cjfa-8193	256	15	)	)	PUNCT
cjfa-8193	256	16	2(log	2(log	NOUN
cjfa-8193	256	17	2	2	NUM
cjfa-8193	256	18	1	1	NUM
cjfa-8193	256	19	2	2	NUM
cjfa-8193	256	20	log	log	NOUN
cjfa-8193	256	21	2	2	NUM
cjfa-8193	256	22	1log	1log	NUM
cjfa-8193	256	23	1	1	NUM
cjfa-8193	256	24	2	2	NUM
cjfa-8193	256	25	2	2	NUM
cjfa-8193	256	26			ADJ
cjfa-8193	256	27			PROPN
cjfa-8193	256	28			PROPN
cjfa-8193	256	29			PRON
cjfa-8193	256	30			NOUN
cjfa-8193	256	31			VERB
cjfa-8193	256	32			PROPN
cjfa-8193	256	33			NOUN
cjfa-8193	256	34			NOUN
cjfa-8193	256	35			PROPN
cjfa-8193	256	36			PROPN
cjfa-8193	256	37			PROPN
cjfa-8193	256	38			NOUN
cjfa-8193	256	39			PROPN
cjfa-8193	256	40			PROPN
cjfa-8193	256	41			PROPN
cjfa-8193	256	42			PROPN
cjfa-8193	257	1			PROPN
cjfa-8193	257	2			INTJ
cjfa-8193	257	3			NUM
cjfa-8193	257	4			ADV
cjfa-8193	257	5			VERB
cjfa-8193	257	6			NOUN
cjfa-8193	257	7			PRON
cjfa-8193	257	8			PROPN
cjfa-8193	257	9			PROPN
cjfa-8193	257	10			NOUN
cjfa-8193	257	11			NUM
cjfa-8193	257	12			PRON
cjfa-8193	257	13			PROPN
cjfa-8193	257	14			PROPN
cjfa-8193	257	15			NOUN
cjfa-8193	257	16			PUNCT
cjfa-8193	258	1	t	t	PROPN
cjfa-8193	258	2	t	t	PROPN
cjfa-8193	258	3	t	t	PROPN
cjfa-8193	258	4	t	t	PROPN
cjfa-8193	258	5	stud	stud	NOUN
cjfa-8193	258	6	v	v	ADP
cjfa-8193	258	7	z	z	PROPN
cjfa-8193	258	8	tl	tl	PROPN
cjfa-8193	258	9			PROPN
cjfa-8193	258	10			NOUN
cjfa-8193	258	11	]	]	PUNCT
cjfa-8193	258	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	258	13	1	1	NUM
cjfa-8193	258	14	21	21	NUM
cjfa-8193	258	15			PROPN
cjfa-8193	258	16			NOUN
cjfa-8193	258	17			NOUN
cjfa-8193	258	18			PROPN
cjfa-8193	258	19			PROPN
cjfa-8193	258	20			X
cjfa-8193	258	21			NOUN
cjfa-8193	258	22			NOUN
cjfa-8193	258	23			NOUN
cjfa-8193	259	1			PROPN
cjfa-8193	259	2			NOUN
cjfa-8193	259	3			NOUN
cjfa-8193	259	4			PRON
cjfa-8193	259	5			PROPN
cjfa-8193	260	1			PROPN
cjfa-8193	260	2			NOUN
cjfa-8193	260	3			NOUN
cjfa-8193	260	4			PROPN
cjfa-8193	260	5			PROPN
cjfa-8193	260	6			PROPN
cjfa-8193	260	7			NOUN
cjfa-8193	261	1			PROPN
cjfa-8193	261	2	t	t	PROPN
cjfa-8193	261	3	t	t	PROPN
cjfa-8193	261	4	t	t	PROPN
cjfa-8193	261	5	t	t	PROPN
cjfa-8193	261	6	ged	ge	VERB
cjfa-8193	261	7	zl	zl	PROPN
cjfa-8193	261	8			PROPN
cjfa-8193	261	9			ADJ
cjfa-8193	261	10			NOUN
cjfa-8193	261	11			NOUN
cjfa-8193	261	12			ADJ
cjfa-8193	261	13			ADJ
cjfa-8193	261	14			NOUN
cjfa-8193	261	15	[	[	X
cjfa-8193	261	16	6	6	NUM
cjfa-8193	261	17	]	]	PUNCT
cjfa-8193	261	18	(	(	PUNCT
cjfa-8193	261	19	vi	vi	NOUN
cjfa-8193	261	20	)	)	PUNCT
cjfa-8193	261	21	 	 	SPACE
cjfa-8193	261	22	generalized	generalize	VERB
cjfa-8193	261	23	error	error	NOUN
cjfa-8193	261	24	distribution	distribution	NOUN
cjfa-8193	261	25	(	(	PUNCT
cjfa-8193	261	26	ged	ge	VERB
cjfa-8193	261	27	)	)	PUNCT
cjfa-8193	261	28	where	where	SCONJ
cjfa-8193	261	29	the	the	DET
cjfa-8193	261	30	log	log	NOUN
cjfa-8193	261	31	-	-	PUNCT
cjfa-8193	261	32	likelihood	likelihood	NOUN
cjfa-8193	261	33	function	function	NOUN
cjfa-8193	261	34	of	of	ADP
cjfa-8193	261	35	the	the	DET
cjfa-8193	261	36	distribution	distribution	NOUN
cjfa-8193	261	37	is	be	AUX
cjfa-8193	261	38	:	:	PUNCT
cjfa-8193	261	39	[	[	X
cjfa-8193	261	40	7	7	X
cjfa-8193	261	41	]	]	PUNCT
cjfa-8193	261	42	this	this	DET
cjfa-8193	261	43	variation	variation	NOUN
cjfa-8193	261	44	on	on	ADP
cjfa-8193	261	45	the	the	DET
cjfa-8193	261	46	garch	garch	NOUN
cjfa-8193	261	47	model	model	NOUN
cjfa-8193	261	48	was	be	AUX
cjfa-8193	261	49	proposed	propose	VERB
cjfa-8193	261	50	by	by	ADP
cjfa-8193	261	51	glosten	glosten	ADJ
cjfa-8193	261	52	,	,	PUNCT
cjfa-8193	261	53	jagannathan	jagannathan	NOUN
cjfa-8193	261	54	,	,	PUNCT
cjfa-8193	261	55	and	and	CCONJ
cjfa-8193	261	56	runkle	runkle	ADJ
cjfa-8193	261	57	(	(	PUNCT
cjfa-8193	261	58	1993	1993	NUM
cjfa-8193	261	59	)	)	PUNCT
cjfa-8193	261	60	as	as	ADP
cjfa-8193	261	61	an	an	DET
cjfa-8193	261	62	alternative	alternative	ADJ
cjfa-8193	261	63	way	way	NOUN
cjfa-8193	261	64	of	of	ADP
cjfa-8193	261	65	dealing	deal	VERB
cjfa-8193	261	66	with	with	ADP
cjfa-8193	261	67	asymmetric	asymmetric	ADJ
cjfa-8193	261	68	shocks	shock	NOUN
cjfa-8193	261	69	in	in	ADP
cjfa-8193	261	70	financial	financial	ADJ
cjfa-8193	261	71	series	series	NOUN
cjfa-8193	261	72	.	.	PUNCT
cjfa-8193	262	1	its	its	PRON
cjfa-8193	262	2	generalized	generalized	ADJ
cjfa-8193	262	3	version	version	NOUN
cjfa-8193	262	4	is	be	AUX
cjfa-8193	262	5	:	:	PUNCT
cjfa-8193	262	6	where	where	SCONJ
cjfa-8193	262	7	�	�	PROPN
cjfa-8193	262	8	�	�	PROPN
cjfa-8193	262	9	�	�	PROPN
cjfa-8193	262	10	is	be	AUX
cjfa-8193	262	11	a	a	DET
cjfa-8193	262	12	dummy	dummy	ADJ
cjfa-8193	262	13	variable	variable	NOUN
cjfa-8193	262	14	that	that	PRON
cjfa-8193	262	15	take	take	VERB
cjfa-8193	262	16	the	the	DET
cjfa-8193	262	17	value	value	NOUN
cjfa-8193	262	18	1	1	NUM
cjfa-8193	262	19	when	when	SCONJ
cjfa-8193	262	20	�	�	PROPN
cjfa-8193	262	21	�	�	PROPN
cjfa-8193	262	22	�	�	PROPN
cjfa-8193	262	23	�	�	PROPN
cjfa-8193	262	24	<	<	X
cjfa-8193	262	25	0	0	NUM
cjfa-8193	262	26	,	,	PUNCT
cjfa-8193	262	27	and	and	CCONJ
cjfa-8193	262	28	0	0	NUM
cjfa-8193	262	29	when	when	SCONJ
cjfa-8193	262	30	�	�	PROPN
cjfa-8193	262	31	�	�	PROPN
cjfa-8193	262	32	�	�	PROPN
cjfa-8193	262	33	�	�	PROPN
cjfa-8193	262	34	≥	≥	NUM
cjfa-8193	262	35	0	0	NUM
cjfa-8193	262	36	.	.	PUNCT
cjfa-8193	263	1	a	a	DET
cjfa-8193	263	2	feature	feature	NOUN
cjfa-8193	263	3	of	of	ADP
cjfa-8193	263	4	the	the	DET
cjfa-8193	263	5	gjr	gjr	NOUN
cjfa-8193	263	6	model	model	NOUN
cjfa-8193	263	7	is	be	AUX
cjfa-8193	263	8	that	that	SCONJ
cjfa-8193	263	9	the	the	DET
cjfa-8193	263	10	null	null	ADJ
cjfa-8193	263	11	hypothesis	hypothesis	NOUN
cjfa-8193	263	12	of	of	ADP
cjfa-8193	263	13	no	no	DET
cjfa-8193	263	14	leverage	leverage	NOUN
cjfa-8193	263	15	(	(	PUNCT
cjfa-8193	263	16	asymmetry	asymmetry	NOUN
cjfa-8193	263	17	)	)	PUNCT
cjfa-8193	263	18	effect	effect	NOUN
cjfa-8193	263	19	is	be	AUX
cjfa-8193	263	20	simple	simple	ADJ
cjfa-8193	263	21	to	to	PART
cjfa-8193	263	22	test	test	VERB
cjfa-8193	263	23	.	.	PUNCT
cjfa-8193	264	1	indeed	indeed	ADV
cjfa-8193	264	2	,	,	PUNCT
cjfa-8193	264	3	γ1	γ1	PROPN
cjfa-8193	264	4	=	=	SYM
cjfa-8193	264	5	…	…	PUNCT
cjfa-8193	264	6	=	=	SYM
cjfa-8193	264	7	γq	γq	ADP
cjfa-8193	264	8	=	=	SYM
cjfa-8193	264	9	0	0	NUM
cjfa-8193	264	10	implies	imply	VERB
cjfa-8193	264	11	that	that	SCONJ
cjfa-8193	264	12	the	the	DET
cjfa-8193	264	13	impact	impact	NOUN
cjfa-8193	264	14	of	of	ADP
cjfa-8193	264	15	a	a	DET
cjfa-8193	264	16	shock	shock	NOUN
cjfa-8193	264	17	is	be	AUX
cjfa-8193	264	18	symmetric	symmetric	ADJ
cjfa-8193	264	19	,	,	PUNCT
cjfa-8193	264	20	i.e.	i.e.	X
cjfa-8193	264	21	,	,	PUNCT
cjfa-8193	264	22	past	past	ADP
cjfa-8193	264	23	positive	positive	ADJ
cjfa-8193	264	24	shocks	shock	NOUN
cjfa-8193	264	25	have	have	VERB
cjfa-8193	264	26	the	the	DET
cjfa-8193	264	27	same	same	ADJ
cjfa-8193	264	28	impact	impact	NOUN
cjfa-8193	264	29	on	on	ADP
cjfa-8193	264	30	today	today	NOUN
cjfa-8193	264	31	’s	’s	PART
cjfa-8193	264	32	volatility	volatility	NOUN
cjfa-8193	264	33	as	as	ADP
cjfa-8193	264	34	past	past	ADP
cjfa-8193	264	35	negative	negative	ADJ
cjfa-8193	264	36	shocks	shock	NOUN
cjfa-8193	264	37	.	.	PUNCT
cjfa-8193	265	1	they	they	PRON
cjfa-8193	265	2	do	do	AUX
cjfa-8193	265	3	have	have	VERB
cjfa-8193	265	4	a	a	DET
cjfa-8193	265	5	drawback	drawback	NOUN
cjfa-8193	265	6	in	in	ADP
cjfa-8193	265	7	that	that	SCONJ
cjfa-8193	265	8	they	they	PRON
cjfa-8193	265	9	are	be	AUX
cjfa-8193	265	10	symmetric	symmetric	ADJ
cjfa-8193	265	11	.	.	PUNCT
cjfa-8193	266	1	our	our	PRON
cjfa-8193	266	2	preferred	preferred	ADJ
cjfa-8193	266	3	option	option	NOUN
cjfa-8193	266	4	is	be	AUX
cjfa-8193	266	5	therefore	therefore	ADV
cjfa-8193	266	6	the	the	DET
cjfa-8193	266	7	skewed	skewed	ADJ
cjfa-8193	266	8	-	-	PUNCT
cjfa-8193	266	9	student	student	NOUN
cjfa-8193	266	10	density	density	NOUN
cjfa-8193	266	11	proposed	propose	VERB
cjfa-8193	266	12	by	by	ADP
cjfa-8193	266	13	fernández	fernández	PROPN
cjfa-8193	266	14	and	and	CCONJ
cjfa-8193	266	15	steel	steel	NOUN
cjfa-8193	266	16	(	(	PUNCT
cjfa-8193	266	17	1998	1998	NUM
cjfa-8193	266	18	)	)	PUNCT
cjfa-8193	266	19	.	.	PUNCT
cjfa-8193	267	1	(	(	PUNCT
cjfa-8193	267	2	iv	iv	X
cjfa-8193	267	3	)	)	PUNCT
cjfa-8193	267	4	gaussian	gaussian	NOUN
cjfa-8193	267	5	(	(	PUNCT
cjfa-8193	267	6	normal	normal	ADJ
cjfa-8193	267	7	)	)	PUNCT
cjfa-8193	267	8	distribution	distribution	NOUN
cjfa-8193	267	9	where	where	SCONJ
cjfa-8193	267	10	the	the	DET
cjfa-8193	267	11	log	log	NOUN
cjfa-8193	267	12	-	-	PUNCT
cjfa-8193	267	13	likelihood	likelihood	NOUN
cjfa-8193	267	14	function	function	NOUN
cjfa-8193	267	15	of	of	ADP
cjfa-8193	267	16	the	the	DET
cjfa-8193	267	17	distribution	distribution	NOUN
cjfa-8193	267	18	is	be	AUX
cjfa-8193	267	19	:	:	PUNCT
cjfa-8193	267	20	(	(	PUNCT
cjfa-8193	267	21	v	v	NOUN
cjfa-8193	267	22	)	)	PUNCT
cjfa-8193	267	23	student	student	NOUN
cjfa-8193	267	24	-	-	PUNCT
cjfa-8193	267	25	t	t	NOUN
cjfa-8193	267	26	distribution	distribution	NOUN
cjfa-8193	267	27	where	where	SCONJ
cjfa-8193	267	28	the	the	DET
cjfa-8193	267	29	log	log	NOUN
cjfa-8193	267	30	-	-	PUNCT
cjfa-8193	267	31	likelihood	likelihood	NOUN
cjfa-8193	267	32	function	function	NOUN
cjfa-8193	267	33	of	of	ADP
cjfa-8193	267	34	the	the	DET
cjfa-8193	267	35	distribution	distribution	NOUN
cjfa-8193	267	36	is	be	AUX
cjfa-8193	267	37	:	:	PUNCT
cjfa-8193	267	38	(	(	PUNCT
cjfa-8193	267	39	vi	vi	NOUN
cjfa-8193	267	40	)	)	PUNCT
cjfa-8193	267	41	generalized	generalize	VERB
cjfa-8193	267	42	error	error	NOUN
cjfa-8193	267	43	distribution	distribution	NOUN
cjfa-8193	267	44	(	(	PUNCT
cjfa-8193	267	45	ged	ge	VERB
cjfa-8193	267	46	)	)	PUNCT
cjfa-8193	267	47	where	where	SCONJ
cjfa-8193	267	48	the	the	DET
cjfa-8193	267	49	log	log	NOUN
cjfa-8193	267	50	-	-	PUNCT
cjfa-8193	267	51	likelihood	likelihood	NOUN
cjfa-8193	267	52	function	function	NOUN
cjfa-8193	267	53	of	of	ADP
cjfa-8193	267	54	the	the	DET
cjfa-8193	267	55	distribution	distribution	NOUN
cjfa-8193	267	56	is	be	AUX
cjfa-8193	267	57	:	:	PUNCT
cjfa-8193	267	58	(	(	PUNCT
cjfa-8193	267	59	vii	vii	PROPN
cjfa-8193	267	60	)	)	PUNCT
cjfa-8193	267	61	standardized	standardized	ADJ
cjfa-8193	267	62	(	(	PUNCT
cjfa-8193	267	63	zero	zero	NUM
cjfa-8193	267	64	mean	mean	NOUN
cjfa-8193	267	65	and	and	CCONJ
cjfa-8193	267	66	unit	unit	NOUN
cjfa-8193	267	67	variance	variance	NOUN
cjfa-8193	267	68	)	)	PUNCT
cjfa-8193	267	69	skewed	skewed	ADJ
cjfa-8193	267	70	-	-	PUNCT
cjfa-8193	267	71	student	student	NOUN
cjfa-8193	267	72	distribution	distribution	NOUN
cjfa-8193	267	73	]	]	PUNCT
cjfa-8193	267	74	4	4	NUM
cjfa-8193	267	75	[	[	NOUN
cjfa-8193	267	76	)	)	PUNCT
cjfa-8193	267	77	(	(	PUNCT
cjfa-8193	267	78	2	2	NUM
cjfa-8193	267	79	1	1	NUM
cjfa-8193	267	80	2	2	NUM
cjfa-8193	267	81	1	1	NUM
cjfa-8193	267	82	22	22	NUM
cjfa-8193	267	83	jt	jt	PROPN
cjfa-8193	267	84	p	p	PROPN
cjfa-8193	267	85	j	j	PROPN
cjfa-8193	267	86	jititi	jititi	PROPN
cjfa-8193	267	87	q	q	PROPN
cjfa-8193	268	1	i	i	PRON
cjfa-8193	268	2	itit	itit	VERB
cjfa-8193	268	3	s	s	PART
cjfa-8193	268	4			PROPN
cjfa-8193	268	5			PROPN
cjfa-8193	268	6			PROPN
cjfa-8193	268	7			PROPN
cjfa-8193	268	8			PROPN
cjfa-8193	268	9			PROPN
cjfa-8193	268	10			PROPN
cjfa-8193	268	11			PRON
cjfa-8193	268	12			VERB
cjfa-8193	268	13			PROPN
cjfa-8193	268	14	]	]	SYM
cjfa-8193	268	15	5[)log()2[log	5[)log()2[log	PROPN
cjfa-8193	268	16	(	(	PUNCT
cjfa-8193	268	17	2	2	NUM
cjfa-8193	268	18	1	1	NUM
cjfa-8193	268	19	2	2	NUM
cjfa-8193	268	20	1	1	NUM
cjfa-8193	268	21	2	2	NUM
cjfa-8193	268	22	t	t	NOUN
cjfa-8193	268	23	t	t	NOUN
cjfa-8193	268	24	t	t	NOUN
cjfa-8193	268	25	tnorm	tnorm	NOUN
cjfa-8193	269	1	zl	zl	PROPN
cjfa-8193	270	1			PROPN
cjfa-8193	270	2			NUM
cjfa-8193	270	3			NUM
cjfa-8193	270	4			VERB
cjfa-8193	270	5			PROPN
cjfa-8193	270	6			PROPN
cjfa-8193	270	7	]	]	SYM
cjfa-8193	270	8	6	6	NUM
cjfa-8193	270	9	[	[	SYM
cjfa-8193	270	10	2	2	NUM
cjfa-8193	270	11	1log)1()log	1log)1()log	NUM
cjfa-8193	270	12	(	(	PUNCT
cjfa-8193	270	13	2	2	NUM
cjfa-8193	270	14	1	1	NUM
cjfa-8193	270	15	)	)	PUNCT
cjfa-8193	270	16	2(log	2(log	NOUN
cjfa-8193	270	17	2	2	NUM
cjfa-8193	270	18	1	1	NUM
cjfa-8193	270	19	2	2	NUM
cjfa-8193	270	20	log	log	NOUN
cjfa-8193	270	21	2	2	NUM
cjfa-8193	270	22	1log	1log	NUM
cjfa-8193	270	23	1	1	NUM
cjfa-8193	270	24	2	2	NUM
cjfa-8193	270	25	2	2	NUM
cjfa-8193	270	26			ADJ
cjfa-8193	270	27			PROPN
cjfa-8193	270	28			PROPN
cjfa-8193	270	29			PRON
cjfa-8193	270	30			NOUN
cjfa-8193	270	31			VERB
cjfa-8193	270	32			PROPN
cjfa-8193	270	33			NOUN
cjfa-8193	270	34			NOUN
cjfa-8193	270	35			PROPN
cjfa-8193	270	36			PROPN
cjfa-8193	270	37			PROPN
cjfa-8193	270	38			NOUN
cjfa-8193	270	39			PROPN
cjfa-8193	270	40			PROPN
cjfa-8193	270	41			PROPN
cjfa-8193	270	42			PROPN
cjfa-8193	271	1			PROPN
cjfa-8193	271	2			INTJ
cjfa-8193	271	3			NUM
cjfa-8193	271	4			ADV
cjfa-8193	271	5			VERB
cjfa-8193	271	6			NOUN
cjfa-8193	271	7			PRON
cjfa-8193	271	8			PROPN
cjfa-8193	271	9			PROPN
cjfa-8193	271	10			NOUN
cjfa-8193	271	11			NUM
cjfa-8193	271	12			PRON
cjfa-8193	271	13			PROPN
cjfa-8193	271	14			PROPN
cjfa-8193	271	15			NOUN
cjfa-8193	271	16			PUNCT
cjfa-8193	272	1	t	t	PROPN
cjfa-8193	272	2	t	t	PROPN
cjfa-8193	272	3	t	t	PROPN
cjfa-8193	272	4	t	t	PROPN
cjfa-8193	272	5	stud	stud	NOUN
cjfa-8193	272	6	v	v	ADP
cjfa-8193	272	7	z	z	PROPN
cjfa-8193	272	8	tl	tl	PROPN
cjfa-8193	272	9			PROPN
cjfa-8193	272	10			NOUN
cjfa-8193	272	11	]	]	PUNCT
cjfa-8193	272	12	7[)log(5.01log)2log()1(5.0log	7[)log(5.01log)2log()1(5.0log	NOUN
cjfa-8193	272	13	1	1	NUM
cjfa-8193	272	14	21	21	NUM
cjfa-8193	272	15			PROPN
cjfa-8193	272	16			NOUN
cjfa-8193	272	17			NOUN
cjfa-8193	272	18			PROPN
cjfa-8193	272	19			PROPN
cjfa-8193	272	20			X
cjfa-8193	272	21			NOUN
cjfa-8193	272	22			NOUN
cjfa-8193	272	23			NOUN
cjfa-8193	273	1			PROPN
cjfa-8193	273	2			NOUN
cjfa-8193	273	3			NOUN
cjfa-8193	273	4			PRON
cjfa-8193	273	5			PROPN
cjfa-8193	274	1			PROPN
cjfa-8193	274	2			NOUN
cjfa-8193	274	3			NOUN
cjfa-8193	274	4			PROPN
cjfa-8193	274	5			PROPN
cjfa-8193	274	6			PROPN
cjfa-8193	274	7			NOUN
cjfa-8193	275	1			PROPN
cjfa-8193	275	2	t	t	PROPN
cjfa-8193	275	3	t	t	PROPN
cjfa-8193	275	4	t	t	PROPN
cjfa-8193	275	5	t	t	PROPN
cjfa-8193	275	6	ged	ge	VERB
cjfa-8193	275	7	zl	zl	PROPN
cjfa-8193	275	8			PROPN
cjfa-8193	275	9			ADJ
cjfa-8193	275	10			NOUN
cjfa-8193	275	11			NOUN
cjfa-8193	275	12			PROPN
cjfa-8193	275	13			NOUN
cjfa-8193	275	14			NOUN
cjfa-8193	275	15	h.	h.	PROPN
cjfa-8193	275	16	al	al	PROPN
cjfa-8193	275	17	-	-	PUNCT
cjfa-8193	275	18	hajieh	hajieh	PROPN
cjfa-8193	275	19	,	,	PUNCT
cjfa-8193	275	20	h.	h.	PROPN
cjfa-8193	275	21	alnemer	alnemer	PROPN
cjfa-8193	275	22	,	,	PUNCT
cjfa-8193	275	23	t.	t.	PROPN
cjfa-8193	275	24	rodgers	rodgers	PROPN
cjfa-8193	275	25	,	,	PUNCT
cjfa-8193	275	26	j.	j.	PROPN
cjfa-8193	275	27	niklewski18	niklewski18	PROPN
cjfa-8193	275	28	(	(	PUNCT
cjfa-8193	275	29	vii	vii	PROPN
cjfa-8193	275	30	)	)	PUNCT
cjfa-8193	275	31	 	 	SPACE
cjfa-8193	275	32	standardized	standardized	ADJ
cjfa-8193	275	33	(	(	PUNCT
cjfa-8193	275	34	zero	zero	NUM
cjfa-8193	275	35	mean	mean	NOUN
cjfa-8193	275	36	and	and	CCONJ
cjfa-8193	275	37	unit	unit	NOUN
cjfa-8193	275	38	variance	variance	NOUN
cjfa-8193	275	39	)	)	PUNCT
cjfa-8193	275	40	skewed	skewed	ADJ
cjfa-8193	275	41	-	-	PUNCT
cjfa-8193	275	42	student	student	NOUN
cjfa-8193	275	43	distribution	distribution	NOUN
cjfa-8193	275	44	where	where	SCONJ
cjfa-8193	275	45	the	the	DET
cjfa-8193	275	46	log	log	NOUN
cjfa-8193	275	47	-	-	PUNCT
cjfa-8193	275	48	likelihood	likelihood	NOUN
cjfa-8193	275	49	function	function	NOUN
cjfa-8193	275	50	of	of	ADP
cjfa-8193	275	51	the	the	DET
cjfa-8193	275	52	distribution	distribution	NOUN
cjfa-8193	275	53	is	be	AUX
cjfa-8193	275	54	:	:	PUNCT
cjfa-8193	275	55	where	where	SCONJ
cjfa-8193	275	56	the	the	DET
cjfa-8193	275	57	log	log	NOUN
cjfa-8193	275	58	-	-	PUNCT
cjfa-8193	275	59	likelihood	likelihood	NOUN
cjfa-8193	275	60	function	function	NOUN
cjfa-8193	275	61	of	of	ADP
cjfa-8193	275	62	the	the	DET
cjfa-8193	275	63	distribution	distribution	NOUN
cjfa-8193	275	64	is	be	AUX
cjfa-8193	275	65	:	:	PUNCT
cjfa-8193	275	66	results	result	NOUN
cjfa-8193	275	67	:	:	PUNCT
cjfa-8193	275	68	model	model	NOUN
cjfa-8193	275	69	evalutation	evalutation	NOUN
cjfa-8193	275	70	we	we	PRON
cjfa-8193	275	71	evaluate	evaluate	VERB
cjfa-8193	275	72	the	the	DET
cjfa-8193	275	73	alternative	alternative	ADJ
cjfa-8193	275	74	models	model	NOUN
cjfa-8193	275	75	by	by	ADP
cjfa-8193	275	76	(	(	PUNCT
cjfa-8193	275	77	i	i	NOUN
cjfa-8193	275	78	)	)	PUNCT
cjfa-8193	275	79	an	an	DET
cjfa-8193	275	80	assessment	assessment	NOUN
cjfa-8193	275	81	of	of	ADP
cjfa-8193	275	82	the	the	DET
cjfa-8193	275	83	parameters	parameter	NOUN
cjfa-8193	275	84	associated	associate	VERB
cjfa-8193	275	85	with	with	ADP
cjfa-8193	275	86	each	each	DET
cjfa-8193	275	87	model	model	NOUN
cjfa-8193	275	88	set	set	NOUN
cjfa-8193	275	89	(	(	PUNCT
cjfa-8193	275	90	ii	ii	NOUN
cjfa-8193	275	91	)	)	PUNCT
cjfa-8193	275	92	an	an	DET
cjfa-8193	275	93	evaluation	evaluation	NOUN
cjfa-8193	275	94	of	of	ADP
cjfa-8193	275	95	each	each	DET
cjfa-8193	275	96	model	model	NOUN
cjfa-8193	275	97	set	set	PROPN
cjfa-8193	275	98	’s	’s	PART
cjfa-8193	275	99	forecasting	forecasting	NOUN
cjfa-8193	275	100	performance	performance	NOUN
cjfa-8193	275	101	.	.	PUNCT
cjfa-8193	276	1	(	(	PUNCT
cjfa-8193	276	2	i	i	NOUN
cjfa-8193	276	3	)	)	PUNCT
cjfa-8193	276	4	parameter	parameter	NOUN
cjfa-8193	276	5	based	base	VERB
cjfa-8193	276	6	evaluation	evaluation	NOUN
cjfa-8193	276	7	tables	table	NOUN
cjfa-8193	276	8	2	2	NUM
cjfa-8193	276	9	,	,	PUNCT
cjfa-8193	276	10	3	3	NUM
cjfa-8193	276	11	and	and	CCONJ
cjfa-8193	276	12	4	4	NUM
cjfa-8193	276	13	,	,	PUNCT
cjfa-8193	276	14	present	present	VERB
cjfa-8193	276	15	the	the	DET
cjfa-8193	276	16	parameter	parameter	NOUN
cjfa-8193	276	17	values	value	NOUN
cjfa-8193	276	18	and	and	CCONJ
cjfa-8193	276	19	associated	associate	VERB
cjfa-8193	276	20	significance	significance	NOUN
cjfa-8193	276	21	tests	test	NOUN
cjfa-8193	276	22	for	for	ADP
cjfa-8193	276	23	the	the	DET
cjfa-8193	276	24	garch	garch	NOUN
cjfa-8193	276	25	,	,	PUNCT
cjfa-8193	276	26	egarch	egarch	NOUN
cjfa-8193	276	27	and	and	CCONJ
cjfa-8193	276	28	gjr	gjr	NOUN
cjfa-8193	276	29	-	-	PUNCT
cjfa-8193	276	30	garch	garch	NOUN
cjfa-8193	276	31	specified	specify	VERB
cjfa-8193	276	32	model	model	NOUN
cjfa-8193	276	33	sets	set	NOUN
cjfa-8193	276	34	.	.	PUNCT
cjfa-8193	277	1	for	for	ADP
cjfa-8193	277	2	the	the	DET
cjfa-8193	277	3	first	first	ADJ
cjfa-8193	277	4	and	and	CCONJ
cjfa-8193	277	5	third	third	ADJ
cjfa-8193	277	6	model	model	NOUN
cjfa-8193	277	7	sets	set	VERB
cjfa-8193	277	8	the	the	DET
cjfa-8193	277	9	constants	constant	NOUN
cjfa-8193	277	10	in	in	ADP
cjfa-8193	277	11	the	the	DET
cjfa-8193	277	12	mean	mean	ADJ
cjfa-8193	277	13	equations	equation	NOUN
cjfa-8193	277	14	and	and	CCONJ
cjfa-8193	277	15	the	the	DET
cjfa-8193	277	16	variance	variance	NOUN
cjfa-8193	277	17	parameters	parameter	NOUN
cjfa-8193	277	18	are	be	AUX
cjfa-8193	277	19	positive	positive	ADJ
cjfa-8193	277	20	and	and	CCONJ
cjfa-8193	277	21	statistically	statistically	ADV
cjfa-8193	277	22	significant	significant	ADJ
cjfa-8193	277	23	for	for	ADP
cjfa-8193	277	24	all	all	DET
cjfa-8193	277	25	distributions	distribution	NOUN
cjfa-8193	277	26	.	.	PUNCT
cjfa-8193	278	1	for	for	ADP
cjfa-8193	278	2	the	the	DET
cjfa-8193	278	3	egarch	egarch	NOUN
cjfa-8193	278	4	model	model	NOUN
cjfa-8193	278	5	set	set	VERB
cjfa-8193	278	6	the	the	DET
cjfa-8193	278	7	constants	constant	NOUN
cjfa-8193	278	8	for	for	ADP
cjfa-8193	278	9	the	the	DET
cjfa-8193	278	10	mean	mean	ADJ
cjfa-8193	278	11	equations	equation	NOUN
cjfa-8193	278	12	are	be	AUX
cjfa-8193	278	13	not	not	PART
cjfa-8193	278	14	statistically	statistically	ADV
cjfa-8193	278	15	significant	significant	ADJ
cjfa-8193	278	16	.	.	PUNCT
cjfa-8193	279	1	the	the	DET
cjfa-8193	279	2	alpha	alpha	ADJ
cjfa-8193	279	3	coefficient	coefficient	NOUN
cjfa-8193	279	4	for	for	ADP
cjfa-8193	279	5	all	all	DET
cjfa-8193	279	6	models	model	NOUN
cjfa-8193	279	7	and	and	CCONJ
cjfa-8193	279	8	distributions	distribution	NOUN
cjfa-8193	279	9	is	be	AUX
cjfa-8193	279	10	statistically	statistically	ADV
cjfa-8193	279	11	significant	significant	ADJ
cjfa-8193	279	12	at	at	ADP
cjfa-8193	279	13	the	the	DET
cjfa-8193	279	14	99	99	NUM
cjfa-8193	279	15	%	%	NOUN
cjfa-8193	279	16	level	level	NOUN
cjfa-8193	279	17	of	of	ADP
cjfa-8193	279	18	confidence	confidence	NOUN
cjfa-8193	279	19	.	.	PUNCT
cjfa-8193	280	1	this	this	PRON
cjfa-8193	280	2	implies	imply	VERB
cjfa-8193	280	3	the	the	DET
cjfa-8193	280	4	existence	existence	NOUN
cjfa-8193	280	5	of	of	ADP
cjfa-8193	280	6	the	the	DET
cjfa-8193	280	7	arch	arch	ADJ
cjfa-8193	280	8	process	process	NOUN
cjfa-8193	280	9	in	in	ADP
cjfa-8193	280	10	the	the	DET
cjfa-8193	280	11	residuals	residual	NOUN
cjfa-8193	280	12	term	term	NOUN
cjfa-8193	280	13	.	.	PUNCT
cjfa-8193	281	1	the	the	DET
cjfa-8193	281	2	returns	return	NOUN
cjfa-8193	281	3	exhibit	exhibit	VERB
cjfa-8193	281	4	time	time	NOUN
cjfa-8193	281	5	-	-	PUNCT
cjfa-8193	281	6	varying	vary	VERB
cjfa-8193	281	7	volatility	volatility	NOUN
cjfa-8193	281	8	clustering	clustering	NOUN
cjfa-8193	281	9	;	;	PUNCT
cjfa-8193	281	10	this	this	PRON
cjfa-8193	281	11	indicates	indicate	VERB
cjfa-8193	281	12	that	that	SCONJ
cjfa-8193	281	13	periods	period	NOUN
cjfa-8193	281	14	of	of	ADP
cjfa-8193	281	15	volatility	volatility	NOUN
cjfa-8193	281	16	are	be	AUX
cjfa-8193	281	17	followed	follow	VERB
cjfa-8193	281	18	by	by	ADP
cjfa-8193	281	19	periods	period	NOUN
cjfa-8193	281	20	of	of	ADP
cjfa-8193	281	21	relative	relative	ADJ
cjfa-8193	281	22	calm	calm	NOUN
cjfa-8193	281	23	.	.	PUNCT
cjfa-8193	282	1	the	the	DET
cjfa-8193	282	2	beta	beta	ADJ
cjfa-8193	282	3	coefficients	coefficient	NOUN
cjfa-8193	282	4	of	of	ADP
cjfa-8193	282	5	the	the	DET
cjfa-8193	282	6	three	three	NUM
cjfa-8193	282	7	models	model	NOUN
cjfa-8193	282	8	in	in	ADP
cjfa-8193	282	9	all	all	DET
cjfa-8193	282	10	distribution	distribution	NOUN
cjfa-8193	282	11	are	be	AUX
cjfa-8193	282	12	also	also	ADV
cjfa-8193	282	13	statistically	statistically	ADV
cjfa-8193	282	14	significant	significant	ADJ
cjfa-8193	282	15	at	at	ADP
cjfa-8193	282	16	the	the	DET
cjfa-8193	282	17	99	99	NUM
cjfa-8193	282	18	%	%	NOUN
cjfa-8193	282	19	level	level	NOUN
cjfa-8193	282	20	of	of	ADP
cjfa-8193	282	21	confidence	confidence	NOUN
cjfa-8193	282	22	.	.	PUNCT
cjfa-8193	283	1	this	this	PRON
cjfa-8193	283	2	indicates	indicate	VERB
cjfa-8193	283	3	that	that	SCONJ
cjfa-8193	283	4	the	the	DET
cjfa-8193	283	5	variance	variance	NOUN
cjfa-8193	283	6	is	be	AUX
cjfa-8193	283	7	dependent	dependent	ADJ
cjfa-8193	283	8	on	on	ADP
cjfa-8193	283	9	its	its	PRON
cjfa-8193	283	10	moving	move	VERB
cjfa-8193	283	11	average	average	NOUN
cjfa-8193	283	12	.	.	PUNCT
cjfa-8193	284	1	in	in	ADP
cjfa-8193	284	2	a	a	DET
cjfa-8193	284	3	subset	subset	NOUN
cjfa-8193	284	4	of	of	ADP
cjfa-8193	284	5	the	the	DET
cjfa-8193	284	6	models	model	NOUN
cjfa-8193	284	7	the	the	DET
cjfa-8193	284	8	sum	sum	NOUN
cjfa-8193	284	9	of	of	ADP
cjfa-8193	284	10	alpha	alpha	NOUN
cjfa-8193	284	11	and	and	CCONJ
cjfa-8193	284	12	beta	beta	NOUN
cjfa-8193	284	13	is	be	AUX
cjfa-8193	284	14	close	close	ADJ
cjfa-8193	284	15	to	to	ADP
cjfa-8193	284	16	unity	unity	NOUN
cjfa-8193	284	17	,	,	PUNCT
cjfa-8193	284	18	which	which	PRON
cjfa-8193	284	19	implies	imply	VERB
cjfa-8193	284	20	in	in	ADP
cjfa-8193	284	21	these	these	DET
cjfa-8193	284	22	cases	case	NOUN
cjfa-8193	284	23	that	that	SCONJ
cjfa-8193	284	24	volatility	volatility	NOUN
cjfa-8193	284	25	shocks	shock	NOUN
cjfa-8193	284	26	are	be	AUX
cjfa-8193	284	27	quite	quite	ADV
cjfa-8193	284	28	persistent	persistent	ADJ
cjfa-8193	284	29	and	and	CCONJ
cjfa-8193	284	30	suggests	suggest	VERB
cjfa-8193	284	31	that	that	SCONJ
cjfa-8193	284	32	a	a	DET
cjfa-8193	284	33	large	large	ADJ
cjfa-8193	284	34	positive	positive	ADJ
cjfa-8193	284	35	(	(	PUNCT
cjfa-8193	284	36	or	or	CCONJ
cjfa-8193	284	37	negative	negative	ADJ
cjfa-8193	284	38	)	)	PUNCT
cjfa-8193	284	39	return	return	NOUN
cjfa-8193	284	40	will	will	AUX
cjfa-8193	284	41	lead	lead	VERB
cjfa-8193	284	42	future	future	ADJ
cjfa-8193	284	43	forecasts	forecast	NOUN
cjfa-8193	284	44	of	of	ADP
cjfa-8193	284	45	the	the	DET
cjfa-8193	284	46	variance	variance	NOUN
cjfa-8193	284	47	to	to	PART
cjfa-8193	284	48	be	be	AUX
cjfa-8193	284	49	high	high	ADJ
cjfa-8193	284	50	for	for	ADP
cjfa-8193	284	51	an	an	DET
cjfa-8193	284	52	extended	extended	ADJ
cjfa-8193	284	53	period	period	NOUN
cjfa-8193	284	54	.	.	PUNCT
cjfa-8193	285	1	the	the	DET
cjfa-8193	285	2	garch	garch	NOUN
cjfa-8193	285	3	coefficient	coefficient	NOUN
cjfa-8193	285	4	(	(	PUNCT
cjfa-8193	285	5	beta	beta	NOUN
cjfa-8193	285	6	)	)	PUNCT
cjfa-8193	285	7	is	be	AUX
cjfa-8193	285	8	larger	large	ADJ
cjfa-8193	285	9	than	than	ADP
cjfa-8193	285	10	the	the	DET
cjfa-8193	285	11	arch	arch	ADJ
cjfa-8193	285	12	term	term	NOUN
cjfa-8193	285	13	(	(	PUNCT
cjfa-8193	285	14	alpha	alpha	NOUN
cjfa-8193	285	15	)	)	PUNCT
cjfa-8193	285	16	in	in	ADP
cjfa-8193	285	17	all	all	DET
cjfa-8193	285	18	three	three	NUM
cjfa-8193	285	19	model	model	NOUN
cjfa-8193	285	20	sets	set	NOUN
cjfa-8193	285	21	.	.	PUNCT
cjfa-8193	286	1	this	this	PRON
cjfa-8193	286	2	is	be	AUX
cjfa-8193	286	3	a	a	DET
cjfa-8193	286	4	further	further	ADJ
cjfa-8193	286	5	indication	indication	NOUN
cjfa-8193	286	6	that	that	SCONJ
cjfa-8193	286	7	the	the	DET
cjfa-8193	286	8	conditional	conditional	ADJ
cjfa-8193	286	9	variance	variance	NOUN
cjfa-8193	286	10	will	will	AUX
cjfa-8193	286	11	exhibit	exhibit	VERB
cjfa-8193	286	12	long	long	ADJ
cjfa-8193	286	13	persistence	persistence	NOUN
cjfa-8193	286	14	of	of	ADP
cjfa-8193	286	15	volatility	volatility	NOUN
cjfa-8193	286	16	.	.	PUNCT
cjfa-8193	287	1			ADJ
cjfa-8193	287	2			X
cjfa-8193	287	3	]	]	SYM
cjfa-8193	287	4	8	8	NUM
cjfa-8193	287	5	[	[	SYM
cjfa-8193	287	6	2	2	NUM
cjfa-8193	287	7	)	)	PUNCT
cjfa-8193	287	8	(	(	PUNCT
cjfa-8193	287	9	1log)1(log5.0	1log)1(log5.0	NUM
cjfa-8193	287	10	)	)	PUNCT
cjfa-8193	287	11	log(1	log(1	NOUN
cjfa-8193	287	12	2log)2(log5.0	2log)2(log5.0	NUM
cjfa-8193	287	13	2	2	NUM
cjfa-8193	287	14	log	log	NOUN
cjfa-8193	287	15	2	2	NUM
cjfa-8193	287	16	1log	1log	NUM
cjfa-8193	287	17	1	1	NUM
cjfa-8193	287	18	2	2	NUM
cjfa-8193	287	19	2	2	NUM
cjfa-8193	287	20	2	2	NUM
cjfa-8193	288	1			NUM
cjfa-8193	288	2			NOUN
cjfa-8193	288	3			PROPN
cjfa-8193	288	4			PROPN
cjfa-8193	289	1			PROPN
cjfa-8193	289	2			INTJ
cjfa-8193	289	3			NUM
cjfa-8193	289	4			ADP
cjfa-8193	290	1			PROPN
cjfa-8193	290	2			PROPN
cjfa-8193	290	3			PRON
cjfa-8193	290	4			NOUN
cjfa-8193	290	5			VERB
cjfa-8193	290	6			PROPN
cjfa-8193	290	7			PROPN
cjfa-8193	290	8			NOUN
cjfa-8193	290	9			ADP
cjfa-8193	290	10			NUM
cjfa-8193	290	11			NOUN
cjfa-8193	290	12			NOUN
cjfa-8193	291	1			INTJ
cjfa-8193	292	1			NUM
cjfa-8193	292	2			NUM
cjfa-8193	292	3			PRON
cjfa-8193	292	4			NUM
cjfa-8193	292	5			NOUN
cjfa-8193	293	1			NOUN
cjfa-8193	293	2			ADP
cjfa-8193	293	3			PROPN
cjfa-8193	293	4			PROPN
cjfa-8193	294	1			PROPN
cjfa-8193	294	2			PROPN
cjfa-8193	295	1			PROPN
cjfa-8193	295	2			NOUN
cjfa-8193	296	1			PROPN
cjfa-8193	297	1			PROPN
cjfa-8193	298	1			PROPN
cjfa-8193	299	1			PROPN
cjfa-8193	299	2			PROPN
cjfa-8193	300	1			PROPN
cjfa-8193	300	2			NOUN
cjfa-8193	300	3			VERB
cjfa-8193	300	4			PUNCT
cjfa-8193	300	5			NOUN
cjfa-8193	300	6			PRON
cjfa-8193	300	7			PROPN
cjfa-8193	300	8			PROPN
cjfa-8193	300	9			NOUN
cjfa-8193	300	10			NUM
cjfa-8193	300	11			PRON
cjfa-8193	300	12			PROPN
cjfa-8193	300	13			PROPN
cjfa-8193	300	14			NOUN
cjfa-8193	300	15			PUNCT
cjfa-8193	301	1	t	t	PROPN
cjfa-8193	301	2	t	t	X
cjfa-8193	301	3	it	it	PRON
cjfa-8193	301	4	t	t	PROPN
cjfa-8193	301	5	skst	skst	NOUN
cjfa-8193	301	6	t	t	PROPN
cjfa-8193	301	7	msz	msz	VERB
cjfa-8193	301	8	svtl	svtl	NOUN
cjfa-8193	301	9			NOUN
cjfa-8193	301	10			PRON
cjfa-8193	301	11			NOUN
cjfa-8193	301	12			VERB
cjfa-8193	301	13			NOUN
cjfa-8193	301	14			NOUN
cjfa-8193	301	15	where	where	SCONJ
cjfa-8193	301	16	the	the	DET
cjfa-8193	301	17	log	log	NOUN
cjfa-8193	301	18	-	-	PUNCT
cjfa-8193	301	19	likelihood	likelihood	NOUN
cjfa-8193	301	20	function	function	NOUN
cjfa-8193	301	21	of	of	ADP
cjfa-8193	301	22	the	the	DET
cjfa-8193	301	23	distribution	distribution	NOUN
cjfa-8193	301	24	is	be	AUX
cjfa-8193	301	25	:	:	PUNCT
cjfa-8193	301	26	results	result	NOUN
cjfa-8193	301	27	:	:	PUNCT
cjfa-8193	301	28	model	model	NOUN
cjfa-8193	301	29	evalutation	evalutation	NOUN
cjfa-8193	301	30	we	we	PRON
cjfa-8193	301	31	evaluate	evaluate	VERB
cjfa-8193	301	32	the	the	DET
cjfa-8193	301	33	alternative	alternative	ADJ
cjfa-8193	301	34	models	model	NOUN
cjfa-8193	301	35	by	by	ADP
cjfa-8193	301	36	(	(	PUNCT
cjfa-8193	301	37	i	i	NOUN
cjfa-8193	301	38	)	)	PUNCT
cjfa-8193	301	39	an	an	DET
cjfa-8193	301	40	assessment	assessment	NOUN
cjfa-8193	301	41	of	of	ADP
cjfa-8193	301	42	the	the	DET
cjfa-8193	301	43	parameters	parameter	NOUN
cjfa-8193	301	44	associated	associate	VERB
cjfa-8193	301	45	with	with	ADP
cjfa-8193	301	46	each	each	DET
cjfa-8193	301	47	model	model	NOUN
cjfa-8193	301	48	set	set	NOUN
cjfa-8193	301	49	(	(	PUNCT
cjfa-8193	301	50	ii	ii	NOUN
cjfa-8193	301	51	)	)	PUNCT
cjfa-8193	301	52	an	an	DET
cjfa-8193	301	53	evaluation	evaluation	NOUN
cjfa-8193	301	54	of	of	ADP
cjfa-8193	301	55	each	each	DET
cjfa-8193	301	56	model	model	NOUN
cjfa-8193	301	57	set	set	PROPN
cjfa-8193	301	58	’s	’s	PART
cjfa-8193	301	59	forecasting	forecasting	NOUN
cjfa-8193	301	60	performance	performance	NOUN
cjfa-8193	301	61	.	.	PUNCT
cjfa-8193	302	1	(	(	PUNCT
cjfa-8193	302	2	i	i	NOUN
cjfa-8193	302	3	)	)	PUNCT
cjfa-8193	302	4	parameter	parameter	NOUN
cjfa-8193	302	5	based	base	VERB
cjfa-8193	302	6	evaluation	evaluation	NOUN
cjfa-8193	302	7	tables	table	NOUN
cjfa-8193	302	8	2	2	NUM
cjfa-8193	302	9	,	,	PUNCT
cjfa-8193	302	10	3	3	NUM
cjfa-8193	302	11	and	and	CCONJ
cjfa-8193	302	12	4	4	NUM
cjfa-8193	302	13	,	,	PUNCT
cjfa-8193	302	14	present	present	VERB
cjfa-8193	302	15	the	the	DET
cjfa-8193	302	16	parameter	parameter	NOUN
cjfa-8193	302	17	values	value	NOUN
cjfa-8193	302	18	and	and	CCONJ
cjfa-8193	302	19	associated	associate	VERB
cjfa-8193	302	20	significance	significance	NOUN
cjfa-8193	302	21	tests	test	NOUN
cjfa-8193	302	22	for	for	ADP
cjfa-8193	302	23	the	the	DET
cjfa-8193	302	24	garch	garch	NOUN
cjfa-8193	302	25	,	,	PUNCT
cjfa-8193	302	26	egarch	egarch	NOUN
cjfa-8193	302	27	and	and	CCONJ
cjfa-8193	302	28	gjr	gjr	NOUN
cjfa-8193	302	29	-	-	PUNCT
cjfa-8193	302	30	garch	garch	NOUN
cjfa-8193	302	31	specified	specify	VERB
cjfa-8193	302	32	model	model	NOUN
cjfa-8193	302	33	sets	set	NOUN
cjfa-8193	302	34	.	.	PUNCT
cjfa-8193	303	1	for	for	ADP
cjfa-8193	303	2	the	the	DET
cjfa-8193	303	3	first	first	ADJ
cjfa-8193	303	4	and	and	CCONJ
cjfa-8193	303	5	third	third	ADJ
cjfa-8193	303	6	model	model	NOUN
cjfa-8193	303	7	sets	set	VERB
cjfa-8193	303	8	the	the	DET
cjfa-8193	303	9	constants	constant	NOUN
cjfa-8193	303	10	in	in	ADP
cjfa-8193	303	11	the	the	DET
cjfa-8193	303	12	mean	mean	ADJ
cjfa-8193	303	13	equations	equation	NOUN
cjfa-8193	303	14	and	and	CCONJ
cjfa-8193	303	15	the	the	DET
cjfa-8193	303	16	variance	variance	NOUN
cjfa-8193	303	17	parameters	parameter	NOUN
cjfa-8193	303	18	are	be	AUX
cjfa-8193	303	19	positive	positive	ADJ
cjfa-8193	303	20	and	and	CCONJ
cjfa-8193	303	21	statistically	statistically	ADV
cjfa-8193	303	22	significant	significant	ADJ
cjfa-8193	303	23	for	for	ADP
cjfa-8193	303	24	all	all	DET
cjfa-8193	303	25	distributions	distribution	NOUN
cjfa-8193	303	26	.	.	PUNCT
cjfa-8193	304	1	for	for	ADP
cjfa-8193	304	2	the	the	DET
cjfa-8193	304	3	egarch	egarch	NOUN
cjfa-8193	304	4	model	model	NOUN
cjfa-8193	304	5	set	set	VERB
cjfa-8193	304	6	the	the	DET
cjfa-8193	304	7	constants	constant	NOUN
cjfa-8193	304	8	for	for	ADP
cjfa-8193	304	9	the	the	DET
cjfa-8193	304	10	mean	mean	ADJ
cjfa-8193	304	11	equations	equation	NOUN
cjfa-8193	304	12	are	be	AUX
cjfa-8193	304	13	not	not	PART
cjfa-8193	304	14	statistically	statistically	ADV
cjfa-8193	304	15	significant	significant	ADJ
cjfa-8193	304	16	.	.	PUNCT
cjfa-8193	305	1	the	the	DET
cjfa-8193	305	2	alpha	alpha	ADJ
cjfa-8193	305	3	coefficient	coefficient	NOUN
cjfa-8193	305	4	for	for	ADP
cjfa-8193	305	5	all	all	DET
cjfa-8193	305	6	models	model	NOUN
cjfa-8193	305	7	and	and	CCONJ
cjfa-8193	305	8	distributions	distribution	NOUN
cjfa-8193	305	9	is	be	AUX
cjfa-8193	305	10	statistically	statistically	ADV
cjfa-8193	305	11	significant	significant	ADJ
cjfa-8193	305	12	at	at	ADP
cjfa-8193	305	13	the	the	DET
cjfa-8193	305	14	99	99	NUM
cjfa-8193	305	15	%	%	NOUN
cjfa-8193	305	16	level	level	NOUN
cjfa-8193	305	17	of	of	ADP
cjfa-8193	305	18	confidence	confidence	NOUN
cjfa-8193	305	19	.	.	PUNCT
cjfa-8193	306	1	this	this	PRON
cjfa-8193	306	2	implies	imply	VERB
cjfa-8193	306	3	the	the	DET
cjfa-8193	306	4	existence	existence	NOUN
cjfa-8193	306	5	of	of	ADP
cjfa-8193	306	6	the	the	DET
cjfa-8193	306	7	arch	arch	ADJ
cjfa-8193	306	8	process	process	NOUN
cjfa-8193	306	9	in	in	ADP
cjfa-8193	306	10	the	the	DET
cjfa-8193	306	11	residuals	residual	NOUN
cjfa-8193	306	12	term	term	NOUN
cjfa-8193	306	13	.	.	PUNCT
cjfa-8193	307	1	the	the	DET
cjfa-8193	307	2	returns	return	NOUN
cjfa-8193	307	3	exhibit	exhibit	VERB
cjfa-8193	307	4	time	time	NOUN
cjfa-8193	307	5	-	-	PUNCT
cjfa-8193	307	6	varying	vary	VERB
cjfa-8193	307	7	volatility	volatility	NOUN
cjfa-8193	307	8	clustering	clustering	NOUN
cjfa-8193	307	9	;	;	PUNCT
cjfa-8193	307	10	this	this	PRON
cjfa-8193	307	11	indicates	indicate	VERB
cjfa-8193	307	12	that	that	SCONJ
cjfa-8193	307	13	periods	period	NOUN
cjfa-8193	307	14	of	of	ADP
cjfa-8193	307	15	volatility	volatility	NOUN
cjfa-8193	307	16	are	be	AUX
cjfa-8193	307	17	followed	follow	VERB
cjfa-8193	307	18	by	by	ADP
cjfa-8193	307	19	periods	period	NOUN
cjfa-8193	307	20	of	of	ADP
cjfa-8193	307	21	relative	relative	ADJ
cjfa-8193	307	22	calm	calm	NOUN
cjfa-8193	307	23	.	.	PUNCT
cjfa-8193	308	1	the	the	DET
cjfa-8193	308	2	beta	beta	ADJ
cjfa-8193	308	3	coefficients	coefficient	NOUN
cjfa-8193	308	4	of	of	ADP
cjfa-8193	308	5	the	the	DET
cjfa-8193	308	6	three	three	NUM
cjfa-8193	308	7	models	model	NOUN
cjfa-8193	308	8	in	in	ADP
cjfa-8193	308	9	all	all	DET
cjfa-8193	308	10	distribution	distribution	NOUN
cjfa-8193	308	11	are	be	AUX
cjfa-8193	308	12	also	also	ADV
cjfa-8193	308	13	statistically	statistically	ADV
cjfa-8193	308	14	significant	significant	ADJ
cjfa-8193	308	15	at	at	ADP
cjfa-8193	308	16	the	the	DET
cjfa-8193	308	17	99	99	NUM
cjfa-8193	308	18	%	%	NOUN
cjfa-8193	308	19	level	level	NOUN
cjfa-8193	308	20	of	of	ADP
cjfa-8193	308	21	confidence	confidence	NOUN
cjfa-8193	308	22	.	.	PUNCT
cjfa-8193	309	1	this	this	PRON
cjfa-8193	309	2	indicates	indicate	VERB
cjfa-8193	309	3	that	that	SCONJ
cjfa-8193	309	4	the	the	DET
cjfa-8193	309	5	variance	variance	NOUN
cjfa-8193	309	6	is	be	AUX
cjfa-8193	309	7	dependent	dependent	ADJ
cjfa-8193	309	8	on	on	ADP
cjfa-8193	309	9	its	its	PRON
cjfa-8193	309	10	moving	move	VERB
cjfa-8193	309	11	average	average	NOUN
cjfa-8193	309	12	.	.	PUNCT
cjfa-8193	310	1	in	in	ADP
cjfa-8193	310	2	a	a	DET
cjfa-8193	310	3	subset	subset	NOUN
cjfa-8193	310	4	of	of	ADP
cjfa-8193	310	5	the	the	DET
cjfa-8193	310	6	models	model	NOUN
cjfa-8193	310	7	the	the	DET
cjfa-8193	310	8	sum	sum	NOUN
cjfa-8193	310	9	of	of	ADP
cjfa-8193	310	10	alpha	alpha	NOUN
cjfa-8193	310	11	and	and	CCONJ
cjfa-8193	310	12	beta	beta	NOUN
cjfa-8193	310	13	is	be	AUX
cjfa-8193	310	14	close	close	ADJ
cjfa-8193	310	15	to	to	ADP
cjfa-8193	310	16	unity	unity	NOUN
cjfa-8193	310	17	,	,	PUNCT
cjfa-8193	310	18	which	which	PRON
cjfa-8193	310	19	implies	imply	VERB
cjfa-8193	310	20	in	in	ADP
cjfa-8193	310	21	these	these	DET
cjfa-8193	310	22	cases	case	NOUN
cjfa-8193	310	23	that	that	SCONJ
cjfa-8193	310	24	volatility	volatility	NOUN
cjfa-8193	310	25	shocks	shock	NOUN
cjfa-8193	310	26	are	be	AUX
cjfa-8193	310	27	quite	quite	ADV
cjfa-8193	310	28	persistent	persistent	ADJ
cjfa-8193	310	29	and	and	CCONJ
cjfa-8193	310	30	suggests	suggest	VERB
cjfa-8193	310	31	that	that	SCONJ
cjfa-8193	310	32	a	a	DET
cjfa-8193	310	33	large	large	ADJ
cjfa-8193	310	34	positive	positive	ADJ
cjfa-8193	310	35	(	(	PUNCT
cjfa-8193	310	36	or	or	CCONJ
cjfa-8193	310	37	negative	negative	ADJ
cjfa-8193	310	38	)	)	PUNCT
cjfa-8193	310	39	return	return	NOUN
cjfa-8193	310	40	will	will	AUX
cjfa-8193	310	41	lead	lead	VERB
cjfa-8193	310	42	future	future	ADJ
cjfa-8193	310	43	forecasts	forecast	NOUN
cjfa-8193	310	44	of	of	ADP
cjfa-8193	310	45	the	the	DET
cjfa-8193	310	46	variance	variance	NOUN
cjfa-8193	310	47	to	to	PART
cjfa-8193	310	48	be	be	AUX
cjfa-8193	310	49	high	high	ADJ
cjfa-8193	310	50	for	for	ADP
cjfa-8193	310	51	an	an	DET
cjfa-8193	310	52	extended	extended	ADJ
cjfa-8193	310	53	period	period	NOUN
cjfa-8193	310	54	.	.	PUNCT
cjfa-8193	311	1	the	the	DET
cjfa-8193	311	2	garch	garch	NOUN
cjfa-8193	311	3	coefficient	coefficient	NOUN
cjfa-8193	311	4	(	(	PUNCT
cjfa-8193	311	5	beta	beta	NOUN
cjfa-8193	311	6	)	)	PUNCT
cjfa-8193	311	7	is	be	AUX
cjfa-8193	311	8	larger	large	ADJ
cjfa-8193	311	9	than	than	ADP
cjfa-8193	311	10	the	the	DET
cjfa-8193	311	11	arch	arch	ADJ
cjfa-8193	311	12	term	term	NOUN
cjfa-8193	311	13	(	(	PUNCT
cjfa-8193	311	14	alpha	alpha	NOUN
cjfa-8193	311	15	)	)	PUNCT
cjfa-8193	311	16	in	in	ADP
cjfa-8193	311	17	all	all	DET
cjfa-8193	311	18	three	three	NUM
cjfa-8193	311	19	model	model	NOUN
cjfa-8193	311	20	sets	set	NOUN
cjfa-8193	311	21	.	.	PUNCT
cjfa-8193	312	1	this	this	PRON
cjfa-8193	312	2	is	be	AUX
cjfa-8193	312	3	a	a	DET
cjfa-8193	312	4	further	further	ADJ
cjfa-8193	312	5	indication	indication	NOUN
cjfa-8193	312	6	that	that	SCONJ
cjfa-8193	312	7	the	the	DET
cjfa-8193	312	8	conditional	conditional	ADJ
cjfa-8193	312	9	variance	variance	NOUN
cjfa-8193	312	10	will	will	AUX
cjfa-8193	312	11	exhibit	exhibit	VERB
cjfa-8193	312	12	long	long	ADJ
cjfa-8193	312	13	persistence	persistence	NOUN
cjfa-8193	312	14	of	of	ADP
cjfa-8193	312	15	volatility	volatility	NOUN
cjfa-8193	312	16	.	.	PUNCT
cjfa-8193	313	1			ADJ
cjfa-8193	313	2			X
cjfa-8193	313	3	]	]	SYM
cjfa-8193	313	4	8	8	NUM
cjfa-8193	313	5	[	[	SYM
cjfa-8193	313	6	2	2	NUM
cjfa-8193	313	7	)	)	PUNCT
cjfa-8193	313	8	(	(	PUNCT
cjfa-8193	313	9	1log)1(log5.0	1log)1(log5.0	NUM
cjfa-8193	313	10	)	)	PUNCT
cjfa-8193	313	11	log(1	log(1	NOUN
cjfa-8193	313	12	2log)2(log5.0	2log)2(log5.0	NUM
cjfa-8193	313	13	2	2	NUM
cjfa-8193	313	14	log	log	NOUN
cjfa-8193	313	15	2	2	NUM
cjfa-8193	313	16	1log	1log	NUM
cjfa-8193	313	17	1	1	NUM
cjfa-8193	313	18	2	2	NUM
cjfa-8193	313	19	2	2	NUM
cjfa-8193	313	20	2	2	NUM
cjfa-8193	314	1			NUM
cjfa-8193	314	2			NOUN
cjfa-8193	314	3			PROPN
cjfa-8193	314	4			PROPN
cjfa-8193	315	1			PROPN
cjfa-8193	315	2			INTJ
cjfa-8193	315	3			NUM
cjfa-8193	315	4			ADP
cjfa-8193	316	1			PROPN
cjfa-8193	316	2			PROPN
cjfa-8193	316	3			PRON
cjfa-8193	316	4			NOUN
cjfa-8193	316	5			VERB
cjfa-8193	316	6			PROPN
cjfa-8193	316	7			PROPN
cjfa-8193	316	8			NOUN
cjfa-8193	316	9			ADP
cjfa-8193	316	10			NUM
cjfa-8193	316	11			NOUN
cjfa-8193	316	12			NOUN
cjfa-8193	317	1			INTJ
cjfa-8193	318	1			NUM
cjfa-8193	318	2			NUM
cjfa-8193	318	3			PRON
cjfa-8193	318	4			NUM
cjfa-8193	318	5			NOUN
cjfa-8193	319	1			NOUN
cjfa-8193	319	2			ADP
cjfa-8193	319	3			PROPN
cjfa-8193	319	4			PROPN
cjfa-8193	320	1			PROPN
cjfa-8193	320	2			PROPN
cjfa-8193	321	1			PROPN
cjfa-8193	321	2			NOUN
cjfa-8193	322	1			PROPN
cjfa-8193	323	1			PROPN
cjfa-8193	324	1			PROPN
cjfa-8193	325	1			PROPN
cjfa-8193	325	2			PROPN
cjfa-8193	326	1			PROPN
cjfa-8193	326	2			NOUN
cjfa-8193	326	3			VERB
cjfa-8193	326	4			PUNCT
cjfa-8193	326	5			NOUN
cjfa-8193	326	6			PRON
cjfa-8193	326	7			PROPN
cjfa-8193	326	8			PROPN
cjfa-8193	326	9			NOUN
cjfa-8193	326	10			NUM
cjfa-8193	326	11			PRON
cjfa-8193	326	12			PROPN
cjfa-8193	326	13			PROPN
cjfa-8193	326	14			NOUN
cjfa-8193	326	15			PUNCT
cjfa-8193	327	1	t	t	PROPN
cjfa-8193	327	2	t	t	X
cjfa-8193	327	3	it	it	PRON
cjfa-8193	327	4	t	t	PROPN
cjfa-8193	327	5	skst	skst	NOUN
cjfa-8193	327	6	t	t	PROPN
cjfa-8193	327	7	msz	msz	VERB
cjfa-8193	327	8	svtl	svtl	NOUN
cjfa-8193	327	9			NOUN
cjfa-8193	327	10			PRON
cjfa-8193	327	11			NOUN
cjfa-8193	327	12			NOUN
cjfa-8193	327	13			X
cjfa-8193	327	14			NOUN
cjfa-8193	327	15	[	[	X
cjfa-8193	327	16	8	8	NUM
cjfa-8193	327	17	]	]	PUNCT
cjfa-8193	327	18	results	result	NOUN
cjfa-8193	327	19	:	:	PUNCT
cjfa-8193	327	20	model	model	NOUN
cjfa-8193	327	21	evalutation	evalutation	NOUN
cjfa-8193	327	22	we	we	PRON
cjfa-8193	327	23	evaluate	evaluate	VERB
cjfa-8193	327	24	the	the	DET
cjfa-8193	327	25	alternative	alternative	ADJ
cjfa-8193	327	26	models	model	NOUN
cjfa-8193	327	27	by	by	ADP
cjfa-8193	327	28	(	(	PUNCT
cjfa-8193	327	29	i	i	NOUN
cjfa-8193	327	30	)	)	PUNCT
cjfa-8193	327	31	an	an	DET
cjfa-8193	327	32	assessment	assessment	NOUN
cjfa-8193	327	33	of	of	ADP
cjfa-8193	327	34	the	the	DET
cjfa-8193	327	35	parameters	parameter	NOUN
cjfa-8193	327	36	associated	associate	VERB
cjfa-8193	327	37	with	with	ADP
cjfa-8193	327	38	each	each	DET
cjfa-8193	327	39	model	model	NOUN
cjfa-8193	327	40	set	set	NOUN
cjfa-8193	327	41	(	(	PUNCT
cjfa-8193	327	42	ii	ii	NOUN
cjfa-8193	327	43	)	)	PUNCT
cjfa-8193	327	44	an	an	DET
cjfa-8193	327	45	evaluation	evaluation	NOUN
cjfa-8193	327	46	of	of	ADP
cjfa-8193	327	47	each	each	DET
cjfa-8193	327	48	model	model	NOUN
cjfa-8193	327	49	set	set	PROPN
cjfa-8193	327	50	’s	’s	PART
cjfa-8193	327	51	forecasting	forecasting	NOUN
cjfa-8193	327	52	performance	performance	NOUN
cjfa-8193	327	53	.	.	PUNCT
cjfa-8193	328	1	(	(	PUNCT
cjfa-8193	328	2	i	i	NOUN
cjfa-8193	328	3	)	)	PUNCT
cjfa-8193	328	4	 	 	SPACE
cjfa-8193	328	5	parameter	parameter	NOUN
cjfa-8193	328	6	based	base	VERB
cjfa-8193	328	7	evaluation	evaluation	NOUN
cjfa-8193	328	8	tables	table	NOUN
cjfa-8193	328	9	2	2	NUM
cjfa-8193	328	10	,	,	PUNCT
cjfa-8193	328	11	3	3	NUM
cjfa-8193	328	12	and	and	CCONJ
cjfa-8193	328	13	4	4	NUM
cjfa-8193	328	14	,	,	PUNCT
cjfa-8193	328	15	present	present	VERB
cjfa-8193	328	16	the	the	DET
cjfa-8193	328	17	parameter	parameter	NOUN
cjfa-8193	328	18	values	value	NOUN
cjfa-8193	328	19	and	and	CCONJ
cjfa-8193	328	20	associated	associate	VERB
cjfa-8193	328	21	significance	significance	NOUN
cjfa-8193	328	22	tests	test	NOUN
cjfa-8193	328	23	for	for	ADP
cjfa-8193	328	24	the	the	DET
cjfa-8193	328	25	garch	garch	NOUN
cjfa-8193	328	26	,	,	PUNCT
cjfa-8193	328	27	egarch	egarch	NOUN
cjfa-8193	328	28	and	and	CCONJ
cjfa-8193	328	29	gjr	gjr	NOUN
cjfa-8193	328	30	-	-	PUNCT
cjfa-8193	328	31	garch	garch	NOUN
cjfa-8193	328	32	specified	specify	VERB
cjfa-8193	328	33	model	model	NOUN
cjfa-8193	328	34	sets	set	NOUN
cjfa-8193	328	35	.	.	PUNCT
cjfa-8193	329	1	for	for	ADP
cjfa-8193	329	2	the	the	DET
cjfa-8193	329	3	first	first	ADJ
cjfa-8193	329	4	and	and	CCONJ
cjfa-8193	329	5	third	third	ADJ
cjfa-8193	329	6	model	model	NOUN
cjfa-8193	329	7	sets	set	VERB
cjfa-8193	329	8	the	the	DET
cjfa-8193	329	9	constants	constant	NOUN
cjfa-8193	329	10	in	in	ADP
cjfa-8193	329	11	the	the	DET
cjfa-8193	329	12	mean	mean	ADJ
cjfa-8193	329	13	equations	equation	NOUN
cjfa-8193	329	14	and	and	CCONJ
cjfa-8193	329	15	the	the	DET
cjfa-8193	329	16	variance	variance	NOUN
cjfa-8193	329	17	parameters	parameter	NOUN
cjfa-8193	329	18	are	be	AUX
cjfa-8193	329	19	positive	positive	ADJ
cjfa-8193	329	20	and	and	CCONJ
cjfa-8193	329	21	statistically	statistically	ADV
cjfa-8193	329	22	significant	significant	ADJ
cjfa-8193	329	23	for	for	ADP
cjfa-8193	329	24	all	all	DET
cjfa-8193	329	25	distributions	distribution	NOUN
cjfa-8193	329	26	.	.	PUNCT
cjfa-8193	330	1	for	for	ADP
cjfa-8193	330	2	the	the	DET
cjfa-8193	330	3	egarch	egarch	NOUN
cjfa-8193	330	4	model	model	NOUN
cjfa-8193	330	5	set	set	VERB
cjfa-8193	330	6	the	the	DET
cjfa-8193	330	7	constants	constant	NOUN
cjfa-8193	330	8	for	for	ADP
cjfa-8193	330	9	the	the	DET
cjfa-8193	330	10	mean	mean	ADJ
cjfa-8193	330	11	equations	equation	NOUN
cjfa-8193	330	12	are	be	AUX
cjfa-8193	330	13	not	not	PART
cjfa-8193	330	14	statistically	statistically	ADV
cjfa-8193	330	15	significant	significant	ADJ
cjfa-8193	330	16	.	.	PUNCT
cjfa-8193	331	1	the	the	DET
cjfa-8193	331	2	alpha	alpha	ADJ
cjfa-8193	331	3	coefficient	coefficient	NOUN
cjfa-8193	331	4	for	for	ADP
cjfa-8193	331	5	all	all	DET
cjfa-8193	331	6	models	model	NOUN
cjfa-8193	331	7	and	and	CCONJ
cjfa-8193	331	8	distributions	distribution	NOUN
cjfa-8193	331	9	is	be	AUX
cjfa-8193	331	10	statistically	statistically	ADV
cjfa-8193	331	11	significant	significant	ADJ
cjfa-8193	331	12	at	at	ADP
cjfa-8193	331	13	the	the	DET
cjfa-8193	331	14	99	99	NUM
cjfa-8193	331	15	%	%	NOUN
cjfa-8193	331	16	level	level	NOUN
cjfa-8193	331	17	of	of	ADP
cjfa-8193	331	18	confidence	confidence	NOUN
cjfa-8193	331	19	.	.	PUNCT
cjfa-8193	332	1	this	this	PRON
cjfa-8193	332	2	implies	imply	VERB
cjfa-8193	332	3	the	the	DET
cjfa-8193	332	4	existence	existence	NOUN
cjfa-8193	332	5	of	of	ADP
cjfa-8193	332	6	the	the	DET
cjfa-8193	332	7	arch	arch	ADJ
cjfa-8193	332	8	process	process	NOUN
cjfa-8193	332	9	in	in	ADP
cjfa-8193	332	10	the	the	DET
cjfa-8193	332	11	residuals	residual	NOUN
cjfa-8193	332	12	term	term	NOUN
cjfa-8193	332	13	.	.	PUNCT
cjfa-8193	333	1	the	the	DET
cjfa-8193	333	2	returns	return	NOUN
cjfa-8193	333	3	exhibit	exhibit	VERB
cjfa-8193	333	4	time	time	NOUN
cjfa-8193	333	5	-	-	PUNCT
cjfa-8193	333	6	varying	vary	VERB
cjfa-8193	333	7	volatility	volatility	NOUN
cjfa-8193	333	8	clustering	clustering	NOUN
cjfa-8193	333	9	;	;	PUNCT
cjfa-8193	333	10	this	this	PRON
cjfa-8193	333	11	indicates	indicate	VERB
cjfa-8193	333	12	that	that	SCONJ
cjfa-8193	333	13	periods	period	NOUN
cjfa-8193	333	14	of	of	ADP
cjfa-8193	333	15	volatility	volatility	NOUN
cjfa-8193	333	16	are	be	AUX
cjfa-8193	333	17	followed	follow	VERB
cjfa-8193	333	18	by	by	ADP
cjfa-8193	333	19	periods	period	NOUN
cjfa-8193	333	20	of	of	ADP
cjfa-8193	333	21	relative	relative	ADJ
cjfa-8193	333	22	calm	calm	NOUN
cjfa-8193	333	23	.	.	PUNCT
cjfa-8193	334	1	the	the	DET
cjfa-8193	334	2	beta	beta	ADJ
cjfa-8193	334	3	coefficients	coefficient	NOUN
cjfa-8193	334	4	of	of	ADP
cjfa-8193	334	5	the	the	DET
cjfa-8193	334	6	three	three	NUM
cjfa-8193	334	7	models	model	NOUN
cjfa-8193	334	8	in	in	ADP
cjfa-8193	334	9	all	all	DET
cjfa-8193	334	10	distribution	distribution	NOUN
cjfa-8193	334	11	are	be	AUX
cjfa-8193	334	12	also	also	ADV
cjfa-8193	334	13	statistically	statistically	ADV
cjfa-8193	334	14	significant	significant	ADJ
cjfa-8193	334	15	at	at	ADP
cjfa-8193	334	16	the	the	DET
cjfa-8193	334	17	99	99	NUM
cjfa-8193	334	18	%	%	NOUN
cjfa-8193	334	19	level	level	NOUN
cjfa-8193	334	20	of	of	ADP
cjfa-8193	334	21	confidence	confidence	NOUN
cjfa-8193	334	22	.	.	PUNCT
cjfa-8193	335	1	this	this	PRON
cjfa-8193	335	2	indicates	indicate	VERB
cjfa-8193	335	3	that	that	SCONJ
cjfa-8193	335	4	the	the	DET
cjfa-8193	335	5	variance	variance	NOUN
cjfa-8193	335	6	is	be	AUX
cjfa-8193	335	7	dependent	dependent	ADJ
cjfa-8193	335	8	on	on	ADP
cjfa-8193	335	9	its	its	PRON
cjfa-8193	335	10	moving	move	VERB
cjfa-8193	335	11	average	average	NOUN
cjfa-8193	335	12	.	.	PUNCT
cjfa-8193	336	1	in	in	ADP
cjfa-8193	336	2	a	a	DET
cjfa-8193	336	3	subset	subset	NOUN
cjfa-8193	336	4	of	of	ADP
cjfa-8193	336	5	the	the	DET
cjfa-8193	336	6	models	model	NOUN
cjfa-8193	336	7	the	the	DET
cjfa-8193	336	8	sum	sum	NOUN
cjfa-8193	336	9	of	of	ADP
cjfa-8193	336	10	alpha	alpha	NOUN
cjfa-8193	336	11	and	and	CCONJ
cjfa-8193	336	12	beta	beta	NOUN
cjfa-8193	336	13	is	be	AUX
cjfa-8193	336	14	close	close	ADJ
cjfa-8193	336	15	to	to	ADP
cjfa-8193	336	16	unity	unity	NOUN
cjfa-8193	336	17	,	,	PUNCT
cjfa-8193	336	18	which	which	PRON
cjfa-8193	336	19	implies	imply	VERB
cjfa-8193	336	20	in	in	ADP
cjfa-8193	336	21	these	these	DET
cjfa-8193	336	22	cases	case	NOUN
cjfa-8193	336	23	that	that	SCONJ
cjfa-8193	336	24	volatility	volatility	NOUN
cjfa-8193	336	25	shocks	shock	NOUN
cjfa-8193	336	26	are	be	AUX
cjfa-8193	336	27	quite	quite	ADV
cjfa-8193	336	28	persistent	persistent	ADJ
cjfa-8193	336	29	and	and	CCONJ
cjfa-8193	336	30	suggests	suggest	VERB
cjfa-8193	336	31	that	that	SCONJ
cjfa-8193	336	32	a	a	DET
cjfa-8193	336	33	large	large	ADJ
cjfa-8193	336	34	positive	positive	ADJ
cjfa-8193	336	35	(	(	PUNCT
cjfa-8193	336	36	or	or	CCONJ
cjfa-8193	336	37	negative	negative	ADJ
cjfa-8193	336	38	)	)	PUNCT
cjfa-8193	336	39	return	return	NOUN
cjfa-8193	336	40	will	will	AUX
cjfa-8193	336	41	lead	lead	VERB
cjfa-8193	336	42	future	future	ADJ
cjfa-8193	336	43	forecasts	forecast	NOUN
cjfa-8193	336	44	of	of	ADP
cjfa-8193	336	45	the	the	DET
cjfa-8193	336	46	variance	variance	NOUN
cjfa-8193	336	47	to	to	PART
cjfa-8193	336	48	be	be	AUX
cjfa-8193	336	49	high	high	ADJ
cjfa-8193	336	50	for	for	ADP
cjfa-8193	336	51	an	an	DET
cjfa-8193	336	52	extended	extended	ADJ
cjfa-8193	336	53	period	period	NOUN
cjfa-8193	336	54	.	.	PUNCT
cjfa-8193	337	1	the	the	DET
cjfa-8193	337	2	garch	garch	NOUN
cjfa-8193	337	3	coefficient	coefficient	NOUN
cjfa-8193	337	4	(	(	PUNCT
cjfa-8193	337	5	beta	beta	NOUN
cjfa-8193	337	6	)	)	PUNCT
cjfa-8193	337	7	is	be	AUX
cjfa-8193	337	8	larger	large	ADJ
cjfa-8193	337	9	than	than	ADP
cjfa-8193	337	10	the	the	DET
cjfa-8193	337	11	arch	arch	ADJ
cjfa-8193	337	12	term	term	NOUN
cjfa-8193	337	13	(	(	PUNCT
cjfa-8193	337	14	alpha	alpha	NOUN
cjfa-8193	337	15	)	)	PUNCT
cjfa-8193	337	16	in	in	ADP
cjfa-8193	337	17	all	all	DET
cjfa-8193	337	18	three	three	NUM
cjfa-8193	337	19	model	model	NOUN
cjfa-8193	337	20	sets	set	NOUN
cjfa-8193	337	21	.	.	PUNCT
cjfa-8193	338	1	this	this	PRON
cjfa-8193	338	2	is	be	AUX
cjfa-8193	338	3	a	a	DET
cjfa-8193	338	4	further	further	ADJ
cjfa-8193	338	5	indication	indication	NOUN
cjfa-8193	338	6	that	that	SCONJ
cjfa-8193	338	7	the	the	DET
cjfa-8193	338	8	conditional	conditional	ADJ
cjfa-8193	338	9	variance	variance	NOUN
cjfa-8193	338	10	will	will	AUX
cjfa-8193	338	11	exhibit	exhibit	VERB
cjfa-8193	338	12	long	long	ADJ
cjfa-8193	338	13	persistence	persistence	NOUN
cjfa-8193	338	14	of	of	ADP
cjfa-8193	338	15	volatility	volatility	NOUN
cjfa-8193	338	16	.	.	PUNCT
cjfa-8193	339	1	forecasting	forecast	VERB
cjfa-8193	339	2	the	the	DET
cjfa-8193	339	3	jordanian	jordanian	ADJ
cjfa-8193	339	4	stock	stock	NOUN
cjfa-8193	339	5	index	index	PROPN
cjfa-8193	339	6	…	…	PUNCT
cjfa-8193	339	7	19	19	NUM
cjfa-8193	339	8	the	the	DET
cjfa-8193	339	9	gjr	gjr	NOUN
cjfa-8193	339	10	models	model	NOUN
cjfa-8193	339	11	show	show	VERB
cjfa-8193	339	12	no	no	DET
cjfa-8193	339	13	evidence	evidence	NOUN
cjfa-8193	339	14	of	of	ADP
cjfa-8193	339	15	asymmetry	asymmetry	NOUN
cjfa-8193	339	16	effects	effect	NOUN
cjfa-8193	339	17	being	be	AUX
cjfa-8193	339	18	statistically	statistically	ADV
cjfa-8193	339	19	significant	significant	ADJ
cjfa-8193	339	20	.	.	PUNCT
cjfa-8193	340	1	egarch	egarch	NOUN
cjfa-8193	340	2	models	model	NOUN
cjfa-8193	340	3	however	however	ADV
cjfa-8193	340	4	,	,	PUNCT
cjfa-8193	340	5	indicate	indicate	VERB
cjfa-8193	340	6	significance	significance	NOUN
cjfa-8193	340	7	in	in	ADP
cjfa-8193	340	8	the	the	DET
cjfa-8193	340	9	magnitude	magnitude	ADJ
cjfa-8193	340	10	effect	effect	NOUN
cjfa-8193	340	11	but	but	CCONJ
cjfa-8193	340	12	not	not	PART
cjfa-8193	340	13	in	in	ADP
cjfa-8193	340	14	the	the	DET
cjfa-8193	340	15	sign	sign	NOUN
cjfa-8193	340	16	effect	effect	NOUN
cjfa-8193	340	17	.	.	PUNCT
cjfa-8193	341	1	table	table	NOUN
cjfa-8193	341	2	2	2	NUM
cjfa-8193	341	3	.	.	PUNCT
cjfa-8193	342	1	the	the	DET
cjfa-8193	342	2	garch	garch	NOUN
cjfa-8193	342	3	model	model	NOUN
cjfa-8193	342	4	set	set	VERB
cjfa-8193	342	5	distribution	distribution	NOUN
cjfa-8193	342	6	const	const	NOUN
cjfa-8193	342	7	.	.	PUNCT
cjfa-8193	343	1	(	(	PUNCT
cjfa-8193	343	2	m)α	m)α	X
cjfa-8193	343	3	const	const	X
cjfa-8193	343	4	.	.	PUNCT
cjfa-8193	344	1	(	(	PUNCT
cjfa-8193	344	2	v)β	v)β	X
cjfa-8193	344	3	arch	arch	NOUN
cjfa-8193	344	4	(	(	PUNCT
cjfa-8193	344	5	alpha	alpha	NOUN
cjfa-8193	344	6	)	)	PUNCT
cjfa-8193	344	7	garch	garch	NOUN
cjfa-8193	344	8	(	(	PUNCT
cjfa-8193	344	9	beta	beta	NOUN
cjfa-8193	344	10	)	)	PUNCT
cjfa-8193	344	11	student	student	NOUN
cjfa-8193	344	12	(	(	PUNCT
cjfa-8193	344	13	df)µ	df)µ	PROPN
cjfa-8193	344	14	ged	ge	VERB
cjfa-8193	344	15	(	(	PUNCT
cjfa-8193	344	16	df)µ	df)µ	PROPN
cjfa-8193	344	17	asymm	asymm	NOUN
cjfa-8193	344	18	.	.	PUNCT
cjfa-8193	345	1	tail	tail	NOUN
cjfa-8193	345	2	normal	normal	ADJ
cjfa-8193	345	3	coefficient	coefficient	NOUN
cjfa-8193	345	4	0.02	0.02	NUM
cjfa-8193	345	5	0.01	0.01	NUM
cjfa-8193	345	6	0.11	0.11	NUM
cjfa-8193	345	7	0.89	0.89	NUM
cjfa-8193	345	8	na	na	NOUN
cjfa-8193	345	9	na	na	NOUN
cjfa-8193	345	10	na	na	ADP
cjfa-8193	345	11	na	na	ADP
cjfa-8193	345	12	p	p	NOUN
cjfa-8193	345	13	-	-	PUNCT
cjfa-8193	345	14	value	value	NOUN
cjfa-8193	345	15	0.05	0.05	NUM
cjfa-8193	345	16	0.02	0.02	NUM
cjfa-8193	345	17	0	0	NUM
cjfa-8193	345	18	0	0	NUM
cjfa-8193	345	19	na	na	NOUN
cjfa-8193	345	20	na	na	PART
cjfa-8193	345	21	na	na	VERB
cjfa-8193	345	22	na	na	VERB
cjfa-8193	345	23	student	student	NOUN
cjfa-8193	345	24	coefficient	coefficient	NOUN
cjfa-8193	345	25	0.02	0.02	NUM
cjfa-8193	345	26	0.01	0.01	NUM
cjfa-8193	345	27	0.14	0.14	NUM
cjfa-8193	345	28	0.86	0.86	NUM
cjfa-8193	345	29	6.23	6.23	NUM
cjfa-8193	345	30	na	na	NOUN
cjfa-8193	345	31	na	na	ADP
cjfa-8193	345	32	na	na	ADP
cjfa-8193	345	33	p	p	NOUN
cjfa-8193	345	34	-	-	PUNCT
cjfa-8193	345	35	value	value	NOUN
cjfa-8193	345	36	0.02	0.02	NUM
cjfa-8193	345	37	0.02	0.02	NUM
cjfa-8193	345	38	0	0	NUM
cjfa-8193	345	39	0	0	NUM
cjfa-8193	345	40	0	0	NUM
cjfa-8193	345	41	na	na	NOUN
cjfa-8193	345	42	na	na	AUX
cjfa-8193	345	43	na	na	AUX
cjfa-8193	345	44	ged	ge	VERB
cjfa-8193	345	45	coefficient	coefficient	NOUN
cjfa-8193	345	46	0.02	0.02	NUM
cjfa-8193	345	47	0.01	0.01	NUM
cjfa-8193	345	48	0.12	0.12	NUM
cjfa-8193	345	49	0.88	0.88	NUM
cjfa-8193	345	50	na	na	PROPN
cjfa-8193	345	51	1.36	1.36	NUM
cjfa-8193	345	52	na	na	PART
cjfa-8193	345	53	na	na	ADP
cjfa-8193	345	54	p	p	NOUN
cjfa-8193	345	55	-	-	PUNCT
cjfa-8193	345	56	value	value	NOUN
cjfa-8193	345	57	0.02	0.02	NUM
cjfa-8193	345	58	0.02	0.02	NUM
cjfa-8193	345	59	0	0	NUM
cjfa-8193	345	60	0	0	NUM
cjfa-8193	345	61	na	na	NOUN
cjfa-8193	345	62	0	0	NUM
cjfa-8193	345	63	na	na	NOUN
cjfa-8193	345	64	na	na	ADP
cjfa-8193	345	65	skewed	skewed	ADJ
cjfa-8193	345	66	student	student	NOUN
cjfa-8193	345	67	coefficient	coefficient	NOUN
cjfa-8193	345	68	0.02	0.02	NUM
cjfa-8193	345	69	0.01	0.01	NUM
cjfa-8193	345	70	0.14	0.14	NUM
cjfa-8193	345	71	0.86	0.86	NUM
cjfa-8193	345	72	na	na	NOUN
cjfa-8193	345	73	na	na	SYM
cjfa-8193	345	74	-0.01	-0.01	NUM
cjfa-8193	345	75	6.22	6.22	NUM
cjfa-8193	345	76	p	p	ADJ
cjfa-8193	345	77	-	-	PUNCT
cjfa-8193	345	78	value	value	NOUN
cjfa-8193	345	79	0.05	0.05	NUM
cjfa-8193	345	80	0.02	0.02	NUM
cjfa-8193	345	81	0	0	NUM
cjfa-8193	345	82	0	0	NUM
cjfa-8193	345	83	na	na	NOUN
cjfa-8193	345	84	na	na	SYM
cjfa-8193	345	85	0.69	0.69	NUM
cjfa-8193	345	86	0	0	NUM
cjfa-8193	346	1	α	α	NOUN
cjfa-8193	346	2	mean	mean	NOUN
cjfa-8193	346	3	equation	equation	NOUN
cjfa-8193	346	4	,	,	PUNCT
cjfa-8193	346	5	β	β	X
cjfa-8193	346	6	variance	variance	NOUN
cjfa-8193	346	7	equation	equation	NOUN
cjfa-8193	346	8	,	,	PUNCT
cjfa-8193	346	9	µ	µ	X
cjfa-8193	346	10	degrees	degree	NOUN
cjfa-8193	346	11	of	of	ADP
cjfa-8193	346	12	freedom	freedom	NOUN
cjfa-8193	346	13	.	.	PUNCT
cjfa-8193	347	1	s	s	PART
cjfa-8193	347	2	o	o	X
cjfa-8193	347	3	u	u	NOUN
cjfa-8193	347	4	r	r	NOUN
cjfa-8193	347	5	c	c	NOUN
cjfa-8193	347	6	e	e	NOUN
cjfa-8193	347	7	:	:	PUNCT
cjfa-8193	347	8	estimated	estimate	VERB
cjfa-8193	347	9	by	by	ADP
cjfa-8193	347	10	the	the	DET
cjfa-8193	347	11	authors	author	NOUN
cjfa-8193	347	12	using	use	VERB
cjfa-8193	347	13	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	347	14	7	7	NUM
cjfa-8193	347	15	.	.	PUNCT
cjfa-8193	347	16	table	table	NOUN
cjfa-8193	347	17	3	3	NUM
cjfa-8193	347	18	.	.	PUNCT
cjfa-8193	348	1	the	the	DET
cjfa-8193	348	2	egarch	egarch	NOUN
cjfa-8193	348	3	model	model	NOUN
cjfa-8193	348	4	set	set	VERB
cjfa-8193	348	5	distribution	distribution	NOUN
cjfa-8193	348	6	const	const	NOUN
cjfa-8193	348	7	.	.	PUNCT
cjfa-8193	349	1	(	(	PUNCT
cjfa-8193	349	2	m)α	m)α	X
cjfa-8193	349	3	const	const	X
cjfa-8193	349	4	.	.	PUNCT
cjfa-8193	350	1	(	(	PUNCT
cjfa-8193	350	2	v)β	v)β	X
cjfa-8193	350	3	arch	arch	NOUN
cjfa-8193	350	4	(	(	PUNCT
cjfa-8193	350	5	alpha	alpha	NOUN
cjfa-8193	350	6	)	)	PUNCT
cjfa-8193	350	7	garch	garch	NOUN
cjfa-8193	350	8	(	(	PUNCT
cjfa-8193	350	9	beta	beta	NOUN
cjfa-8193	350	10	)	)	PUNCT
cjfa-8193	350	11	student	student	NOUN
cjfa-8193	350	12	(	(	PUNCT
cjfa-8193	350	13	df)µ	df)µ	PROPN
cjfa-8193	350	14	ged	ge	VERB
cjfa-8193	350	15	(	(	PUNCT
cjfa-8193	350	16	df)µ	df)µ	PROPN
cjfa-8193	350	17	asymm	asymm	NOUN
cjfa-8193	350	18	.	.	PUNCT
cjfa-8193	351	1	tail	tail	NOUN
cjfa-8193	351	2	egarch	egarch	NOUN
cjfa-8193	351	3	(	(	PUNCT
cjfa-8193	351	4	theta1	theta1	NOUN
cjfa-8193	351	5	)	)	PUNCT
cjfa-8193	351	6	egarch	egarch	NOUN
cjfa-8193	351	7	(	(	PUNCT
cjfa-8193	351	8	theta2	theta2	NOUN
cjfa-8193	351	9	)	)	PUNCT
cjfa-8193	351	10	normal	normal	ADJ
cjfa-8193	351	11	coefficient	coefficient	NOUN
cjfa-8193	351	12	0.01	0.01	NUM
cjfa-8193	351	13	0.12	0.12	NUM
cjfa-8193	351	14	-0.53	-0.53	NUM
cjfa-8193	351	15	0.99	0.99	NUM
cjfa-8193	351	16	na	na	NOUN
cjfa-8193	351	17	na	na	NOUN
cjfa-8193	351	18	na	na	NOUN
cjfa-8193	351	19	na	na	SYM
cjfa-8193	351	20	0	0	NUM
cjfa-8193	351	21	0.39	0.39	NUM
cjfa-8193	351	22	p	p	NOUN
cjfa-8193	351	23	-	-	PUNCT
cjfa-8193	351	24	value	value	NOUN
cjfa-8193	351	25	0.16	0.16	NUM
cjfa-8193	351	26	0.74	0.74	NUM
cjfa-8193	351	27	0	0	NUM
cjfa-8193	351	28	0	0	NUM
cjfa-8193	351	29	na	na	NOUN
cjfa-8193	351	30	na	na	NOUN
cjfa-8193	351	31	na	na	NOUN
cjfa-8193	351	32	na	na	PART
cjfa-8193	351	33	0.8	0.8	NUM
cjfa-8193	351	34	0	0	NUM
cjfa-8193	351	35	student	student	NOUN
cjfa-8193	351	36	coefficient	coefficient	NOUN
cjfa-8193	351	37	0.02	0.02	NUM
cjfa-8193	351	38	-0.59	-0.59	NUM
cjfa-8193	351	39	-0.52	-0.52	NUM
cjfa-8193	351	40	0.99	0.99	NUM
cjfa-8193	351	41	6.47	6.47	NUM
cjfa-8193	351	42	na	na	PART
cjfa-8193	351	43	na	na	NOUN
cjfa-8193	351	44	na	na	NOUN
cjfa-8193	351	45	-0.01	-0.01	NUM
cjfa-8193	351	46	0.43	0.43	NUM
cjfa-8193	351	47	p	p	NOUN
cjfa-8193	351	48	-	-	PUNCT
cjfa-8193	351	49	value	value	NOUN
cjfa-8193	351	50	0.17	0.17	NUM
cjfa-8193	351	51	0.02	0.02	NUM
cjfa-8193	351	52	0	0	NUM
cjfa-8193	351	53	0	0	NUM
cjfa-8193	351	54	0	0	NUM
cjfa-8193	351	55	na	na	NOUN
cjfa-8193	351	56	na	na	NOUN
cjfa-8193	351	57	na	na	ADP
cjfa-8193	351	58	0.55	0.55	NUM
cjfa-8193	351	59	0	0	NUM
cjfa-8193	351	60	ged	ge	VERB
cjfa-8193	351	61	coefficient	coefficient	NOUN
cjfa-8193	351	62	0.02	0.02	NUM
cjfa-8193	351	63	-0.68	-0.68	NOUN
cjfa-8193	351	64	-0.53	-0.53	NOUN
cjfa-8193	351	65	0.99	0.99	NUM
cjfa-8193	351	66	na	na	NOUN
cjfa-8193	351	67	1.38	1.38	NUM
cjfa-8193	351	68	na	na	NOUN
cjfa-8193	351	69	na	na	SYM
cjfa-8193	351	70	0	0	NUM
cjfa-8193	351	71	0.41	0.41	NUM
cjfa-8193	351	72	p	p	NOUN
cjfa-8193	351	73	-	-	PUNCT
cjfa-8193	351	74	value	value	NOUN
cjfa-8193	351	75	0.11	0.11	NUM
cjfa-8193	351	76	0	0	NUM
cjfa-8193	351	77	0	0	NUM
cjfa-8193	351	78	0	0	NUM
cjfa-8193	351	79	na	na	NOUN
cjfa-8193	351	80	0	0	NUM
cjfa-8193	351	81	na	na	NOUN
cjfa-8193	351	82	na	na	ADP
cjfa-8193	351	83	0.93	0.93	NUM
cjfa-8193	351	84	0	0	NUM
cjfa-8193	351	85	skewed	skewed	ADJ
cjfa-8193	351	86	student	student	NOUN
cjfa-8193	351	87	coefficient	coefficient	NOUN
cjfa-8193	351	88	0.01	0.01	NUM
cjfa-8193	351	89	-1.11	-1.11	NUM
cjfa-8193	351	90	-0.53	-0.53	NOUN
cjfa-8193	351	91	0.99	0.99	NUM
cjfa-8193	351	92	na	na	NOUN
cjfa-8193	351	93	na	na	ADP
cjfa-8193	351	94	-0.02	-0.02	NUM
cjfa-8193	351	95	6.44	6.44	NUM
cjfa-8193	351	96	-0.01	-0.01	NUM
cjfa-8193	351	97	0.43	0.43	NUM
cjfa-8193	351	98	p	p	NOUN
cjfa-8193	351	99	-	-	PUNCT
cjfa-8193	351	100	value	value	NOUN
cjfa-8193	351	101	0.15	0.15	NUM
cjfa-8193	351	102	0.15	0.15	NUM
cjfa-8193	351	103	0	0	NUM
cjfa-8193	351	104	0	0	NUM
cjfa-8193	351	105	na	na	NOUN
cjfa-8193	351	106	na	na	SYM
cjfa-8193	351	107	0.48	0.48	NUM
cjfa-8193	351	108	0	0	NUM
cjfa-8193	351	109	0.65	0.65	NUM
cjfa-8193	351	110	0	0	NUM
cjfa-8193	352	1	α	α	NOUN
cjfa-8193	352	2	mean	mean	NOUN
cjfa-8193	352	3	equation	equation	NOUN
cjfa-8193	352	4	,	,	PUNCT
cjfa-8193	352	5	β	β	X
cjfa-8193	352	6	variance	variance	NOUN
cjfa-8193	352	7	equation	equation	NOUN
cjfa-8193	352	8	,	,	PUNCT
cjfa-8193	352	9	µ	µ	X
cjfa-8193	352	10	degrees	degree	NOUN
cjfa-8193	352	11	of	of	ADP
cjfa-8193	352	12	freedom	freedom	NOUN
cjfa-8193	352	13	.	.	PUNCT
cjfa-8193	353	1	s	s	PART
cjfa-8193	353	2	o	o	X
cjfa-8193	353	3	u	u	NOUN
cjfa-8193	353	4	r	r	NOUN
cjfa-8193	353	5	c	c	NOUN
cjfa-8193	353	6	e	e	NOUN
cjfa-8193	353	7	:	:	PUNCT
cjfa-8193	353	8	estimated	estimate	VERB
cjfa-8193	353	9	by	by	ADP
cjfa-8193	353	10	the	the	DET
cjfa-8193	353	11	authors	author	NOUN
cjfa-8193	353	12	using	use	VERB
cjfa-8193	353	13	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	353	14	7	7	NUM
cjfa-8193	353	15	.	.	PUNCT
cjfa-8193	354	1	h.	h.	PROPN
cjfa-8193	354	2	al	al	PROPN
cjfa-8193	354	3	-	-	PUNCT
cjfa-8193	354	4	hajieh	hajieh	PROPN
cjfa-8193	354	5	,	,	PUNCT
cjfa-8193	354	6	h.	h.	PROPN
cjfa-8193	354	7	alnemer	alnemer	PROPN
cjfa-8193	354	8	,	,	PUNCT
cjfa-8193	354	9	t.	t.	PROPN
cjfa-8193	354	10	rodgers	rodgers	PROPN
cjfa-8193	354	11	,	,	PUNCT
cjfa-8193	354	12	j.	j.	PROPN
cjfa-8193	354	13	niklewski20	niklewski20	PROPN
cjfa-8193	354	14	table	table	NOUN
cjfa-8193	354	15	4	4	NUM
cjfa-8193	354	16	.	.	PUNCT
cjfa-8193	355	1	the	the	DET
cjfa-8193	355	2	gjr	gjr	NOUN
cjfa-8193	355	3	-	-	PUNCT
cjfa-8193	355	4	garch	garch	NOUN
cjfa-8193	355	5	model	model	NOUN
cjfa-8193	355	6	set	set	VERB
cjfa-8193	355	7	distribution	distribution	NOUN
cjfa-8193	355	8	const	const	NOUN
cjfa-8193	355	9	.	.	PUNCT
cjfa-8193	356	1	(	(	PUNCT
cjfa-8193	356	2	m)α	m)α	X
cjfa-8193	356	3	const	const	X
cjfa-8193	356	4	.	.	PUNCT
cjfa-8193	357	1	(	(	PUNCT
cjfa-8193	357	2	v)β	v)β	X
cjfa-8193	357	3	arch	arch	NOUN
cjfa-8193	357	4	(	(	PUNCT
cjfa-8193	357	5	alpha	alpha	NOUN
cjfa-8193	357	6	)	)	PUNCT
cjfa-8193	357	7	garch	garch	NOUN
cjfa-8193	357	8	(	(	PUNCT
cjfa-8193	357	9	beta	beta	NOUN
cjfa-8193	357	10	)	)	PUNCT
cjfa-8193	357	11	student	student	NOUN
cjfa-8193	357	12	(	(	PUNCT
cjfa-8193	357	13	df)µ	df)µ	PROPN
cjfa-8193	357	14	ged	ge	VERB
cjfa-8193	357	15	(	(	PUNCT
cjfa-8193	357	16	df)µ	df)µ	PROPN
cjfa-8193	357	17	asymm	asymm	NOUN
cjfa-8193	357	18	.	.	PUNCT
cjfa-8193	358	1	tail	tail	NOUN
cjfa-8193	358	2	gjr	gjr	NOUN
cjfa-8193	358	3	(	(	PUNCT
cjfa-8193	358	4	gamma	gamma	NOUN
cjfa-8193	358	5	)	)	PUNCT
cjfa-8193	358	6	normal	normal	ADJ
cjfa-8193	358	7	coefficient	coefficient	NOUN
cjfa-8193	358	8	0.02	0.02	NUM
cjfa-8193	358	9	0.01	0.01	NUM
cjfa-8193	358	10	0.11	0.11	NUM
cjfa-8193	358	11	0.89	0.89	NUM
cjfa-8193	358	12	na	na	NOUN
cjfa-8193	358	13	na	na	NOUN
cjfa-8193	358	14	na	na	ADV
cjfa-8193	358	15	na	na	PART
cjfa-8193	358	16	-0.01	-0.01	NUM
cjfa-8193	358	17	p	p	NOUN
cjfa-8193	358	18	-	-	PUNCT
cjfa-8193	358	19	value	value	NOUN
cjfa-8193	358	20	0.03	0.03	NUM
cjfa-8193	358	21	0.03	0.03	NUM
cjfa-8193	358	22	0	0	NUM
cjfa-8193	358	23	0	0	NUM
cjfa-8193	358	24	na	na	NOUN
cjfa-8193	358	25	na	na	NOUN
cjfa-8193	358	26	na	na	ADV
cjfa-8193	358	27	na	na	PART
cjfa-8193	358	28	0.53	0.53	NUM
cjfa-8193	358	29	student	student	NOUN
cjfa-8193	358	30	coefficient	coefficient	NOUN
cjfa-8193	358	31	0.02	0.02	NUM
cjfa-8193	358	32	0.01	0.01	NUM
cjfa-8193	358	33	0.14	0.14	NUM
cjfa-8193	358	34	0.86	0.86	NUM
cjfa-8193	358	35	6.22	6.22	NUM
cjfa-8193	358	36	na	na	NOUN
cjfa-8193	358	37	na	na	NOUN
cjfa-8193	358	38	na	na	ADP
cjfa-8193	358	39	0.01	0.01	NUM
cjfa-8193	358	40	p	p	NOUN
cjfa-8193	358	41	-	-	PUNCT
cjfa-8193	358	42	value	value	NOUN
cjfa-8193	358	43	0.03	0.03	NUM
cjfa-8193	358	44	0.02	0.02	NUM
cjfa-8193	358	45	0	0	NUM
cjfa-8193	358	46	0	0	NUM
cjfa-8193	358	47	0	0	NUM
cjfa-8193	358	48	na	na	NOUN
cjfa-8193	358	49	na	na	NOUN
cjfa-8193	358	50	na	na	PART
cjfa-8193	358	51	0.6	0.6	NUM
cjfa-8193	358	52	ged	ge	VERB
cjfa-8193	358	53	coefficient	coefficient	NOUN
cjfa-8193	358	54	0.02	0.02	NUM
cjfa-8193	358	55	0.01	0.01	NUM
cjfa-8193	358	56	0.12	0.12	NUM
cjfa-8193	358	57	0.88	0.88	NUM
cjfa-8193	358	58	na	na	PROPN
cjfa-8193	358	59	1.36	1.36	NUM
cjfa-8193	358	60	na	na	NOUN
cjfa-8193	358	61	na	na	ADP
cjfa-8193	358	62	0	0	NUM
cjfa-8193	359	1	p	p	NOUN
cjfa-8193	359	2	-	-	PUNCT
cjfa-8193	359	3	value	value	NOUN
cjfa-8193	359	4	0.02	0.02	NUM
cjfa-8193	359	5	0.03	0.03	NUM
cjfa-8193	359	6	0	0	NUM
cjfa-8193	359	7	0	0	NUM
cjfa-8193	359	8	na	na	NOUN
cjfa-8193	359	9	0	0	NUM
cjfa-8193	359	10	na	na	NOUN
cjfa-8193	359	11	na	na	SYM
cjfa-8193	359	12	0.92	0.92	NUM
cjfa-8193	359	13	skewed	skewed	ADJ
cjfa-8193	359	14	student	student	NOUN
cjfa-8193	359	15	coefficient	coefficient	NOUN
cjfa-8193	359	16	0.02	0.02	NUM
cjfa-8193	359	17	0.01	0.01	NUM
cjfa-8193	359	18	0.14	0.14	NUM
cjfa-8193	359	19	0.86	0.86	NUM
cjfa-8193	359	20	na	na	NOUN
cjfa-8193	359	21	na	na	NOUN
cjfa-8193	359	22	-0.01	-0.01	NUM
cjfa-8193	359	23	6.21	6.21	NUM
cjfa-8193	359	24	0.01	0.01	NUM
cjfa-8193	359	25	p	p	NOUN
cjfa-8193	359	26	-	-	PUNCT
cjfa-8193	359	27	value	value	NOUN
cjfa-8193	359	28	0.05	0.05	NUM
cjfa-8193	359	29	0.03	0.03	NUM
cjfa-8193	359	30	0	0	NUM
cjfa-8193	359	31	0	0	NUM
cjfa-8193	359	32	na	na	NOUN
cjfa-8193	359	33	na	na	SYM
cjfa-8193	359	34	0.75	0.75	NUM
cjfa-8193	359	35	0	0	NUM
cjfa-8193	359	36	0.62	0.62	NUM
cjfa-8193	359	37	α	α	NOUN
cjfa-8193	359	38	mean	mean	NOUN
cjfa-8193	359	39	equation	equation	NOUN
cjfa-8193	359	40	,	,	PUNCT
cjfa-8193	359	41	β	β	X
cjfa-8193	359	42	variance	variance	NOUN
cjfa-8193	359	43	equation	equation	NOUN
cjfa-8193	359	44	,	,	PUNCT
cjfa-8193	359	45	µ	µ	X
cjfa-8193	359	46	degrees	degree	NOUN
cjfa-8193	359	47	of	of	ADP
cjfa-8193	359	48	freedom	freedom	NOUN
cjfa-8193	359	49	.	.	PUNCT
cjfa-8193	360	1	s	s	PART
cjfa-8193	360	2	o	o	X
cjfa-8193	360	3	u	u	NOUN
cjfa-8193	360	4	r	r	NOUN
cjfa-8193	360	5	c	c	NOUN
cjfa-8193	360	6	e	e	NOUN
cjfa-8193	360	7	:	:	PUNCT
cjfa-8193	360	8	estimated	estimate	VERB
cjfa-8193	360	9	by	by	ADP
cjfa-8193	360	10	the	the	DET
cjfa-8193	360	11	authors	author	NOUN
cjfa-8193	360	12	using	use	VERB
cjfa-8193	360	13	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	360	14	7	7	X
cjfa-8193	360	15	.	.	PUNCT
cjfa-8193	361	1	we	we	PRON
cjfa-8193	361	2	turn	turn	VERB
cjfa-8193	361	3	now	now	ADV
cjfa-8193	361	4	to	to	ADP
cjfa-8193	361	5	the	the	DET
cjfa-8193	361	6	issue	issue	NOUN
cjfa-8193	361	7	of	of	ADP
cjfa-8193	361	8	identifying	identify	VERB
cjfa-8193	361	9	the	the	DET
cjfa-8193	361	10	most	most	ADV
cjfa-8193	361	11	efficient	efficient	ADJ
cjfa-8193	361	12	model(s	model(s	NOUN
cjfa-8193	361	13	)	)	PUNCT
cjfa-8193	361	14	from	from	ADP
cjfa-8193	361	15	the	the	DET
cjfa-8193	361	16	groups	group	NOUN
cjfa-8193	361	17	that	that	PRON
cjfa-8193	361	18	have	have	AUX
cjfa-8193	361	19	been	be	AUX
cjfa-8193	361	20	tested	test	VERB
cjfa-8193	361	21	.	.	PUNCT
cjfa-8193	362	1	the	the	DET
cjfa-8193	362	2	diagnostic	diagnostic	ADJ
cjfa-8193	362	3	tests	test	NOUN
cjfa-8193	362	4	of	of	ADP
cjfa-8193	362	5	the	the	DET
cjfa-8193	362	6	standardized	standardized	ADJ
cjfa-8193	362	7	residuals	residual	NOUN
cjfa-8193	362	8	(	(	PUNCT
cjfa-8193	362	9	table	table	NOUN
cjfa-8193	362	10	5	5	NUM
cjfa-8193	362	11	)	)	PUNCT
cjfa-8193	362	12	give	give	VERB
cjfa-8193	362	13	us	we	PRON
cjfa-8193	362	14	little	little	ADJ
cjfa-8193	362	15	help	help	NOUN
cjfa-8193	362	16	in	in	ADP
cjfa-8193	362	17	this	this	DET
cjfa-8193	362	18	respect	respect	NOUN
cjfa-8193	362	19	.	.	PUNCT
cjfa-8193	363	1	both	both	DET
cjfa-8193	363	2	arch(10	arch(10	ADJ
cjfa-8193	363	3	)	)	PUNCT
cjfa-8193	363	4	and	and	CCONJ
cjfa-8193	363	5	q2(10	q2(10	NOUN
cjfa-8193	363	6	)	)	PUNCT
cjfa-8193	363	7	statistics	statistic	NOUN
cjfa-8193	363	8	indicate	indicate	VERB
cjfa-8193	363	9	that	that	SCONJ
cjfa-8193	363	10	hetroskedasticity	hetroskedasticity	NOUN
cjfa-8193	363	11	has	have	AUX
cjfa-8193	363	12	not	not	PART
cjfa-8193	363	13	been	be	AUX
cjfa-8193	363	14	fully	fully	ADV
cjfa-8193	363	15	accounted	account	VERB
cjfa-8193	363	16	for	for	ADP
cjfa-8193	363	17	by	by	ADP
cjfa-8193	363	18	the	the	DET
cjfa-8193	363	19	models	model	NOUN
cjfa-8193	363	20	which	which	PRON
cjfa-8193	363	21	means	mean	VERB
cjfa-8193	363	22	the	the	DET
cjfa-8193	363	23	estimated	estimate	VERB
cjfa-8193	363	24	volatility	volatility	NOUN
cjfa-8193	363	25	equations	equation	NOUN
cjfa-8193	363	26	have	have	VERB
cjfa-8193	363	27	to	to	PART
cjfa-8193	363	28	be	be	AUX
cjfa-8193	363	29	treated	treat	VERB
cjfa-8193	363	30	with	with	ADP
cjfa-8193	363	31	some	some	DET
cjfa-8193	363	32	degree	degree	NOUN
cjfa-8193	363	33	of	of	ADP
cjfa-8193	363	34	caution	caution	NOUN
cjfa-8193	363	35	.	.	PUNCT
cjfa-8193	364	1	furthermore	furthermore	ADV
cjfa-8193	364	2	,	,	PUNCT
cjfa-8193	364	3	log	log	NOUN
cjfa-8193	364	4	likelihood	likelihood	NOUN
cjfa-8193	364	5	and	and	CCONJ
cjfa-8193	364	6	akaike	akaike	ADJ
cjfa-8193	364	7	information	information	NOUN
cjfa-8193	364	8	criteria	criterion	NOUN
cjfa-8193	364	9	based	base	VERB
cjfa-8193	364	10	tests	test	NOUN
cjfa-8193	364	11	all	all	PRON
cjfa-8193	364	12	have	have	VERB
cjfa-8193	364	13	approximately	approximately	ADV
cjfa-8193	364	14	similar	similar	ADJ
cjfa-8193	364	15	results	result	NOUN
cjfa-8193	364	16	;	;	PUNCT
cjfa-8193	364	17	this	this	PRON
cjfa-8193	364	18	suggests	suggest	VERB
cjfa-8193	364	19	they	they	PRON
cjfa-8193	364	20	provide	provide	VERB
cjfa-8193	364	21	minimal	minimal	ADJ
cjfa-8193	364	22	help	help	NOUN
cjfa-8193	364	23	in	in	ADP
cjfa-8193	364	24	distinguishing	distinguish	VERB
cjfa-8193	364	25	between	between	ADP
cjfa-8193	364	26	model	model	NOUN
cjfa-8193	364	27	sets	set	NOUN
cjfa-8193	364	28	on	on	ADP
cjfa-8193	364	29	the	the	DET
cjfa-8193	364	30	basis	basis	NOUN
cjfa-8193	364	31	of	of	ADP
cjfa-8193	364	32	model	model	NOUN
cjfa-8193	364	33	fit	fit	PROPN
cjfa-8193	364	34	.	.	PUNCT
cjfa-8193	365	1	we	we	PRON
cjfa-8193	365	2	can	can	AUX
cjfa-8193	365	3	conclude	conclude	VERB
cjfa-8193	365	4	from	from	ADP
cjfa-8193	365	5	this	this	PRON
cjfa-8193	365	6	that	that	SCONJ
cjfa-8193	365	7	alternative	alternative	ADJ
cjfa-8193	365	8	forecasting	forecasting	NOUN
cjfa-8193	365	9	-	-	PUNCT
cjfa-8193	365	10	based	base	VERB
cjfa-8193	365	11	testing	testing	NOUN
cjfa-8193	365	12	procedures	procedure	NOUN
cjfa-8193	365	13	will	will	AUX
cjfa-8193	365	14	be	be	AUX
cjfa-8193	365	15	required	require	VERB
cjfa-8193	365	16	.	.	PUNCT
cjfa-8193	366	1	it	it	PRON
cjfa-8193	366	2	can	can	AUX
cjfa-8193	366	3	be	be	AUX
cjfa-8193	366	4	noted	note	VERB
cjfa-8193	366	5	as	as	ADP
cjfa-8193	366	6	a	a	DET
cjfa-8193	366	7	caveat	caveat	NOUN
cjfa-8193	366	8	to	to	ADP
cjfa-8193	366	9	the	the	DET
cjfa-8193	366	10	above	above	ADJ
cjfa-8193	366	11	conclusion	conclusion	NOUN
cjfa-8193	366	12	however	however	ADV
cjfa-8193	366	13	,	,	PUNCT
cjfa-8193	366	14	that	that	SCONJ
cjfa-8193	366	15	for	for	ADP
cjfa-8193	366	16	all	all	DET
cjfa-8193	366	17	model	model	NOUN
cjfa-8193	366	18	sets	set	NOUN
cjfa-8193	366	19	,	,	PUNCT
cjfa-8193	366	20	akaike	akaike	ADJ
cjfa-8193	366	21	indicates	indicate	VERB
cjfa-8193	366	22	that	that	SCONJ
cjfa-8193	366	23	the	the	DET
cjfa-8193	366	24	normal	normal	ADJ
cjfa-8193	366	25	distribution	distribution	NOUN
cjfa-8193	366	26	produces	produce	VERB
cjfa-8193	366	27	the	the	DET
cjfa-8193	366	28	worst	bad	ADJ
cjfa-8193	366	29	performance	performance	NOUN
cjfa-8193	366	30	.	.	PUNCT
cjfa-8193	367	1	from	from	ADP
cjfa-8193	367	2	this	this	PRON
cjfa-8193	367	3	it	it	PRON
cjfa-8193	367	4	can	can	AUX
cjfa-8193	367	5	possibly	possibly	ADV
cjfa-8193	367	6	be	be	AUX
cjfa-8193	367	7	concluded	conclude	VERB
cjfa-8193	367	8	that	that	SCONJ
cjfa-8193	367	9	this	this	DET
cjfa-8193	367	10	distribution	distribution	NOUN
cjfa-8193	367	11	can	can	AUX
cjfa-8193	367	12	probably	probably	ADV
cjfa-8193	367	13	be	be	AUX
cjfa-8193	367	14	discounted	discount	VERB
cjfa-8193	367	15	at	at	ADP
cjfa-8193	367	16	the	the	DET
cjfa-8193	367	17	outset	outset	NOUN
cjfa-8193	367	18	.	.	PUNCT
cjfa-8193	368	1	forecasting	forecast	VERB
cjfa-8193	368	2	the	the	DET
cjfa-8193	368	3	jordanian	jordanian	ADJ
cjfa-8193	368	4	stock	stock	NOUN
cjfa-8193	368	5	index	index	PROPN
cjfa-8193	368	6	…	…	SYM
cjfa-8193	368	7	21	21	NUM
cjfa-8193	368	8	table	table	NOUN
cjfa-8193	368	9	5	5	NUM
cjfa-8193	368	10	.	.	PUNCT
cjfa-8193	369	1	diagnostic	diagnostic	ADJ
cjfa-8193	369	2	tests	test	NOUN
cjfa-8193	369	3	of	of	ADP
cjfa-8193	369	4	the	the	DET
cjfa-8193	369	5	standardised	standardised	ADJ
cjfa-8193	369	6	residuals	residual	NOUN
cjfa-8193	369	7	model	model	NOUN
cjfa-8193	369	8	distribution	distribution	NOUN
cjfa-8193	369	9	log	log	NOUN
cjfa-8193	369	10	likelihood	likelihood	NOUN
cjfa-8193	369	11	q2(10)α	q2(10)α	ADV
cjfa-8193	369	12	arch(10)α	arch(10)α	PROPN
cjfa-8193	369	13	akaike	akaike	ADJ
cjfa-8193	369	14	garch	garch	NOUN
cjfa-8193	369	15	normal	normal	ADJ
cjfa-8193	369	16	-4044.15	-4044.15	PROPN
cjfa-8193	369	17	37.14	37.14	NUM
cjfa-8193	369	18	(	(	PUNCT
cjfa-8193	369	19	0	0	NUM
cjfa-8193	369	20	)	)	PUNCT
cjfa-8193	369	21	3.49	3.49	NUM
cjfa-8193	369	22	(	(	PUNCT
cjfa-8193	369	23	0	0	NUM
cjfa-8193	369	24	)	)	PUNCT
cjfa-8193	369	25	2.22	2.22	NUM
cjfa-8193	369	26	student	student	NOUN
cjfa-8193	369	27	-3963.3	-3963.3	PROPN
cjfa-8193	369	28	31.31	31.31	NUM
cjfa-8193	369	29	(	(	PUNCT
cjfa-8193	369	30	0	0	NUM
cjfa-8193	369	31	)	)	PUNCT
cjfa-8193	369	32	2.92	2.92	NUM
cjfa-8193	369	33	(	(	PUNCT
cjfa-8193	369	34	0	0	NUM
cjfa-8193	369	35	)	)	PUNCT
cjfa-8193	369	36	2.18	2.18	NUM
cjfa-8193	369	37	ged	ge	VERB
cjfa-8193	369	38	-3966.62	-3966.62	PROPN
cjfa-8193	369	39	33.86	33.86	NUM
cjfa-8193	369	40	(	(	PUNCT
cjfa-8193	369	41	0	0	NUM
cjfa-8193	369	42	)	)	PUNCT
cjfa-8193	369	43	3.15	3.15	NUM
cjfa-8193	369	44	(	(	PUNCT
cjfa-8193	369	45	0	0	NUM
cjfa-8193	369	46	)	)	PUNCT
cjfa-8193	369	47	2.17	2.17	NUM
cjfa-8193	369	48	skewed	skewed	ADJ
cjfa-8193	369	49	student	student	NOUN
cjfa-8193	369	50	-3963.22	-3963.22	NOUN
cjfa-8193	369	51	31.29	31.29	NUM
cjfa-8193	369	52	(	(	PUNCT
cjfa-8193	369	53	0	0	NUM
cjfa-8193	369	54	)	)	PUNCT
cjfa-8193	369	55	2.92	2.92	NUM
cjfa-8193	369	56	(	(	PUNCT
cjfa-8193	369	57	0	0	NUM
cjfa-8193	369	58	)	)	PUNCT
cjfa-8193	369	59	2.17	2.17	NUM
cjfa-8193	369	60	egarch	egarch	NOUN
cjfa-8193	369	61	normal	normal	ADJ
cjfa-8193	369	62	-3980.23	-3980.23	PROPN
cjfa-8193	369	63	21.62	21.62	NUM
cjfa-8193	369	64	(	(	PUNCT
cjfa-8193	369	65	0	0	NUM
cjfa-8193	369	66	)	)	PUNCT
cjfa-8193	369	67	2.14	2.14	NUM
cjfa-8193	369	68	(	(	PUNCT
cjfa-8193	369	69	0.01	0.01	NUM
cjfa-8193	369	70	)	)	PUNCT
cjfa-8193	369	71	2.18	2.18	NUM
cjfa-8193	369	72	student	student	NOUN
cjfa-8193	369	73	-3893.84	-3893.84	PROPN
cjfa-8193	369	74	21.01	21.01	NUM
cjfa-8193	369	75	(	(	PUNCT
cjfa-8193	369	76	0	0	NUM
cjfa-8193	369	77	)	)	PUNCT
cjfa-8193	369	78	2.11	2.11	NUM
cjfa-8193	369	79	(	(	PUNCT
cjfa-8193	369	80	0.02	0.02	NUM
cjfa-8193	369	81	)	)	PUNCT
cjfa-8193	369	82	2.13	2.13	NUM
cjfa-8193	369	83	ged	ge	VERB
cjfa-8193	369	84	-3900.81	-3900.81	PROPN
cjfa-8193	369	85	21.28	21.28	NUM
cjfa-8193	369	86	(	(	PUNCT
cjfa-8193	369	87	0	0	NUM
cjfa-8193	369	88	)	)	PUNCT
cjfa-8193	369	89	2.12	2.12	NUM
cjfa-8193	369	90	(	(	PUNCT
cjfa-8193	369	91	0.01	0.01	NUM
cjfa-8193	369	92	)	)	PUNCT
cjfa-8193	369	93	2.13	2.13	NUM
cjfa-8193	369	94	skewed	skewed	ADJ
cjfa-8193	369	95	student	student	NOUN
cjfa-8193	369	96	-3890.96	-3890.96	PROPN
cjfa-8193	369	97	21.04	21.04	NUM
cjfa-8193	369	98	(	(	PUNCT
cjfa-8193	369	99	0	0	NUM
cjfa-8193	369	100	)	)	PUNCT
cjfa-8193	369	101	2.11	2.11	NUM
cjfa-8193	369	102	(	(	PUNCT
cjfa-8193	369	103	0.02	0.02	NUM
cjfa-8193	369	104	)	)	PUNCT
cjfa-8193	369	105	2.13	2.13	NUM
cjfa-8193	369	106	gjr	gjr	NOUN
cjfa-8193	369	107	-	-	PUNCT
cjfa-8193	369	108	garch	garch	NOUN
cjfa-8193	369	109	normal	normal	ADJ
cjfa-8193	369	110	-4043.82	-4043.82	PROPN
cjfa-8193	369	111	38.11	38.11	NUM
cjfa-8193	369	112	(	(	PUNCT
cjfa-8193	369	113	0	0	NUM
cjfa-8193	369	114	)	)	PUNCT
cjfa-8193	369	115	3.57	3.57	NUM
cjfa-8193	369	116	(	(	PUNCT
cjfa-8193	369	117	0	0	NUM
cjfa-8193	369	118	)	)	PUNCT
cjfa-8193	369	119	2.22	2.22	NUM
cjfa-8193	369	120	student	student	NOUN
cjfa-8193	369	121	-3963.12	-3963.12	PROPN
cjfa-8193	369	122	30.56	30.56	NUM
cjfa-8193	369	123	(	(	PUNCT
cjfa-8193	369	124	0	0	NUM
cjfa-8193	369	125	)	)	PUNCT
cjfa-8193	369	126	2.86	2.86	NUM
cjfa-8193	369	127	(	(	PUNCT
cjfa-8193	369	128	0	0	NUM
cjfa-8193	369	129	)	)	PUNCT
cjfa-8193	369	130	2.17	2.17	NUM
cjfa-8193	369	131	ged	ge	VERB
cjfa-8193	369	132	-3966.62	-3966.62	PROPN
cjfa-8193	369	133	34.01	34.01	NUM
cjfa-8193	369	134	(	(	PUNCT
cjfa-8193	369	135	0	0	NUM
cjfa-8193	369	136	)	)	PUNCT
cjfa-8193	369	137	3.17	3.17	NUM
cjfa-8193	369	138	(	(	PUNCT
cjfa-8193	369	139	0	0	NUM
cjfa-8193	369	140	)	)	PUNCT
cjfa-8193	369	141	2.17	2.17	NUM
cjfa-8193	369	142	skewed	skewed	ADJ
cjfa-8193	369	143	student	student	NOUN
cjfa-8193	369	144	-3963.07	-3963.07	PROPN
cjfa-8193	369	145	30.59	30.59	NUM
cjfa-8193	369	146	(	(	PUNCT
cjfa-8193	369	147	0	0	NUM
cjfa-8193	369	148	)	)	PUNCT
cjfa-8193	369	149	2.86	2.86	NUM
cjfa-8193	369	150	(	(	PUNCT
cjfa-8193	369	151	0	0	NUM
cjfa-8193	369	152	)	)	PUNCT
cjfa-8193	369	153	2.17	2.17	NUM
cjfa-8193	369	154	α	α	NOUN
cjfa-8193	369	155	the	the	DET
cjfa-8193	369	156	p	p	NOUN
cjfa-8193	369	157	-	-	PUNCT
cjfa-8193	369	158	values	value	NOUN
cjfa-8193	369	159	are	be	AUX
cjfa-8193	369	160	shown	show	VERB
cjfa-8193	369	161	in	in	ADP
cjfa-8193	369	162	brackets	bracket	NOUN
cjfa-8193	369	163	.	.	PUNCT
cjfa-8193	370	1	s	s	PART
cjfa-8193	370	2	o	o	X
cjfa-8193	370	3	u	u	NOUN
cjfa-8193	370	4	r	r	NOUN
cjfa-8193	370	5	c	c	NOUN
cjfa-8193	370	6	e	e	NOUN
cjfa-8193	370	7	:	:	PUNCT
cjfa-8193	370	8	estimated	estimate	VERB
cjfa-8193	370	9	by	by	ADP
cjfa-8193	370	10	the	the	DET
cjfa-8193	370	11	authors	author	NOUN
cjfa-8193	370	12	using	use	VERB
cjfa-8193	370	13	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	370	14	7	7	NUM
cjfa-8193	370	15	.	.	PUNCT
cjfa-8193	370	16	(	(	PUNCT
cjfa-8193	370	17	ii	ii	NOUN
cjfa-8193	370	18	)	)	PUNCT
cjfa-8193	370	19	 	 	SPACE
cjfa-8193	370	20	forecasting	forecasting	NOUN
cjfa-8193	370	21	based	base	VERB
cjfa-8193	370	22	evaluation	evaluation	NOUN
cjfa-8193	370	23	the	the	DET
cjfa-8193	370	24	superior	superior	ADJ
cjfa-8193	370	25	predictive	predictive	ADJ
cjfa-8193	370	26	ability	ability	NOUN
cjfa-8193	370	27	test	test	NOUN
cjfa-8193	370	28	can	can	AUX
cjfa-8193	370	29	be	be	AUX
cjfa-8193	370	30	used	use	VERB
cjfa-8193	370	31	for	for	ADP
cjfa-8193	370	32	comparing	compare	VERB
cjfa-8193	370	33	the	the	DET
cjfa-8193	370	34	performances	performance	NOUN
cjfa-8193	370	35	of	of	ADP
cjfa-8193	370	36	two	two	NUM
cjfa-8193	370	37	or	or	CCONJ
cjfa-8193	370	38	more	more	ADJ
cjfa-8193	370	39	forecasting	forecasting	NOUN
cjfa-8193	370	40	models	model	NOUN
cjfa-8193	370	41	.	.	PUNCT
cjfa-8193	371	1	forecasts	forecast	NOUN
cjfa-8193	371	2	are	be	AUX
cjfa-8193	371	3	evaluated	evaluate	VERB
cjfa-8193	371	4	using	use	VERB
cjfa-8193	371	5	a	a	DET
cjfa-8193	371	6	pre	pre	ADJ
cjfa-8193	371	7	-	-	ADJ
cjfa-8193	371	8	specified	specified	ADJ
cjfa-8193	371	9	loss	loss	NOUN
cjfa-8193	371	10	function	function	NOUN
cjfa-8193	371	11	with	with	ADP
cjfa-8193	371	12	the	the	DET
cjfa-8193	371	13	‘	'	PUNCT
cjfa-8193	371	14	best	good	ADJ
cjfa-8193	371	15	’	'	PUNCT
cjfa-8193	371	16	forecast	forecast	NOUN
cjfa-8193	371	17	model	model	NOUN
cjfa-8193	371	18	being	be	AUX
cjfa-8193	371	19	the	the	DET
cjfa-8193	371	20	one	one	NUM
cjfa-8193	371	21	producing	produce	VERB
cjfa-8193	371	22	the	the	DET
cjfa-8193	371	23	smallest	small	ADJ
cjfa-8193	371	24	expected	expect	VERB
cjfa-8193	371	25	loss	loss	NOUN
cjfa-8193	371	26	.	.	PUNCT
cjfa-8193	372	1	an	an	DET
cjfa-8193	372	2	important	important	ADJ
cjfa-8193	372	3	issue	issue	NOUN
cjfa-8193	372	4	that	that	SCONJ
cjfa-8193	372	5	researchers	researcher	NOUN
cjfa-8193	372	6	face	face	VERB
cjfa-8193	372	7	is	be	AUX
cjfa-8193	372	8	identifying	identify	VERB
cjfa-8193	372	9	what	what	PRON
cjfa-8193	372	10	the	the	DET
cjfa-8193	372	11	loss	loss	NOUN
cjfa-8193	372	12	function	function	NOUN
cjfa-8193	372	13	is	be	AUX
cjfa-8193	372	14	estimated	estimate	VERB
cjfa-8193	372	15	against	against	ADP
cjfa-8193	372	16	.	.	PUNCT
cjfa-8193	373	1	for	for	ADP
cjfa-8193	373	2	the	the	DET
cjfa-8193	373	3	purposes	purpose	NOUN
cjfa-8193	373	4	of	of	ADP
cjfa-8193	373	5	this	this	DET
cjfa-8193	373	6	paper	paper	NOUN
cjfa-8193	373	7	losses	loss	NOUN
cjfa-8193	373	8	are	be	AUX
cjfa-8193	373	9	estimated	estimate	VERB
cjfa-8193	373	10	relative	relative	ADJ
cjfa-8193	373	11	to	to	ADP
cjfa-8193	373	12	the	the	DET
cjfa-8193	373	13	observed	observed	ADJ
cjfa-8193	373	14	returns	return	NOUN
cjfa-8193	373	15	.	.	PUNCT
cjfa-8193	374	1	the	the	DET
cjfa-8193	374	2	two	two	NUM
cjfa-8193	374	3	potential	potential	ADJ
cjfa-8193	374	4	loss	loss	NOUN
cjfa-8193	374	5	functions	function	NOUN
cjfa-8193	374	6	used	use	VERB
cjfa-8193	374	7	by	by	ADP
cjfa-8193	374	8	spa	spa	NOUN
cjfa-8193	374	9	are	be	AUX
cjfa-8193	374	10	the	the	DET
cjfa-8193	374	11	mean	mean	ADJ
cjfa-8193	374	12	squared	square	VERB
cjfa-8193	374	13	error	error	NOUN
cjfa-8193	374	14	(	(	PUNCT
cjfa-8193	374	15	mse	mse	NOUN
cjfa-8193	374	16	)	)	PUNCT
cjfa-8193	374	17	and	and	CCONJ
cjfa-8193	374	18	mean	mean	VERB
cjfa-8193	374	19	absolute	absolute	ADJ
cjfa-8193	374	20	deviation	deviation	NOUN
cjfa-8193	374	21	(	(	PUNCT
cjfa-8193	374	22	mad	mad	ADJ
cjfa-8193	374	23	)	)	PUNCT
cjfa-8193	374	24	.	.	PUNCT
cjfa-8193	375	1	the	the	DET
cjfa-8193	375	2	losses	loss	NOUN
cjfa-8193	375	3	estimated	estimate	VERB
cjfa-8193	375	4	from	from	ADP
cjfa-8193	375	5	the	the	DET
cjfa-8193	375	6	choh	choh	NOUN
cjfa-8193	375	7	.	.	PUNCT
cjfa-8193	376	1	al	al	PROPN
cjfa-8193	376	2	-	-	PUNCT
cjfa-8193	376	3	hajieh	hajieh	PROPN
cjfa-8193	376	4	,	,	PUNCT
cjfa-8193	376	5	h.	h.	PROPN
cjfa-8193	376	6	alnemer	alnemer	PROPN
cjfa-8193	376	7	,	,	PUNCT
cjfa-8193	376	8	t.	t.	PROPN
cjfa-8193	376	9	rodgers	rodgers	PROPN
cjfa-8193	376	10	,	,	PUNCT
cjfa-8193	376	11	j.	j.	PROPN
cjfa-8193	376	12	niklewski22	niklewski22	PROPN
cjfa-8193	376	13	sen	sen	PROPN
cjfa-8193	376	14	function	function	PROPN
cjfa-8193	376	15	are	be	AUX
cjfa-8193	376	16	then	then	ADV
cjfa-8193	376	17	compared	compare	VERB
cjfa-8193	376	18	against	against	ADP
cjfa-8193	376	19	a	a	DET
cjfa-8193	376	20	benchmark	benchmark	NOUN
cjfa-8193	376	21	model	model	NOUN
cjfa-8193	376	22	.	.	PUNCT
cjfa-8193	377	1	identifying	identify	VERB
cjfa-8193	377	2	an	an	DET
cjfa-8193	377	3	appropriate	appropriate	ADJ
cjfa-8193	377	4	benchmark	benchmark	NOUN
cjfa-8193	377	5	to	to	PART
cjfa-8193	377	6	use	use	VERB
cjfa-8193	377	7	is	be	AUX
cjfa-8193	377	8	another	another	DET
cjfa-8193	377	9	important	important	ADJ
cjfa-8193	377	10	issue	issue	NOUN
cjfa-8193	377	11	in	in	ADP
cjfa-8193	377	12	respect	respect	NOUN
cjfa-8193	377	13	to	to	ADP
cjfa-8193	377	14	this	this	DET
cjfa-8193	377	15	methodology	methodology	NOUN
cjfa-8193	377	16	.	.	PUNCT
cjfa-8193	378	1	in	in	ADP
cjfa-8193	378	2	this	this	DET
cjfa-8193	378	3	paper	paper	NOUN
cjfa-8193	378	4	we	we	PRON
cjfa-8193	378	5	benchmark	benchmark	VERB
cjfa-8193	378	6	against	against	ADP
cjfa-8193	378	7	a	a	DET
cjfa-8193	378	8	random	random	ADJ
cjfa-8193	378	9	walk	walk	NOUN
cjfa-8193	378	10	.	.	PUNCT
cjfa-8193	379	1	the	the	DET
cjfa-8193	379	2	result	result	NOUN
cjfa-8193	379	3	presented	present	VERB
cjfa-8193	379	4	in	in	ADP
cjfa-8193	379	5	table	table	NOUN
cjfa-8193	379	6	6	6	NUM
cjfa-8193	379	7	below	below	ADV
cjfa-8193	379	8	identify	identify	VERB
cjfa-8193	379	9	that	that	SCONJ
cjfa-8193	379	10	gjr	gjr	NOUN
cjfa-8193	379	11	-	-	PUNCT
cjfa-8193	379	12	garch	garch	NOUN
cjfa-8193	379	13	with	with	ADP
cjfa-8193	379	14	skewed	skewed	ADJ
cjfa-8193	379	15	distribution	distribution	NOUN
cjfa-8193	379	16	produces	produce	VERB
cjfa-8193	379	17	the	the	DET
cjfa-8193	379	18	smallest	small	ADJ
cjfa-8193	379	19	loss	loss	NOUN
cjfa-8193	379	20	and	and	CCONJ
cjfa-8193	379	21	is	be	AUX
cjfa-8193	379	22	therefore	therefore	ADV
cjfa-8193	379	23	the	the	DET
cjfa-8193	379	24	best	well	ADV
cjfa-8193	379	25	fitting	fitting	ADJ
cjfa-8193	379	26	model	model	NOUN
cjfa-8193	379	27	.	.	PUNCT
cjfa-8193	380	1	these	these	DET
cjfa-8193	380	2	findings	finding	NOUN
cjfa-8193	380	3	are	be	AUX
cjfa-8193	380	4	consistent	consistent	ADJ
cjfa-8193	380	5	with	with	ADP
cjfa-8193	380	6	those	those	PRON
cjfa-8193	380	7	of	of	ADP
cjfa-8193	380	8	marcucci	marcucci	PROPN
cjfa-8193	380	9	(	(	PUNCT
cjfa-8193	380	10	2005	2005	NUM
cjfa-8193	380	11	)	)	PUNCT
cjfa-8193	380	12	and	and	CCONJ
cjfa-8193	380	13	awartani	awartani	NOUN
cjfa-8193	380	14	and	and	CCONJ
cjfa-8193	380	15	corradi	corradi	NOUN
cjfa-8193	380	16	(	(	PUNCT
cjfa-8193	380	17	2005	2005	NUM
cjfa-8193	380	18	)	)	PUNCT
cjfa-8193	380	19	.	.	PUNCT
cjfa-8193	381	1	the	the	DET
cjfa-8193	381	2	latter	latter	ADJ
cjfa-8193	381	3	found	find	VERB
cjfa-8193	381	4	garch	garch	NOUN
cjfa-8193	381	5	-	-	PUNCT
cjfa-8193	381	6	n	n	NOUN
cjfa-8193	381	7	to	to	PART
cjfa-8193	381	8	be	be	AUX
cjfa-8193	381	9	outperformed	outperform	VERB
cjfa-8193	381	10	by	by	ADP
cjfa-8193	381	11	both	both	PRON
cjfa-8193	381	12	egarch	egarch	NOUN
cjfa-8193	381	13	and	and	CCONJ
cjfa-8193	381	14	gjr	gjr	ADJ
cjfa-8193	381	15	-	-	PUNCT
cjfa-8193	381	16	garch	garch	NOUN
cjfa-8193	381	17	models	model	NOUN
cjfa-8193	381	18	across	across	ADP
cjfa-8193	381	19	different	different	ADJ
cjfa-8193	381	20	forecast	forecast	NOUN
cjfa-8193	381	21	horizons	horizon	NOUN
cjfa-8193	381	22	.	.	PUNCT
cjfa-8193	382	1	table	table	NOUN
cjfa-8193	382	2	6	6	NUM
cjfa-8193	382	3	.	.	PUNCT
cjfa-8193	383	1	superior	superior	ADJ
cjfa-8193	383	2	predictive	predictive	ADJ
cjfa-8193	383	3	ability	ability	NOUN
cjfa-8193	383	4	tests	test	VERB
cjfa-8193	383	5	performance	performance	NOUN
cjfa-8193	383	6	model	model	NOUN
cjfa-8193	383	7	sample	sample	NOUN
cjfa-8193	383	8	loss	loss	NOUN
cjfa-8193	383	9	(	(	PUNCT
cjfa-8193	383	10	mse*103	mse*103	NOUN
cjfa-8193	383	11	)	)	PUNCT
cjfa-8193	383	12	t	t	NOUN
cjfa-8193	383	13	-	-	PUNCT
cjfa-8193	383	14	statistic	statistic	NOUN
cjfa-8193	383	15	p	p	NOUN
cjfa-8193	383	16	-	-	PUNCT
cjfa-8193	383	17	value	value	NOUN
cjfa-8193	383	18	most	most	ADV
cjfa-8193	383	19	significant	significant	ADJ
cjfa-8193	383	20	gjr	gjr	ADJ
cjfa-8193	383	21	-	-	PUNCT
cjfa-8193	383	22	garch	garch	NOUN
cjfa-8193	383	23	-	-	PUNCT
cjfa-8193	383	24	skewed	skewed	ADJ
cjfa-8193	383	25	student	student	NOUN
cjfa-8193	383	26	0.00039	0.00039	NUM
cjfa-8193	383	27	16.75819	16.75819	NUM
cjfa-8193	383	28	0	0	NUM
cjfa-8193	383	29	best	good	ADJ
cjfa-8193	383	30	gjr	gjr	NOUN
cjfa-8193	383	31	-	-	PUNCT
cjfa-8193	383	32	garch	garch	NOUN
cjfa-8193	383	33	-	-	PUNCT
cjfa-8193	383	34	skewed	skewed	ADJ
cjfa-8193	383	35	student	student	NOUN
cjfa-8193	383	36	0.00039	0.00039	NUM
cjfa-8193	383	37	16.75819	16.75819	NUM
cjfa-8193	383	38	0	0	NUM
cjfa-8193	384	1	model_25	model_25	NOUN
cjfa-8193	384	2	%	%	NOUN
cjfa-8193	384	3	gjr	gjr	NOUN
cjfa-8193	384	4	-	-	PUNCT
cjfa-8193	384	5	garch	garch	NOUN
cjfa-8193	384	6	-	-	PUNCT
cjfa-8193	384	7	student	student	NOUN
cjfa-8193	384	8	-	-	PUNCT
cjfa-8193	384	9	t	t	NOUN
cjfa-8193	384	10	0.00043	0.00043	NUM
cjfa-8193	384	11	16.75729	16.75729	NUM
cjfa-8193	384	12	0	0	NUM
cjfa-8193	384	13	median	median	ADJ
cjfa-8193	384	14	garch	garch	NOUN
cjfa-8193	384	15	-	-	PUNCT
cjfa-8193	384	16	ged	ge	VERB
cjfa-8193	384	17	0.00049	0.00049	NUM
cjfa-8193	384	18	16.75627	16.75627	NUM
cjfa-8193	384	19	0	0	NUM
cjfa-8193	385	1	model_75	model_75	PROPN
cjfa-8193	385	2	%	%	NOUN
cjfa-8193	385	3	egarch	egarch	NOUN
cjfa-8193	385	4	-	-	PUNCT
cjfa-8193	385	5	normal	normal	ADJ
cjfa-8193	385	6	0.02761	0.02761	NUM
cjfa-8193	385	7	16.63402	16.63402	NUM
cjfa-8193	385	8	0	0	NUM
cjfa-8193	385	9	worst	bad	ADJ
cjfa-8193	385	10	egarch	egarch	NOUN
cjfa-8193	385	11	-	-	PUNCT
cjfa-8193	385	12	skewed	skew	VERB
cjfa-8193	385	13	student	student	NOUN
cjfa-8193	385	14	0.03208	0.03208	NUM
cjfa-8193	385	15	16.59516	16.59516	NUM
cjfa-8193	385	16	0	0	NUM
cjfa-8193	385	17	s	s	PART
cjfa-8193	385	18	o	o	NOUN
cjfa-8193	385	19	u	u	NOUN
cjfa-8193	385	20	r	r	NOUN
cjfa-8193	385	21	c	c	NOUN
cjfa-8193	385	22	e	e	NOUN
cjfa-8193	385	23	:	:	PUNCT
cjfa-8193	385	24	estimated	estimate	VERB
cjfa-8193	385	25	by	by	ADP
cjfa-8193	385	26	the	the	DET
cjfa-8193	385	27	authors	author	NOUN
cjfa-8193	385	28	using	use	VERB
cjfa-8193	385	29	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	385	30	7	7	NUM
cjfa-8193	385	31	and	and	CCONJ
cjfa-8193	385	32	mulcom	mulcom	PROPN
cjfa-8193	385	33	3.0	3.0	NUM
cjfa-8193	385	34	package	package	NOUN
cjfa-8193	385	35	(	(	PUNCT
cjfa-8193	385	36	hansen	hansen	NOUN
cjfa-8193	385	37	,	,	PUNCT
cjfa-8193	385	38	and	and	CCONJ
cjfa-8193	385	39	lunde	lunde	NOUN
cjfa-8193	385	40	2014	2014	NUM
cjfa-8193	385	41	)	)	PUNCT
cjfa-8193	385	42	.	.	PUNCT
cjfa-8193	386	1	forecasts	forecast	NOUN
cjfa-8193	386	2	can	can	AUX
cjfa-8193	386	3	also	also	ADV
cjfa-8193	386	4	be	be	AUX
cjfa-8193	386	5	tested	test	VERB
cjfa-8193	386	6	using	use	VERB
cjfa-8193	386	7	the	the	DET
cjfa-8193	386	8	model	model	NOUN
cjfa-8193	386	9	confidence	confidence	NOUN
cjfa-8193	386	10	set	set	NOUN
cjfa-8193	386	11	(	(	PUNCT
cjfa-8193	386	12	mcs	mcs	NOUN
cjfa-8193	386	13	)	)	PUNCT
cjfa-8193	386	14	procedure	procedure	NOUN
cjfa-8193	386	15	.	.	PUNCT
cjfa-8193	387	1	this	this	PRON
cjfa-8193	387	2	uses	use	VERB
cjfa-8193	387	3	the	the	DET
cjfa-8193	387	4	same	same	ADJ
cjfa-8193	387	5	loss	loss	NOUN
cjfa-8193	387	6	function	function	NOUN
cjfa-8193	387	7	as	as	ADP
cjfa-8193	387	8	spa	spa	NOUN
cjfa-8193	387	9	but	but	CCONJ
cjfa-8193	387	10	requires	require	VERB
cjfa-8193	387	11	no	no	DET
cjfa-8193	387	12	benchmark	benchmark	NOUN
cjfa-8193	387	13	.	.	PUNCT
cjfa-8193	388	1	it	it	PRON
cjfa-8193	388	2	identifies	identify	VERB
cjfa-8193	388	3	efficient	efficient	ADJ
cjfa-8193	388	4	model	model	NOUN
cjfa-8193	388	5	sets	set	NOUN
cjfa-8193	388	6	at	at	ADP
cjfa-8193	388	7	different	different	ADJ
cjfa-8193	388	8	levels	level	NOUN
cjfa-8193	388	9	of	of	ADP
cjfa-8193	388	10	confidence	confidence	NOUN
cjfa-8193	388	11	.	.	PUNCT
cjfa-8193	389	1	hansen	hansen	PROPN
cjfa-8193	389	2	and	and	CCONJ
cjfa-8193	389	3	lunde	lunde	PROPN
cjfa-8193	389	4	state	state	PROPN
cjfa-8193	389	5	“	"	PUNCT
cjfa-8193	389	6	the	the	DET
cjfa-8193	389	7	set	set	NOUN
cjfa-8193	389	8	,	,	PUNCT
cjfa-8193	389	9	,	,	PUNCT
cjfa-8193	389	10	that	that	PRON
cjfa-8193	389	11	consists	consist	VERB
cjfa-8193	389	12	of	of	ADP
cjfa-8193	389	13	the	the	DET
cjfa-8193	389	14	‘	'	PUNCT
cjfa-8193	389	15	best	good	ADJ
cjfa-8193	389	16	’	'	PUNCT
cjfa-8193	389	17	model(s	model(s	NOUN
cjfa-8193	389	18	)	)	PUNCT
cjfa-8193	389	19	from	from	ADP
cjfa-8193	389	20	a	a	DET
cjfa-8193	389	21	collection	collection	NOUN
cjfa-8193	389	22	of	of	ADP
cjfa-8193	389	23	models	model	NOUN
cjfa-8193	389	24	,	,	PUNCT
cjfa-8193	389	25	;	;	PUNCT
cjfa-8193	389	26	where	where	SCONJ
cjfa-8193	389	27	‘	'	PUNCT
cjfa-8193	389	28	best	good	ADJ
cjfa-8193	389	29	’	'	PUNCT
cjfa-8193	389	30	is	be	AUX
cjfa-8193	389	31	defined	define	VERB
cjfa-8193	389	32	in	in	ADP
cjfa-8193	389	33	terms	term	NOUN
cjfa-8193	389	34	of	of	ADP
cjfa-8193	389	35	a	a	DET
cjfa-8193	389	36	criterion	criterion	NOUN
cjfa-8193	389	37	that	that	PRON
cjfa-8193	389	38	is	be	AUX
cjfa-8193	389	39	user	user	NOUN
cjfa-8193	389	40	-	-	PUNCT
cjfa-8193	389	41	specified	specify	VERB
cjfa-8193	389	42	.	.	PUNCT
cjfa-8193	390	1	the	the	DET
cjfa-8193	390	2	mcs	mcs	PROPN
cjfa-8193	390	3	procedure	procedure	NOUN
cjfa-8193	390	4	yields	yield	VERB
cjfa-8193	390	5	a	a	DET
cjfa-8193	390	6	model	model	NOUN
cjfa-8193	390	7	confidence	confidence	NOUN
cjfa-8193	390	8	set	set	NOUN
cjfa-8193	390	9	,	,	PUNCT
cjfa-8193	390	10	,	,	PUNCT
cjfa-8193	390	11	that	that	PRON
cjfa-8193	390	12	is	be	AUX
cjfa-8193	390	13	a	a	DET
cjfa-8193	390	14	set	set	NOUN
cjfa-8193	390	15	of	of	ADP
cjfa-8193	390	16	models	model	NOUN
cjfa-8193	390	17	constructed	construct	VERB
cjfa-8193	390	18	to	to	PART
cjfa-8193	390	19	contain	contain	VERB
cjfa-8193	390	20	the	the	DET
cjfa-8193	390	21	best	good	ADJ
cjfa-8193	390	22	models	model	NOUN
cjfa-8193	390	23	with	with	ADP
cjfa-8193	390	24	a	a	DET
cjfa-8193	390	25	given	give	VERB
cjfa-8193	390	26	level	level	NOUN
cjfa-8193	390	27	of	of	ADP
cjfa-8193	390	28	confidence	confidence	NOUN
cjfa-8193	390	29	.	.	PUNCT
cjfa-8193	391	1	the	the	DET
cjfa-8193	391	2	models	model	NOUN
cjfa-8193	391	3	in	in	ADP
cjfa-8193	391	4	are	be	AUX
cjfa-8193	391	5	evaluated	evaluate	VERB
cjfa-8193	391	6	using	use	VERB
cjfa-8193	391	7	sample	sample	NOUN
cjfa-8193	391	8	information	information	NOUN
cjfa-8193	391	9	about	about	ADP
cjfa-8193	391	10	the	the	DET
cjfa-8193	391	11	relative	relative	ADJ
cjfa-8193	391	12	performances	performance	NOUN
cjfa-8193	391	13	of	of	ADP
cjfa-8193	391	14	the	the	DET
cjfa-8193	391	15	models	model	NOUN
cjfa-8193	391	16	in	in	ADP
cjfa-8193	391	17	”	"	PUNCT
cjfa-8193	391	18	.	.	PUNCT
cjfa-8193	392	1	(	(	PUNCT
cjfa-8193	392	2	hansen	hansen	NOUN
cjfa-8193	392	3	and	and	CCONJ
cjfa-8193	392	4	lunde	lunde	PROPN
cjfa-8193	392	5	2014	2014	NUM
cjfa-8193	392	6	,	,	PUNCT
cjfa-8193	392	7	16	16	NUM
cjfa-8193	392	8	)	)	PUNCT
cjfa-8193	392	9	.	.	PUNCT
cjfa-8193	393	1	the	the	DET
cjfa-8193	393	2	result	result	NOUN
cjfa-8193	393	3	of	of	ADP
cjfa-8193	393	4	mcs	mcs	PROPN
cjfa-8193	393	5	presented	present	VERB
cjfa-8193	393	6	in	in	ADP
cjfa-8193	393	7	table	table	NOUN
cjfa-8193	393	8	7	7	NUM
cjfa-8193	393	9	identifies	identify	VERB
cjfa-8193	393	10	that	that	SCONJ
cjfa-8193	393	11	the	the	DET
cjfa-8193	393	12	90	90	NUM
cjfa-8193	393	13	%	%	NOUN
cjfa-8193	393	14	confidence	confidence	NOUN
cjfa-8193	393	15	model	model	NOUN
cjfa-8193	393	16	set	set	VERB
cjfa-8193	393	17	consists	consist	VERB
cjfa-8193	393	18	of	of	ADP
cjfa-8193	393	19	a	a	DET
cjfa-8193	393	20	single	single	ADJ
cjfa-8193	393	21	model	model	NOUN
cjfa-8193	393	22	;	;	PUNCT
cjfa-8193	393	23	namely	namely	ADV
cjfa-8193	393	24	,	,	PUNCT
cjfa-8193	393	25	gjr	gjr	NOUN
cjfa-8193	393	26	-	-	PUNCT
cjfa-8193	393	27	garch	garch	NOUN
cjfa-8193	393	28	with	with	ADP
cjfa-8193	393	29	skewed	skewed	ADJ
cjfa-8193	393	30	student	student	NOUN
cjfa-8193	393	31	distribution	distribution	NOUN
cjfa-8193	393	32	.	.	PUNCT
cjfa-8193	394	1	forecasting	forecast	VERB
cjfa-8193	394	2	the	the	DET
cjfa-8193	394	3	jordanian	jordanian	ADJ
cjfa-8193	394	4	stock	stock	NOUN
cjfa-8193	394	5	index	index	PROPN
cjfa-8193	394	6	…	…	PUNCT
cjfa-8193	394	7	23	23	NUM
cjfa-8193	394	8	table	table	NOUN
cjfa-8193	394	9	7	7	NUM
cjfa-8193	394	10	.	.	PUNCT
cjfa-8193	394	11	model	model	NOUN
cjfa-8193	394	12	confidence	confidence	NOUN
cjfa-8193	394	13	set	set	VERB
cjfa-8193	394	14	tests	test	NOUN
cjfa-8193	394	15	model	model	VERB
cjfa-8193	394	16	mse*103	mse*103	PROPN
cjfa-8193	394	17	p	p	ADJ
cjfa-8193	394	18	-	-	PUNCT
cjfa-8193	394	19	value	value	NOUN
cjfa-8193	394	20	garch	garch	NOUN
cjfa-8193	394	21	-	-	PUNCT
cjfa-8193	394	22	normal	normal	ADJ
cjfa-8193	394	23	0.00041	0.00041	NUM
cjfa-8193	394	24	0	0	NUM
cjfa-8193	394	25	garch	garch	NOUN
cjfa-8193	394	26	-	-	PUNCT
cjfa-8193	394	27	student	student	NOUN
cjfa-8193	394	28	-	-	PUNCT
cjfa-8193	394	29	t	t	NOUN
cjfa-8193	394	30	0.00047	0.00047	NUM
cjfa-8193	394	31	0	0	NUM
cjfa-8193	394	32	garch	garch	NOUN
cjfa-8193	394	33	-	-	PUNCT
cjfa-8193	394	34	ged	ge	VERB
cjfa-8193	394	35	0.00049	0.00049	NUM
cjfa-8193	394	36	0	0	NUM
cjfa-8193	394	37	garch	garch	NOUN
cjfa-8193	394	38	-	-	PUNCT
cjfa-8193	394	39	skewed	skew	VERB
cjfa-8193	394	40	student	student	NOUN
cjfa-8193	394	41	0.00041	0.00041	NOUN
cjfa-8193	394	42	0	0	NUM
cjfa-8193	394	43	egarch	egarch	NOUN
cjfa-8193	394	44	-	-	PUNCT
cjfa-8193	394	45	normal	normal	ADJ
cjfa-8193	394	46	0.02761	0.02761	NUM
cjfa-8193	394	47	0	0	NUM
cjfa-8193	394	48	egarch	egarch	NOUN
cjfa-8193	394	49	-	-	PUNCT
cjfa-8193	394	50	student	student	NOUN
cjfa-8193	394	51	-	-	PUNCT
cjfa-8193	394	52	t	t	NOUN
cjfa-8193	394	53	0.03117	0.03117	NUM
cjfa-8193	394	54	0	0	NUM
cjfa-8193	394	55	egarch	egarch	NOUN
cjfa-8193	394	56	-	-	PUNCT
cjfa-8193	394	57	ged	ge	VERB
cjfa-8193	394	58	0.02926	0.02926	NUM
cjfa-8193	394	59	0	0	NUM
cjfa-8193	394	60	egarch	egarch	NOUN
cjfa-8193	394	61	-	-	PUNCT
cjfa-8193	394	62	skewed	skew	VERB
cjfa-8193	394	63	student	student	NOUN
cjfa-8193	394	64	0.03208	0.03208	NUM
cjfa-8193	394	65	0	0	NUM
cjfa-8193	394	66	gjr	gjr	NOUN
cjfa-8193	394	67	-	-	PUNCT
cjfa-8193	394	68	garch	garch	NOUN
cjfa-8193	394	69	-	-	PUNCT
cjfa-8193	394	70	normal	normal	ADJ
cjfa-8193	394	71	0.00047	0.00047	NUM
cjfa-8193	394	72	0	0	NUM
cjfa-8193	394	73	gjr	gjr	NOUN
cjfa-8193	394	74	-	-	PUNCT
cjfa-8193	394	75	garch	garch	NOUN
cjfa-8193	394	76	-	-	PUNCT
cjfa-8193	394	77	student	student	NOUN
cjfa-8193	394	78	-	-	PUNCT
cjfa-8193	394	79	t	t	NOUN
cjfa-8193	394	80	0.00043	0.00043	NUM
cjfa-8193	394	81	0	0	NUM
cjfa-8193	394	82	gjr	gjr	NOUN
cjfa-8193	394	83	-	-	PUNCT
cjfa-8193	394	84	garch	garch	NOUN
cjfa-8193	394	85	-	-	PUNCT
cjfa-8193	394	86	ged	ge	VERB
cjfa-8193	394	87	0.0005	0.0005	NUM
cjfa-8193	394	88	0	0	NUM
cjfa-8193	394	89	gjr	gjr	NOUN
cjfa-8193	394	90	-	-	PUNCT
cjfa-8193	394	91	garch	garch	NOUN
cjfa-8193	394	92	-	-	PUNCT
cjfa-8193	394	93	skewed	skewed	ADJ
cjfa-8193	394	94	student	student	NOUN
cjfa-8193	394	95	0.00039	0.00039	NUM
cjfa-8193	394	96	1.0000	1.0000	NUM
cjfa-8193	394	97	*	*	PUNCT
cjfa-8193	394	98	*	*	PUNCT
cjfa-8193	394	99	90	90	NUM
cjfa-8193	394	100	%	%	NOUN
cjfa-8193	394	101	model	model	NOUN
cjfa-8193	394	102	confidence	confidence	NOUN
cjfa-8193	394	103	set	set	VERB
cjfa-8193	394	104	.	.	PUNCT
cjfa-8193	395	1	s	s	PART
cjfa-8193	395	2	o	o	X
cjfa-8193	395	3	u	u	NOUN
cjfa-8193	395	4	r	r	NOUN
cjfa-8193	395	5	c	c	NOUN
cjfa-8193	395	6	e	e	NOUN
cjfa-8193	395	7	:	:	PUNCT
cjfa-8193	395	8	estimated	estimate	VERB
cjfa-8193	395	9	by	by	ADP
cjfa-8193	395	10	the	the	DET
cjfa-8193	395	11	authors	author	NOUN
cjfa-8193	395	12	using	use	VERB
cjfa-8193	395	13	oxmetricstm	oxmetricstm	NOUN
cjfa-8193	395	14	7	7	NUM
cjfa-8193	395	15	and	and	CCONJ
cjfa-8193	395	16	mulcom	mulcom	PROPN
cjfa-8193	395	17	3.0	3.0	NUM
cjfa-8193	395	18	package	package	NOUN
cjfa-8193	395	19	(	(	PUNCT
cjfa-8193	395	20	hansen	hansen	NOUN
cjfa-8193	395	21	,	,	PUNCT
cjfa-8193	395	22	and	and	CCONJ
cjfa-8193	395	23	lunde	lunde	NOUN
cjfa-8193	395	24	2014	2014	NUM
cjfa-8193	395	25	)	)	PUNCT
cjfa-8193	395	26	.	.	PUNCT
cjfa-8193	396	1	discussion	discussion	NOUN
cjfa-8193	396	2	of	of	ADP
cjfa-8193	396	3	findings	finding	NOUN
cjfa-8193	396	4	and	and	CCONJ
cjfa-8193	396	5	conclusions	conclusion	NOUN
cjfa-8193	396	6	given	give	VERB
cjfa-8193	396	7	the	the	DET
cjfa-8193	396	8	large	large	ADJ
cjfa-8193	396	9	differences	difference	NOUN
cjfa-8193	396	10	between	between	ADP
cjfa-8193	396	11	developed	develop	VERB
cjfa-8193	396	12	and	and	CCONJ
cjfa-8193	396	13	emerging	emerge	VERB
cjfa-8193	396	14	markets	market	NOUN
cjfa-8193	396	15	,	,	PUNCT
cjfa-8193	396	16	it	it	PRON
cjfa-8193	396	17	is	be	AUX
cjfa-8193	396	18	possibly	possibly	ADV
cjfa-8193	396	19	a	a	DET
cjfa-8193	396	20	little	little	ADJ
cjfa-8193	396	21	surprising	surprising	ADJ
cjfa-8193	396	22	that	that	SCONJ
cjfa-8193	396	23	the	the	DET
cjfa-8193	396	24	result	result	NOUN
cjfa-8193	396	25	of	of	ADP
cjfa-8193	396	26	our	our	PRON
cjfa-8193	396	27	study	study	NOUN
cjfa-8193	396	28	,	,	PUNCT
cjfa-8193	396	29	made	make	VERB
cjfa-8193	396	30	in	in	ADP
cjfa-8193	396	31	respect	respect	NOUN
cjfa-8193	396	32	to	to	ADP
cjfa-8193	396	33	jordan	jordan	PROPN
cjfa-8193	396	34	,	,	PUNCT
cjfa-8193	396	35	are	be	AUX
cjfa-8193	396	36	consistent	consistent	ADJ
cjfa-8193	396	37	with	with	ADP
cjfa-8193	396	38	previous	previous	ADJ
cjfa-8193	396	39	studies	study	NOUN
cjfa-8193	396	40	made	make	VERB
cjfa-8193	396	41	of	of	ADP
cjfa-8193	396	42	developed	develop	VERB
cjfa-8193	396	43	markets	market	NOUN
cjfa-8193	396	44	.	.	PUNCT
cjfa-8193	397	1	for	for	ADP
cjfa-8193	397	2	example	example	NOUN
cjfa-8193	397	3	,	,	PUNCT
cjfa-8193	397	4	engle	engle	PROPN
cjfa-8193	397	5	and	and	CCONJ
cjfa-8193	397	6	ng	ng	PROPN
cjfa-8193	397	7	(	(	PUNCT
cjfa-8193	397	8	1993	1993	NUM
cjfa-8193	397	9	)	)	PUNCT
cjfa-8193	397	10	,	,	PUNCT
cjfa-8193	397	11	examining	examine	VERB
cjfa-8193	397	12	japanese	japanese	ADJ
cjfa-8193	397	13	stock	stock	NOUN
cjfa-8193	397	14	return	return	NOUN
cjfa-8193	397	15	also	also	ADV
cjfa-8193	397	16	found	find	VERB
cjfa-8193	397	17	strong	strong	ADJ
cjfa-8193	397	18	support	support	NOUN
cjfa-8193	397	19	for	for	ADP
cjfa-8193	397	20	the	the	DET
cjfa-8193	397	21	gjr	gjr	NOUN
cjfa-8193	397	22	-	-	PUNCT
cjfa-8193	397	23	garch	garch	NOUN
cjfa-8193	397	24	model	model	NOUN
cjfa-8193	397	25	.	.	PUNCT
cjfa-8193	398	1	similarly	similarly	ADV
cjfa-8193	398	2	,	,	PUNCT
cjfa-8193	398	3	bentes	bente	NOUN
cjfa-8193	398	4	,	,	PUNCT
cjfa-8193	398	5	menezes	meneze	NOUN
cjfa-8193	398	6	,	,	PUNCT
cjfa-8193	398	7	and	and	CCONJ
cjfa-8193	398	8	ferreira	ferreira	PROPN
cjfa-8193	398	9	(	(	PUNCT
cjfa-8193	398	10	2013	2013	NUM
cjfa-8193	398	11	)	)	PUNCT
cjfa-8193	398	12	examining	examine	VERB
cjfa-8193	398	13	nikkei	nikkei	NOUN
cjfa-8193	398	14	225	225	NUM
cjfa-8193	398	15	,	,	PUNCT
cjfa-8193	398	16	s&p	s&p	PROPN
cjfa-8193	398	17	500	500	NUM
cjfa-8193	398	18	and	and	CCONJ
cjfa-8193	398	19	stoxx	stoxx	VERB
cjfa-8193	398	20	50	50	NUM
cjfa-8193	398	21	from	from	ADP
cjfa-8193	398	22	1987–2013	1987–2013	NUM
cjfa-8193	398	23	found	find	VERB
cjfa-8193	398	24	all	all	DET
cjfa-8193	398	25	stock	stock	NOUN
cjfa-8193	398	26	index	index	NOUN
cjfa-8193	398	27	returns	return	NOUN
cjfa-8193	398	28	tested	test	VERB
cjfa-8193	398	29	exhibited	exhibit	VERB
cjfa-8193	398	30	asymmetry	asymmetry	NOUN
cjfa-8193	398	31	.	.	PUNCT
cjfa-8193	399	1	further	further	ADJ
cjfa-8193	399	2	similarities	similarity	NOUN
cjfa-8193	399	3	can	can	AUX
cjfa-8193	399	4	be	be	AUX
cjfa-8193	399	5	identified	identify	VERB
cjfa-8193	399	6	between	between	ADP
cjfa-8193	399	7	our	our	PRON
cjfa-8193	399	8	results	result	NOUN
cjfa-8193	399	9	and	and	CCONJ
cjfa-8193	399	10	other	other	ADJ
cjfa-8193	399	11	studies	study	NOUN
cjfa-8193	399	12	.	.	PUNCT
cjfa-8193	400	1	liu	liu	PROPN
cjfa-8193	400	2	&	&	CCONJ
cjfa-8193	400	3	hung	hung	PROPN
cjfa-8193	400	4	(	(	PUNCT
cjfa-8193	400	5	2010	2010	NUM
cjfa-8193	400	6	)	)	PUNCT
cjfa-8193	400	7	investigated	investigate	VERB
cjfa-8193	400	8	the	the	DET
cjfa-8193	400	9	performance	performance	NOUN
cjfa-8193	400	10	of	of	ADP
cjfa-8193	400	11	one	one	NUM
cjfa-8193	400	12	-	-	PUNCT
cjfa-8193	400	13	step	step	NOUN
cjfa-8193	400	14	-	-	PUNCT
cjfa-8193	400	15	ahead	ahead	NOUN
cjfa-8193	400	16	forecasting	forecasting	NOUN
cjfa-8193	400	17	using	use	VERB
cjfa-8193	400	18	asymmetric	asymmetric	ADJ
cjfa-8193	400	19	garch	garch	NOUN
cjfa-8193	400	20	models	model	NOUN
cjfa-8193	400	21	with	with	ADP
cjfa-8193	400	22	different	different	ADJ
cjfa-8193	400	23	distribution	distribution	NOUN
cjfa-8193	400	24	assumptions	assumption	NOUN
cjfa-8193	400	25	.	.	PUNCT
cjfa-8193	401	1	their	their	PRON
cjfa-8193	401	2	work	work	NOUN
cjfa-8193	401	3	,	,	PUNCT
cjfa-8193	401	4	in	in	ADP
cjfa-8193	401	5	respect	respect	NOUN
cjfa-8193	401	6	to	to	ADP
cjfa-8193	401	7	united	united	PROPN
cjfa-8193	401	8	states	states	PROPN
cjfa-8193	401	9	data	data	PROPN
cjfa-8193	401	10	,	,	PUNCT
cjfa-8193	401	11	concluded	conclude	VERB
cjfa-8193	401	12	that	that	SCONJ
cjfa-8193	401	13	gjr	gjr	NOUN
cjfa-8193	401	14	-	-	PUNCT
cjfa-8193	401	15	garch	garch	NOUN
cjfa-8193	401	16	generated	generate	VERB
cjfa-8193	401	17	volatility	volatility	NOUN
cjfa-8193	401	18	forecasts	forecast	NOUN
cjfa-8193	401	19	were	be	AUX
cjfa-8193	401	20	more	more	ADV
cjfa-8193	401	21	accurate	accurate	ADJ
cjfa-8193	401	22	that	that	SCONJ
cjfa-8193	401	23	those	those	PRON
cjfa-8193	401	24	produced	produce	VERB
cjfa-8193	401	25	by	by	ADP
cjfa-8193	401	26	their	their	PRON
cjfa-8193	401	27	egarch	egarch	NOUN
cjfa-8193	401	28	counterparts	counterpart	NOUN
cjfa-8193	401	29	.	.	PUNCT
cjfa-8193	402	1	furthermore	furthermore	ADV
cjfa-8193	402	2	,	,	PUNCT
cjfa-8193	402	3	their	their	PRON
cjfa-8193	402	4	results	result	NOUN
cjfa-8193	402	5	indicated	indicate	VERB
cjfa-8193	402	6	that	that	SCONJ
cjfa-8193	402	7	modelling	model	VERB
cjfa-8193	402	8	the	the	DET
cjfa-8193	402	9	asymmetric	asymmetric	ADJ
cjfa-8193	402	10	component	component	NOUN
cjfa-8193	402	11	was	be	AUX
cjfa-8193	402	12	much	much	ADV
cjfa-8193	402	13	more	more	ADV
cjfa-8193	402	14	important	important	ADJ
cjfa-8193	402	15	than	than	ADP
cjfa-8193	402	16	specifying	specify	VERB
cjfa-8193	402	17	the	the	DET
cjfa-8193	402	18	correct	correct	ADJ
cjfa-8193	402	19	h.	h.	PROPN
cjfa-8193	402	20	al	al	PROPN
cjfa-8193	402	21	-	-	PUNCT
cjfa-8193	402	22	hajieh	hajieh	PROPN
cjfa-8193	402	23	,	,	PUNCT
cjfa-8193	402	24	h.	h.	PROPN
cjfa-8193	402	25	alnemer	alnemer	PROPN
cjfa-8193	402	26	,	,	PUNCT
cjfa-8193	402	27	t.	t.	PROPN
cjfa-8193	402	28	rodgers	rodgers	PROPN
cjfa-8193	402	29	,	,	PUNCT
cjfa-8193	402	30	j.	j.	PROPN
cjfa-8193	402	31	niklewski24	niklewski24	NOUN
cjfa-8193	402	32	error	error	NOUN
cjfa-8193	402	33	distribution	distribution	NOUN
cjfa-8193	402	34	when	when	SCONJ
cjfa-8193	402	35	it	it	PRON
cjfa-8193	402	36	came	come	VERB
cjfa-8193	402	37	to	to	ADP
cjfa-8193	402	38	improving	improve	VERB
cjfa-8193	402	39	volatility	volatility	NOUN
cjfa-8193	402	40	forecasting	forecasting	NOUN
cjfa-8193	402	41	.	.	PUNCT
cjfa-8193	403	1	this	this	PRON
cjfa-8193	403	2	was	be	AUX
cjfa-8193	403	3	especially	especially	ADV
cjfa-8193	403	4	the	the	DET
cjfa-8193	403	5	case	case	NOUN
cjfa-8193	403	6	in	in	ADP
cjfa-8193	403	7	the	the	DET
cjfa-8193	403	8	presence	presence	NOUN
cjfa-8193	403	9	of	of	ADP
cjfa-8193	403	10	fat	fat	ADJ
cjfa-8193	403	11	-	-	PUNCT
cjfa-8193	403	12	tails	tail	NOUN
cjfa-8193	403	13	,	,	PUNCT
cjfa-8193	403	14	leptokurtosis	leptokurtosis	NOUN
cjfa-8193	403	15	,	,	PUNCT
cjfa-8193	403	16	skewness	skewness	NOUN
cjfa-8193	403	17	and	and	CCONJ
cjfa-8193	403	18	the	the	DET
cjfa-8193	403	19	leverage	leverage	NOUN
cjfa-8193	403	20	effect	effect	NOUN
cjfa-8193	403	21	.	.	PUNCT
cjfa-8193	404	1	a	a	DET
cjfa-8193	404	2	number	number	NOUN
cjfa-8193	404	3	of	of	ADP
cjfa-8193	404	4	other	other	ADJ
cjfa-8193	404	5	studies	study	NOUN
cjfa-8193	404	6	have	have	AUX
cjfa-8193	404	7	examined	examine	VERB
cjfa-8193	404	8	volatility	volatility	NOUN
cjfa-8193	404	9	in	in	ADP
cjfa-8193	404	10	mena	mena	PROPN
cjfa-8193	404	11	countries	country	NOUN
cjfa-8193	404	12	like	like	ADP
cjfa-8193	404	13	jordan	jordan	PROPN
cjfa-8193	404	14	.	.	PUNCT
cjfa-8193	405	1	assaf	assaf	PROPN
cjfa-8193	405	2	(	(	PUNCT
cjfa-8193	405	3	2015	2015	NUM
cjfa-8193	405	4	)	)	PUNCT
cjfa-8193	405	5	,	,	PUNCT
cjfa-8193	405	6	for	for	ADP
cjfa-8193	405	7	example	example	NOUN
cjfa-8193	405	8	,	,	PUNCT
cjfa-8193	405	9	examined	examine	VERB
cjfa-8193	405	10	the	the	DET
cjfa-8193	405	11	forecasting	forecasting	NOUN
cjfa-8193	405	12	performance	performance	NOUN
cjfa-8193	405	13	of	of	ADP
cjfa-8193	405	14	the	the	DET
cjfa-8193	405	15	value	value	NOUN
cjfa-8193	405	16	-	-	PUNCT
cjfa-8193	405	17	at	at	ADP
cjfa-8193	405	18	-	-	PUNCT
cjfa-8193	405	19	risk	risk	NOUN
cjfa-8193	405	20	(	(	PUNCT
cjfa-8193	405	21	var	var	NOUN
cjfa-8193	405	22	)	)	PUNCT
cjfa-8193	405	23	models	model	NOUN
cjfa-8193	405	24	in	in	ADP
cjfa-8193	405	25	egypt	egypt	PROPN
cjfa-8193	405	26	,	,	PUNCT
cjfa-8193	405	27	jordan	jordan	PROPN
cjfa-8193	405	28	,	,	PUNCT
cjfa-8193	405	29	morocco	morocco	PROPN
cjfa-8193	405	30	,	,	PUNCT
cjfa-8193	405	31	and	and	CCONJ
cjfa-8193	405	32	turkey	turkey	NOUN
cjfa-8193	405	33	.	.	PUNCT
cjfa-8193	406	1	their	their	PRON
cjfa-8193	406	2	results	result	NOUN
cjfa-8193	406	3	suggested	suggest	VERB
cjfa-8193	406	4	that	that	SCONJ
cjfa-8193	406	5	returns	return	NOUN
cjfa-8193	406	6	had	have	VERB
cjfa-8193	406	7	a	a	DET
cjfa-8193	406	8	significantly	significantly	ADV
cjfa-8193	406	9	fatter	fat	ADJ
cjfa-8193	406	10	tails	tail	NOUN
cjfa-8193	406	11	than	than	ADP
cjfa-8193	406	12	the	the	DET
cjfa-8193	406	13	normal	normal	ADJ
cjfa-8193	406	14	distribution	distribution	NOUN
cjfa-8193	406	15	and	and	CCONJ
cjfa-8193	406	16	that	that	DET
cjfa-8193	406	17	student	student	NOUN
cjfa-8193	406	18	aparch	aparch	NOUN
cjfa-8193	406	19	model	model	NOUN
cjfa-8193	406	20	produced	produce	VERB
cjfa-8193	406	21	more	more	ADV
cjfa-8193	406	22	accurate	accurate	ADJ
cjfa-8193	406	23	results	result	NOUN
cjfa-8193	406	24	than	than	ADP
cjfa-8193	406	25	those	those	PRON
cjfa-8193	406	26	generated	generate	VERB
cjfa-8193	406	27	using	use	VERB
cjfa-8193	406	28	normal	normal	ADJ
cjfa-8193	406	29	aparch	aparch	NOUN
cjfa-8193	406	30	models	model	NOUN
cjfa-8193	406	31	.	.	PUNCT
cjfa-8193	407	1	the	the	DET
cjfa-8193	407	2	considerable	considerable	ADJ
cjfa-8193	407	3	variety	variety	NOUN
cjfa-8193	407	4	of	of	ADP
cjfa-8193	407	5	results	result	NOUN
cjfa-8193	407	6	found	find	VERB
cjfa-8193	407	7	in	in	ADP
cjfa-8193	407	8	these	these	DET
cjfa-8193	407	9	different	different	ADJ
cjfa-8193	407	10	studies	study	NOUN
cjfa-8193	407	11	suggests	suggest	VERB
cjfa-8193	407	12	to	to	ADP
cjfa-8193	407	13	us	we	PRON
cjfa-8193	407	14	that	that	SCONJ
cjfa-8193	407	15	it	it	PRON
cjfa-8193	407	16	is	be	AUX
cjfa-8193	407	17	difficult	difficult	ADJ
cjfa-8193	407	18	to	to	PART
cjfa-8193	407	19	conclude	conclude	VERB
cjfa-8193	407	20	that	that	SCONJ
cjfa-8193	407	21	there	there	PRON
cjfa-8193	407	22	is	be	VERB
cjfa-8193	407	23	a	a	DET
cjfa-8193	407	24	‘	'	PUNCT
cjfa-8193	407	25	one	one	NUM
cjfa-8193	407	26	size	size	NOUN
cjfa-8193	407	27	fits	fit	VERB
cjfa-8193	407	28	all	all	DET
cjfa-8193	407	29	’	'	PUNCT
cjfa-8193	407	30	model	model	NOUN
cjfa-8193	407	31	that	that	PRON
cjfa-8193	407	32	can	can	AUX
cjfa-8193	407	33	be	be	AUX
cjfa-8193	407	34	used	use	VERB
cjfa-8193	407	35	to	to	PART
cjfa-8193	407	36	model	model	VERB
cjfa-8193	407	37	asymmetry	asymmetry	NOUN
cjfa-8193	407	38	affects	affect	VERB
cjfa-8193	407	39	in	in	ADP
cjfa-8193	407	40	stock	stock	NOUN
cjfa-8193	407	41	market	market	NOUN
cjfa-8193	407	42	returns	return	NOUN
cjfa-8193	407	43	.	.	PUNCT
cjfa-8193	408	1	we	we	PRON
cjfa-8193	408	2	believe	believe	VERB
cjfa-8193	408	3	that	that	SCONJ
cjfa-8193	408	4	our	our	PRON
cjfa-8193	408	5	study	study	NOUN
cjfa-8193	408	6	contributes	contribute	VERB
cjfa-8193	408	7	significantly	significantly	ADV
cjfa-8193	408	8	to	to	ADP
cjfa-8193	408	9	the	the	DET
cjfa-8193	408	10	literature	literature	NOUN
cjfa-8193	408	11	by	by	ADP
cjfa-8193	408	12	examining	examine	VERB
cjfa-8193	408	13	the	the	DET
cjfa-8193	408	14	relative	relative	ADJ
cjfa-8193	408	15	forecasting	forecasting	NOUN
cjfa-8193	408	16	performances	performance	NOUN
cjfa-8193	408	17	of	of	ADP
cjfa-8193	408	18	different	different	ADJ
cjfa-8193	408	19	distribution	distribution	NOUN
cjfa-8193	408	20	-	-	PUNCT
cjfa-8193	408	21	type	type	NOUN
cjfa-8193	408	22	(	(	PUNCT
cjfa-8193	408	23	normal	normal	ADJ
cjfa-8193	408	24	,	,	PUNCT
cjfa-8193	408	25	student	student	NOUN
cjfa-8193	408	26	-	-	PUNCT
cjfa-8193	408	27	t	t	NOUN
cjfa-8193	408	28	,	,	PUNCT
cjfa-8193	408	29	ged	ge	VERB
cjfa-8193	408	30	,	,	PUNCT
cjfa-8193	408	31	and	and	CCONJ
cjfa-8193	408	32	skewed	skewed	ADJ
cjfa-8193	408	33	student	student	NOUN
cjfa-8193	408	34	)	)	PUNCT
cjfa-8193	408	35	and	and	CCONJ
cjfa-8193	408	36	asymmetry	asymmetry	NOUN
cjfa-8193	408	37	-	-	PUNCT
cjfa-8193	408	38	type	type	NOUN
cjfa-8193	408	39	(	(	PUNCT
cjfa-8193	408	40	gjr-	gjr-	NOUN
cjfa-8193	408	41	 	 	SPACE
cjfa-8193	408	42	garch	garch	NOUN
cjfa-8193	408	43	and	and	CCONJ
cjfa-8193	408	44	egarch	egarch	NOUN
cjfa-8193	408	45	)	)	PUNCT
cjfa-8193	408	46	garch	garch	NOUN
cjfa-8193	408	47	models	model	NOUN
cjfa-8193	408	48	.	.	PUNCT
cjfa-8193	409	1	both	both	CCONJ
cjfa-8193	409	2	our	our	PRON
cjfa-8193	409	3	superior	superior	ADJ
cjfa-8193	409	4	predictive	predictive	ADJ
cjfa-8193	409	5	ability	ability	NOUN
cjfa-8193	409	6	and	and	CCONJ
cjfa-8193	409	7	model	model	NOUN
cjfa-8193	409	8	confidence	confidence	NOUN
cjfa-8193	409	9	set	set	VERB
cjfa-8193	409	10	results	result	NOUN
cjfa-8193	409	11	identify	identify	VERB
cjfa-8193	409	12	that	that	SCONJ
cjfa-8193	409	13	gjr	gjr	NOUN
cjfa-8193	409	14	-	-	PUNCT
cjfa-8193	409	15	garch	garch	NOUN
cjfa-8193	409	16	with	with	ADP
cjfa-8193	409	17	skewed	skewed	ADJ
cjfa-8193	409	18	student	student	NOUN
cjfa-8193	409	19	distribution	distribution	NOUN
cjfa-8193	409	20	is	be	AUX
cjfa-8193	409	21	the	the	DET
cjfa-8193	409	22	best	good	ADJ
cjfa-8193	409	23	fitting	fitting	ADJ
cjfa-8193	409	24	model	model	NOUN
cjfa-8193	409	25	for	for	ADP
cjfa-8193	409	26	jordan	jordan	PROPN
cjfa-8193	409	27	.	.	PUNCT
cjfa-8193	410	1	the	the	DET
cjfa-8193	410	2	finding	finding	NOUN
cjfa-8193	410	3	in	in	ADP
cjfa-8193	410	4	our	our	PRON
cjfa-8193	410	5	research	research	NOUN
cjfa-8193	410	6	chimes	chime	VERB
cjfa-8193	410	7	with	with	ADP
cjfa-8193	410	8	the	the	DET
cjfa-8193	410	9	findings	finding	NOUN
cjfa-8193	410	10	of	of	ADP
cjfa-8193	410	11	similar	similar	ADJ
cjfa-8193	410	12	studies	study	NOUN
cjfa-8193	410	13	undertaken	undertake	VERB
cjfa-8193	410	14	in	in	ADP
cjfa-8193	410	15	different	different	ADJ
cjfa-8193	410	16	market	market	NOUN
cjfa-8193	410	17	contexts	context	NOUN
cjfa-8193	410	18	;	;	PUNCT
cjfa-8193	410	19	such	such	ADJ
cjfa-8193	410	20	as	as	ADP
cjfa-8193	410	21	liu	liu	PROPN
cjfa-8193	410	22	&	&	CCONJ
cjfa-8193	410	23	hung	hung	PROPN
cjfa-8193	410	24	(	(	PUNCT
cjfa-8193	410	25	2010	2010	NUM
cjfa-8193	410	26	)	)	PUNCT
cjfa-8193	410	27	work	work	NOUN
cjfa-8193	410	28	in	in	ADP
cjfa-8193	410	29	respect	respect	NOUN
cjfa-8193	410	30	to	to	ADP
cjfa-8193	410	31	the	the	DET
cjfa-8193	410	32	united	united	PROPN
cjfa-8193	410	33	states	states	PROPN
cjfa-8193	410	34	.	.	PUNCT
cjfa-8193	410	35	 	 	SPACE
cjfa-8193	411	1	references	reference	VERB
cjfa-8193	411	2	al	al	PROPN
cjfa-8193	411	3	-	-	PUNCT
cjfa-8193	411	4	hajieh	hajieh	PROPN
cjfa-8193	411	5	,	,	PUNCT
cjfa-8193	411	6	h.	h.	PROPN
cjfa-8193	411	7	,	,	PUNCT
cjfa-8193	411	8	redhead	redhead	PROPN
cjfa-8193	411	9	,	,	PUNCT
cjfa-8193	411	10	k.	k.	PROPN
cjfa-8193	411	11	,	,	PUNCT
cjfa-8193	411	12	&	&	CCONJ
cjfa-8193	411	13	rodgers	rodgers	PROPN
cjfa-8193	411	14	t.	t.	PROPN
cjfa-8193	411	15	(	(	PUNCT
cjfa-8193	411	16	2011	2011	NUM
cjfa-8193	411	17	)	)	PUNCT
cjfa-8193	411	18	.	.	PUNCT
cjfa-8193	412	1	investor	investor	NOUN
cjfa-8193	412	2	sentiment	sentiment	NOUN
cjfa-8193	412	3	and	and	CCONJ
cjfa-8193	412	4	calendar	calendar	NOUN
cjfa-8193	412	5	anomaly	anomaly	NOUN
cjfa-8193	412	6	effects	effect	NOUN
cjfa-8193	412	7	:	:	PUNCT
cjfa-8193	412	8	a	a	DET
cjfa-8193	412	9	case	case	NOUN
cjfa-8193	412	10	study	study	NOUN
cjfa-8193	412	11	of	of	ADP
cjfa-8193	412	12	the	the	DET
cjfa-8193	412	13	impact	impact	NOUN
cjfa-8193	412	14	of	of	ADP
cjfa-8193	412	15	ramadan	ramadan	PROPN
cjfa-8193	412	16	on	on	ADP
cjfa-8193	412	17	islamic	islamic	PROPN
cjfa-8193	412	18	middle	middle	ADJ
cjfa-8193	412	19	eastern	eastern	ADJ
cjfa-8193	412	20	markets	market	NOUN
cjfa-8193	412	21	.	.	PUNCT
cjfa-8193	413	1	research	research	NOUN
cjfa-8193	413	2	in	in	ADP
cjfa-8193	413	3	international	international	ADJ
cjfa-8193	413	4	business	business	NOUN
cjfa-8193	413	5	and	and	CCONJ
cjfa-8193	413	6	finance	finance	NOUN
cjfa-8193	413	7	,	,	PUNCT
cjfa-8193	413	8	25	25	NUM
cjfa-8193	413	9	(	(	PUNCT
cjfa-8193	413	10	3	3	NUM
cjfa-8193	413	11	)	)	PUNCT
cjfa-8193	413	12	,	,	PUNCT
cjfa-8193	413	13	345	345	NUM
cjfa-8193	413	14	-	-	SYM
cjfa-8193	413	15	356	356	NUM
cjfa-8193	413	16	.	.	PUNCT
cjfa-8193	414	1	http://dx.doi	http://dx.doi	NOUN
cjfa-8193	414	2	.	.	PUNCT
cjfa-8193	415	1	org/10.1016	org/10.1016	PROPN
cjfa-8193	415	2	/	/	SYM
cjfa-8193	415	3	j.ribaf.2011.03.004	j.ribaf.2011.03.004	PROPN
cjfa-8193	415	4	.	.	PUNCT
cjfa-8193	416	1	andrikopoulos	andrikopoulos	PROPN
cjfa-8193	416	2	,	,	PUNCT
cjfa-8193	416	3	p.	p.	PROPN
cjfa-8193	416	4	,	,	PUNCT
cjfa-8193	416	5	niklewski	niklewski	PROPN
cjfa-8193	416	6	,	,	PUNCT
cjfa-8193	416	7	j.	j.	PROPN
cjfa-8193	416	8	,	,	PUNCT
cjfa-8193	416	9	&	&	CCONJ
cjfa-8193	416	10	rodgers	rodgers	PROPN
cjfa-8193	416	11	t.	t.	PROPN
cjfa-8193	416	12	(	(	PUNCT
cjfa-8193	416	13	forthcoming	forthcoming	ADJ
cjfa-8193	416	14	)	)	PUNCT
cjfa-8193	416	15	.	.	PUNCT
cjfa-8193	417	1	the	the	DET
cjfa-8193	417	2	portfolio	portfolio	NOUN
cjfa-8193	417	3	diversification	diversification	NOUN
cjfa-8193	417	4	benefits	benefit	NOUN
cjfa-8193	417	5	of	of	ADP
cjfa-8193	417	6	frontier	frontier	NOUN
cjfa-8193	417	7	markets	market	NOUN
cjfa-8193	417	8	:	:	PUNCT
cjfa-8193	417	9	an	an	DET
cjfa-8193	417	10	investigation	investigation	NOUN
cjfa-8193	417	11	into	into	ADP
cjfa-8193	417	12	regional	regional	ADJ
cjfa-8193	417	13	effects	effect	NOUN
cjfa-8193	417	14	.	.	PUNCT
cjfa-8193	418	1	handbook	handbook	NOUN
cjfa-8193	418	2	of	of	ADP
cjfa-8193	418	3	frontier	frontier	NOUN
cjfa-8193	418	4	markets	market	NOUN
cjfa-8193	418	5	.	.	PUNCT
cjfa-8193	419	1	ed	ed	X
cjfa-8193	419	2	.	.	PUNCT
cjfa-8193	420	1	by	by	ADP
cjfa-8193	420	2	andrikopoulos	andrikopoulos	PROPN
cjfa-8193	420	3	p.	p.	PROPN
cjfa-8193	420	4	,	,	PUNCT
cjfa-8193	420	5	gregoriou	gregoriou	NOUN
cjfa-8193	420	6	g.	g.	PROPN
cjfa-8193	420	7	,	,	PUNCT
cjfa-8193	420	8	and	and	CCONJ
cjfa-8193	420	9	kallinterakis	kallinteraki	NOUN
cjfa-8193	420	10	v.	v.	PROPN
cjfa-8193	420	11	elsevier	elsevier	PROPN
cjfa-8193	420	12	.	.	PUNCT
cjfa-8193	421	1	assaf	assaf	PROPN
cjfa-8193	421	2	,	,	PUNCT
cjfa-8193	421	3	a.	a.	NOUN
cjfa-8193	421	4	(	(	PUNCT
cjfa-8193	421	5	2015	2015	NUM
cjfa-8193	421	6	)	)	PUNCT
cjfa-8193	421	7	.	.	PUNCT
cjfa-8193	422	1	value	value	NOUN
cjfa-8193	422	2	-	-	PUNCT
cjfa-8193	422	3	at	at	ADP
cjfa-8193	422	4	-	-	PUNCT
cjfa-8193	422	5	risk	risk	NOUN
cjfa-8193	422	6	analysis	analysis	NOUN
cjfa-8193	422	7	in	in	ADP
cjfa-8193	422	8	the	the	DET
cjfa-8193	422	9	mena	mena	PROPN
cjfa-8193	422	10	equity	equity	PROPN
cjfa-8193	422	11	markets	market	NOUN
cjfa-8193	422	12	:	:	PUNCT
cjfa-8193	422	13	fat	fat	ADJ
cjfa-8193	422	14	tails	tail	NOUN
cjfa-8193	422	15	and	and	CCONJ
cjfa-8193	422	16	conditional	conditional	ADJ
cjfa-8193	422	17	asymmetries	asymmetry	NOUN
cjfa-8193	422	18	in	in	ADP
cjfa-8193	422	19	return	return	NOUN
cjfa-8193	422	20	distributions	distribution	NOUN
cjfa-8193	422	21	.	.	PUNCT
cjfa-8193	423	1	journal	journal	NOUN
cjfa-8193	423	2	of	of	ADP
cjfa-8193	423	3	multinational	multinational	ADJ
cjfa-8193	423	4	financial	financial	ADJ
cjfa-8193	423	5	management	management	NOUN
cjfa-8193	423	6	,	,	PUNCT
cjfa-8193	423	7	29	29	NUM
cjfa-8193	423	8	,	,	PUNCT
cjfa-8193	423	9	30	30	NUM
cjfa-8193	423	10	-	-	SYM
cjfa-8193	423	11	45	45	NUM
cjfa-8193	423	12	.	.	PUNCT
cjfa-8193	424	1	http://dx.doi.org/10.1016/j.mulfin.2014.11.002	http://dx.doi.org/10.1016/j.mulfin.2014.11.002	PROPN
cjfa-8193	424	2	.	.	PUNCT
cjfa-8193	425	1	awartani	awartani	PROPN
cjfa-8193	425	2	,	,	PUNCT
cjfa-8193	425	3	b.	b.	PROPN
cjfa-8193	425	4	m.	m.	PROPN
cjfa-8193	425	5	,	,	PUNCT
cjfa-8193	425	6	&	&	CCONJ
cjfa-8193	425	7	corradi	corradi	PROPN
cjfa-8193	425	8	,	,	PUNCT
cjfa-8193	425	9	v.	v.	PROPN
cjfa-8193	425	10	(	(	PUNCT
cjfa-8193	425	11	2005	2005	NUM
cjfa-8193	425	12	)	)	PUNCT
cjfa-8193	425	13	.	.	PUNCT
cjfa-8193	426	1	predicting	predict	VERB
cjfa-8193	426	2	the	the	DET
cjfa-8193	426	3	volatility	volatility	NOUN
cjfa-8193	426	4	of	of	ADP
cjfa-8193	426	5	the	the	DET
cjfa-8193	426	6	s&p-500	s&p-500	NUM
cjfa-8193	426	7	stock	stock	NOUN
cjfa-8193	426	8	index	index	NOUN
cjfa-8193	426	9	via	via	ADP
cjfa-8193	426	10	garch	garch	NOUN
cjfa-8193	426	11	models	model	NOUN
cjfa-8193	426	12	:	:	PUNCT
cjfa-8193	426	13	the	the	DET
cjfa-8193	426	14	role	role	NOUN
cjfa-8193	426	15	of	of	ADP
cjfa-8193	426	16	asymmetries	asymmetry	NOUN
cjfa-8193	426	17	.	.	PUNCT
cjfa-8193	427	1	international	international	ADJ
cjfa-8193	427	2	journal	journal	PROPN
cjfa-8193	427	3	of	of	ADP
cjfa-8193	427	4	forecasting	forecasting	NOUN
cjfa-8193	427	5	,	,	PUNCT
cjfa-8193	427	6	21	21	NUM
cjfa-8193	427	7	(	(	PUNCT
cjfa-8193	427	8	1	1	NUM
cjfa-8193	427	9	)	)	PUNCT
cjfa-8193	427	10	,	,	PUNCT
cjfa-8193	427	11	167	167	NUM
cjfa-8193	427	12	-	-	SYM
cjfa-8193	427	13	183	183	NUM
cjfa-8193	427	14	.	.	PUNCT
cjfa-8193	428	1	http://dx.doi.org/10.1016/j.ijforecast.2004.08.003	http://dx.doi.org/10.1016/j.ijforecast.2004.08.003	PROPN
cjfa-8193	428	2	.	.	PROPN
cjfa-8193	428	3	balaban	balaban	PROPN
cjfa-8193	428	4	,	,	PUNCT
cjfa-8193	428	5	e.	e.	PROPN
cjfa-8193	428	6	(	(	PUNCT
cjfa-8193	428	7	2004	2004	NUM
cjfa-8193	428	8	)	)	PUNCT
cjfa-8193	428	9	.	.	PUNCT
cjfa-8193	429	1	comparative	comparative	ADJ
cjfa-8193	429	2	forecasting	forecasting	NOUN
cjfa-8193	429	3	performance	performance	NOUN
cjfa-8193	429	4	of	of	ADP
cjfa-8193	429	5	symmetric	symmetric	ADJ
cjfa-8193	429	6	and	and	CCONJ
cjfa-8193	429	7	asymmetric	asymmetric	ADJ
cjfa-8193	429	8	conditional	conditional	ADJ
cjfa-8193	429	9	volatility	volatility	NOUN
cjfa-8193	429	10	models	model	NOUN
cjfa-8193	429	11	of	of	ADP
cjfa-8193	429	12	an	an	DET
cjfa-8193	429	13	exchange	exchange	NOUN
cjfa-8193	429	14	rate	rate	NOUN
cjfa-8193	429	15	.	.	PUNCT
cjfa-8193	430	1	economics	economic	NOUN
cjfa-8193	430	2	letters	letter	NOUN
cjfa-8193	430	3	,	,	PUNCT
cjfa-8193	430	4	83	83	NUM
cjfa-8193	430	5	(	(	PUNCT
cjfa-8193	430	6	1	1	NUM
cjfa-8193	430	7	)	)	PUNCT
cjfa-8193	430	8	,	,	PUNCT
cjfa-8193	430	9	99	99	NUM
cjfa-8193	430	10	–	–	PUNCT
cjfa-8193	430	11	–	–	PUNCT
cjfa-8193	430	12	105	105	NUM
cjfa-8193	430	13	.	.	PUNCT
cjfa-8193	431	1	http://dx.doi.org/10.1016/j.econlet.2003.09.028	http://dx.doi.org/10.1016/j.econlet.2003.09.028	PROPN
cjfa-8193	431	2	.	.	PUNCT
cjfa-8193	432	1	forecasting	forecast	VERB
cjfa-8193	432	2	the	the	DET
cjfa-8193	432	3	jordanian	jordanian	ADJ
cjfa-8193	432	4	stock	stock	NOUN
cjfa-8193	432	5	index	index	PROPN
cjfa-8193	432	6	…	…	PUNCT
cjfa-8193	432	7	25	25	NUM
cjfa-8193	432	8	bentes	bente	NOUN
cjfa-8193	432	9	,	,	PUNCT
cjfa-8193	432	10	s.	s.	PROPN
cjfa-8193	432	11	r.	r.	PROPN
cjfa-8193	432	12	,	,	PUNCT
cjfa-8193	432	13	menezes	menezes	PROPN
cjfa-8193	432	14	,	,	PUNCT
cjfa-8193	432	15	r.	r.	PROPN
cjfa-8193	432	16	,	,	PUNCT
cjfa-8193	432	17	&	&	CCONJ
cjfa-8193	432	18	ferreira	ferreira	PROPN
cjfa-8193	432	19	,	,	PUNCT
cjfa-8193	432	20	n.	n.	PROPN
cjfa-8193	432	21	b.	b.	PROPN
cjfa-8193	432	22	(	(	PUNCT
cjfa-8193	432	23	2013	2013	NUM
cjfa-8193	432	24	)	)	PUNCT
cjfa-8193	432	25	.	.	PUNCT
cjfa-8193	433	1	on	on	ADP
cjfa-8193	433	2	the	the	DET
cjfa-8193	433	3	asymmetric	asymmetric	ADJ
cjfa-8193	433	4	behaviour	behaviour	NOUN
cjfa-8193	433	5	of	of	ADP
cjfa-8193	433	6	stock	stock	NOUN
cjfa-8193	433	7	market	market	NOUN
cjfa-8193	433	8	volatility	volatility	NOUN
cjfa-8193	433	9	:	:	PUNCT
cjfa-8193	433	10	evidence	evidence	NOUN
cjfa-8193	433	11	from	from	ADP
cjfa-8193	433	12	three	three	NUM
cjfa-8193	433	13	countries	country	NOUN
cjfa-8193	433	14	.	.	PUNCT
cjfa-8193	434	1	international	international	ADJ
cjfa-8193	434	2	journal	journal	PROPN
cjfa-8193	434	3	of	of	ADP
cjfa-8193	434	4	academic	academic	ADJ
cjfa-8193	434	5	research	research	NOUN
cjfa-8193	434	6	,	,	PUNCT
cjfa-8193	434	7	5	5	NUM
cjfa-8193	434	8	(	(	PUNCT
cjfa-8193	434	9	4	4	NUM
cjfa-8193	434	10	)	)	PUNCT
cjfa-8193	434	11	,	,	PUNCT
cjfa-8193	434	12	24	24	NUM
cjfa-8193	434	13	-	-	SYM
cjfa-8193	434	14	32	32	NUM
cjfa-8193	434	15	.	.	PUNCT
cjfa-8193	435	1	http://dx.doi.org/10.7813/2075-4124.2013/5-4/a.4	http://dx.doi.org/10.7813/2075-4124.2013/5-4/a.4	PROPN
cjfa-8193	435	2	.	.	PROPN
cjfa-8193	435	3	bollerslev	bollerslev	PROPN
cjfa-8193	435	4	,	,	PUNCT
cjfa-8193	435	5	t.	t.	PROPN
cjfa-8193	435	6	(	(	PUNCT
cjfa-8193	435	7	1986	1986	NUM
cjfa-8193	435	8	)	)	PUNCT
cjfa-8193	435	9	.	.	PUNCT
cjfa-8193	436	1	generalized	generalize	VERB
cjfa-8193	436	2	autoregressive	autoregressive	ADJ
cjfa-8193	436	3	conditional	conditional	ADJ
cjfa-8193	436	4	heteroskedasticity	heteroskedasticity	NOUN
cjfa-8193	436	5	.	.	PUNCT
cjfa-8193	437	1	journal	journal	PROPN
cjfa-8193	437	2	of	of	ADP
cjfa-8193	437	3	econometrics	econometric	NOUN
cjfa-8193	437	4	,	,	PUNCT
cjfa-8193	437	5	31	31	NUM
cjfa-8193	437	6	(	(	PUNCT
cjfa-8193	437	7	3	3	NUM
cjfa-8193	437	8	)	)	PUNCT
cjfa-8193	437	9	,	,	PUNCT
cjfa-8193	437	10	307	307	NUM
cjfa-8193	437	11	-	-	SYM
cjfa-8193	437	12	327	327	NUM
cjfa-8193	437	13	.	.	PUNCT
cjfa-8193	438	1	http://dx.doi.org/10.1016/0304-4076(86)90063-1	http://dx.doi.org/10.1016/0304-4076(86)90063-1	PROPN
cjfa-8193	438	2	.	.	PUNCT
cjfa-8193	439	1	brailsford	brailsford	PROPN
cjfa-8193	439	2	,	,	PUNCT
cjfa-8193	439	3	t.	t.	PROPN
cjfa-8193	439	4	j.	j.	PROPN
cjfa-8193	439	5	,	,	PUNCT
cjfa-8193	439	6	&	&	CCONJ
cjfa-8193	439	7	faff	faff	PROPN
cjfa-8193	439	8	,	,	PUNCT
cjfa-8193	439	9	r.	r.	PROPN
cjfa-8193	439	10	w.	w.	PROPN
cjfa-8193	439	11	(	(	PUNCT
cjfa-8193	439	12	1996	1996	NUM
cjfa-8193	439	13	)	)	PUNCT
cjfa-8193	439	14	.	.	PUNCT
cjfa-8193	440	1	an	an	DET
cjfa-8193	440	2	evaluation	evaluation	NOUN
cjfa-8193	440	3	of	of	ADP
cjfa-8193	440	4	volatility	volatility	NOUN
cjfa-8193	440	5	forecasting	forecasting	NOUN
cjfa-8193	440	6	techniques	technique	NOUN
cjfa-8193	440	7	.	.	PUNCT
cjfa-8193	441	1	journal	journal	PROPN
cjfa-8193	441	2	of	of	ADP
cjfa-8193	441	3	banking	banking	NOUN
cjfa-8193	441	4	&	&	CCONJ
cjfa-8193	441	5	finance	finance	PROPN
cjfa-8193	441	6	,	,	PUNCT
cjfa-8193	441	7	20	20	NUM
cjfa-8193	441	8	(	(	PUNCT
cjfa-8193	441	9	3	3	NUM
cjfa-8193	441	10	)	)	PUNCT
cjfa-8193	441	11	,	,	PUNCT
cjfa-8193	441	12	419	419	NUM
cjfa-8193	441	13	-	-	SYM
cjfa-8193	441	14	438	438	NUM
cjfa-8193	441	15	.	.	PUNCT
cjfa-8193	442	1	http://dx.doi.org/10.1016/03784266(95)00015-1	http://dx.doi.org/10.1016/03784266(95)00015-1	PROPN
cjfa-8193	442	2	.	.	PUNCT
cjfa-8193	442	3	brooks	brooks	PROPN
cjfa-8193	442	4	,	,	PUNCT
cjfa-8193	442	5	r.	r.	PROPN
cjfa-8193	442	6	(	(	PUNCT
cjfa-8193	442	7	2007	2007	NUM
cjfa-8193	442	8	)	)	PUNCT
cjfa-8193	442	9	.	.	PUNCT
cjfa-8193	443	1	power	power	NOUN
cjfa-8193	443	2	arch	arch	NOUN
cjfa-8193	443	3	modelling	modelling	NOUN
cjfa-8193	443	4	of	of	ADP
cjfa-8193	443	5	the	the	DET
cjfa-8193	443	6	volatility	volatility	NOUN
cjfa-8193	443	7	of	of	ADP
cjfa-8193	443	8	emerging	emerge	VERB
cjfa-8193	443	9	equity	equity	NOUN
cjfa-8193	443	10	markets	market	NOUN
cjfa-8193	443	11	.	.	PUNCT
cjfa-8193	444	1	emerging	emerge	VERB
cjfa-8193	444	2	markets	market	NOUN
cjfa-8193	444	3	review	review	VERB
cjfa-8193	444	4	,	,	PUNCT
cjfa-8193	444	5	8(2	8(2	NUM
cjfa-8193	444	6	)	)	PUNCT
cjfa-8193	444	7	,	,	PUNCT
cjfa-8193	444	8	124	124	NUM
cjfa-8193	444	9	-	-	SYM
cjfa-8193	444	10	133	133	NUM
cjfa-8193	444	11	.	.	PUNCT
cjfa-8193	445	1	http://dx.doi.org/10.1016/j.ememar.2007.01.002	http://dx.doi.org/10.1016/j.ememar.2007.01.002	PROPN
cjfa-8193	445	2	.	.	PUNCT
cjfa-8193	445	3	engle	engle	PROPN
cjfa-8193	445	4	,	,	PUNCT
cjfa-8193	445	5	r.	r.	PROPN
cjfa-8193	445	6	f.	f.	PROPN
cjfa-8193	445	7	(	(	PUNCT
cjfa-8193	445	8	1982	1982	NUM
cjfa-8193	445	9	)	)	PUNCT
cjfa-8193	445	10	.	.	PUNCT
cjfa-8193	446	1	autoregressive	autoregressive	ADJ
cjfa-8193	446	2	conditional	conditional	ADJ
cjfa-8193	446	3	heteroscedasticity	heteroscedasticity	NOUN
cjfa-8193	446	4	with	with	ADP
cjfa-8193	446	5	estimates	estimate	NOUN
cjfa-8193	446	6	of	of	ADP
cjfa-8193	446	7	the	the	DET
cjfa-8193	446	8	variance	variance	NOUN
cjfa-8193	446	9	of	of	ADP
cjfa-8193	446	10	united	united	PROPN
cjfa-8193	446	11	kingdom	kingdom	PROPN
cjfa-8193	446	12	inflation	inflation	NOUN
cjfa-8193	446	13	.	.	PUNCT
cjfa-8193	447	1	econometrica	econometrica	PROPN
cjfa-8193	447	2	:	:	PUNCT
cjfa-8193	447	3	journal	journal	NOUN
cjfa-8193	447	4	of	of	ADP
cjfa-8193	447	5	the	the	DET
cjfa-8193	447	6	econometric	econometric	ADJ
cjfa-8193	447	7	society	society	NOUN
cjfa-8193	447	8	,	,	PUNCT
cjfa-8193	447	9	50	50	NUM
cjfa-8193	447	10	(	(	PUNCT
cjfa-8193	447	11	4	4	NUM
cjfa-8193	447	12	)	)	PUNCT
cjfa-8193	447	13	,	,	PUNCT
cjfa-8193	447	14	987	987	NUM
cjfa-8193	447	15	-	-	SYM
cjfa-8193	447	16	1007	1007	NUM
cjfa-8193	447	17	.	.	PUNCT
cjfa-8193	448	1	http://dx.doi.org/10.2307/1912773	http://dx.doi.org/10.2307/1912773	NOUN
cjfa-8193	448	2	.	.	PUNCT
cjfa-8193	449	1	engle	engle	PROPN
cjfa-8193	449	2	,	,	PUNCT
cjfa-8193	449	3	r.	r.	PROPN
cjfa-8193	449	4	f.	f.	PROPN
cjfa-8193	449	5	,	,	PUNCT
cjfa-8193	449	6	&	&	CCONJ
cjfa-8193	449	7	ng	ng	PROPN
cjfa-8193	449	8	,	,	PUNCT
cjfa-8193	449	9	v.	v.	PROPN
cjfa-8193	449	10	k.	k.	PROPN
cjfa-8193	450	1	(	(	PUNCT
cjfa-8193	450	2	1993	1993	NUM
cjfa-8193	450	3	)	)	PUNCT
cjfa-8193	450	4	.	.	PUNCT
cjfa-8193	451	1	measuring	measure	VERB
cjfa-8193	451	2	and	and	CCONJ
cjfa-8193	451	3	testing	test	VERB
cjfa-8193	451	4	the	the	DET
cjfa-8193	451	5	impact	impact	NOUN
cjfa-8193	451	6	of	of	ADP
cjfa-8193	451	7	news	news	NOUN
cjfa-8193	451	8	on	on	ADP
cjfa-8193	451	9	volatility	volatility	NOUN
cjfa-8193	451	10	.	.	PUNCT
cjfa-8193	452	1	the	the	DET
cjfa-8193	452	2	journal	journal	PROPN
cjfa-8193	452	3	of	of	ADP
cjfa-8193	452	4	finance	finance	NOUN
cjfa-8193	452	5	,	,	PUNCT
cjfa-8193	452	6	48(5	48(5	NUM
cjfa-8193	452	7	)	)	PUNCT
cjfa-8193	452	8	,	,	PUNCT
cjfa-8193	452	9	1749	1749	NUM
cjfa-8193	452	10	-	-	SYM
cjfa-8193	452	11	1778	1778	NUM
cjfa-8193	452	12	.	.	PUNCT
cjfa-8193	453	1	http://dx.doi.org/10.1111/j.1540-6261.1993	http://dx.doi.org/10.1111/j.1540-6261.1993	X
cjfa-8193	453	2	.	.	PUNCT
cjfa-8193	454	1	tb05127.x	tb05127.x	PROPN
cjfa-8193	454	2	.	.	PUNCT
cjfa-8193	454	3	fernández	fernández	PROPN
cjfa-8193	454	4	,	,	PUNCT
cjfa-8193	454	5	c.	c.	PROPN
cjfa-8193	454	6	,	,	PUNCT
cjfa-8193	454	7	&	&	CCONJ
cjfa-8193	454	8	steel	steel	PROPN
cjfa-8193	454	9	,	,	PUNCT
cjfa-8193	454	10	m.	m.	NOUN
cjfa-8193	454	11	f.	f.	PROPN
cjfa-8193	454	12	(	(	PUNCT
cjfa-8193	454	13	1998	1998	NUM
cjfa-8193	454	14	)	)	PUNCT
cjfa-8193	454	15	.	.	PUNCT
cjfa-8193	455	1	on	on	ADP
cjfa-8193	455	2	bayesian	bayesian	NOUN
cjfa-8193	455	3	modeling	modeling	NOUN
cjfa-8193	455	4	of	of	ADP
cjfa-8193	455	5	fat	fat	ADJ
cjfa-8193	455	6	tails	tail	NOUN
cjfa-8193	455	7	and	and	CCONJ
cjfa-8193	455	8	skewness	skewness	NOUN
cjfa-8193	455	9	.	.	PUNCT
cjfa-8193	456	1	journal	journal	PROPN
cjfa-8193	456	2	of	of	ADP
cjfa-8193	456	3	the	the	DET
cjfa-8193	456	4	american	american	PROPN
cjfa-8193	456	5	statistical	statistical	PROPN
cjfa-8193	456	6	association	association	PROPN
cjfa-8193	456	7	,	,	PUNCT
cjfa-8193	456	8	93(441	93(441	NOUN
cjfa-8193	456	9	)	)	PUNCT
cjfa-8193	456	10	,	,	PUNCT
cjfa-8193	456	11	359	359	NUM
cjfa-8193	456	12	-	-	SYM
cjfa-8193	456	13	371	371	NUM
cjfa-8193	456	14	.	.	PUNCT
cjfa-8193	456	15	http://dx.doi.org	http://dx.doi.org	NUM
cjfa-8193	456	16	/10.1080/01621459.1998.10474117	/10.1080/01621459.1998.10474117	PUNCT
cjfa-8193	456	17	.	.	PUNCT
cjfa-8193	457	1	glosten	glosten	ADJ
cjfa-8193	457	2	,	,	PUNCT
cjfa-8193	457	3	l.	l.	PROPN
cjfa-8193	457	4	r.	r.	PROPN
cjfa-8193	457	5	,	,	PUNCT
cjfa-8193	457	6	jagannathan	jagannathan	PROPN
cjfa-8193	457	7	,	,	PUNCT
cjfa-8193	457	8	r.	r.	PROPN
cjfa-8193	457	9	,	,	PUNCT
cjfa-8193	457	10	&	&	CCONJ
cjfa-8193	457	11	runkle	runkle	PROPN
cjfa-8193	457	12	,	,	PUNCT
cjfa-8193	457	13	d.	d.	PROPN
cjfa-8193	457	14	e.	e.	PROPN
cjfa-8193	457	15	(	(	PUNCT
cjfa-8193	457	16	1993	1993	NUM
cjfa-8193	457	17	)	)	PUNCT
cjfa-8193	457	18	.	.	PUNCT
cjfa-8193	458	1	on	on	ADP
cjfa-8193	458	2	the	the	DET
cjfa-8193	458	3	relation	relation	NOUN
cjfa-8193	458	4	between	between	ADP
cjfa-8193	458	5	the	the	DET
cjfa-8193	458	6	expected	expect	VERB
cjfa-8193	458	7	value	value	NOUN
cjfa-8193	458	8	and	and	CCONJ
cjfa-8193	458	9	the	the	DET
cjfa-8193	458	10	volatility	volatility	NOUN
cjfa-8193	458	11	of	of	ADP
cjfa-8193	458	12	the	the	DET
cjfa-8193	458	13	nominal	nominal	ADJ
cjfa-8193	458	14	excess	excess	ADJ
cjfa-8193	458	15	return	return	NOUN
cjfa-8193	458	16	on	on	ADP
cjfa-8193	458	17	stocks	stock	NOUN
cjfa-8193	458	18	.	.	PUNCT
cjfa-8193	459	1	the	the	DET
cjfa-8193	459	2	journal	journal	PROPN
cjfa-8193	459	3	of	of	ADP
cjfa-8193	459	4	finance	finance	NOUN
cjfa-8193	459	5	,	,	PUNCT
cjfa-8193	459	6	48	48	NUM
cjfa-8193	459	7	(	(	PUNCT
cjfa-8193	459	8	5	5	NUM
cjfa-8193	459	9	)	)	PUNCT
cjfa-8193	459	10	,	,	PUNCT
cjfa-8193	459	11	1779	1779	NUM
cjfa-8193	459	12	-	-	SYM
cjfa-8193	459	13	1801	1801	NUM
cjfa-8193	459	14	.	.	PUNCT
cjfa-8193	460	1	http://dx.doi.org/10.1111/j.1540-6261.1993.tb05128.x	http://dx.doi.org/10.1111/j.1540-6261.1993.tb05128.x	PROPN
cjfa-8193	460	2	.	.	PUNCT
cjfa-8193	460	3	gokcan	gokcan	PROPN
cjfa-8193	460	4	,	,	PUNCT
cjfa-8193	460	5	s.	s.	PROPN
cjfa-8193	460	6	(	(	PUNCT
cjfa-8193	460	7	2000	2000	NUM
cjfa-8193	460	8	)	)	PUNCT
cjfa-8193	460	9	.	.	PUNCT
cjfa-8193	461	1	forecasting	forecast	VERB
cjfa-8193	461	2	volatility	volatility	NOUN
cjfa-8193	461	3	of	of	ADP
cjfa-8193	461	4	emerging	emerge	VERB
cjfa-8193	461	5	stock	stock	NOUN
cjfa-8193	461	6	markets	market	NOUN
cjfa-8193	461	7	:	:	PUNCT
cjfa-8193	461	8	linear	linear	ADJ
cjfa-8193	461	9	versus	versus	ADP
cjfa-8193	461	10	non	non	ADJ
cjfa-8193	461	11	-	-	ADJ
cjfa-8193	461	12	linear	linear	ADJ
cjfa-8193	461	13	garch	garch	NOUN
cjfa-8193	461	14	models	model	NOUN
cjfa-8193	461	15	.	.	PUNCT
cjfa-8193	462	1	journal	journal	NOUN
cjfa-8193	462	2	of	of	ADP
cjfa-8193	462	3	forecasting	forecasting	NOUN
cjfa-8193	462	4	,	,	PUNCT
cjfa-8193	462	5	19	19	NUM
cjfa-8193	462	6	(	(	PUNCT
cjfa-8193	462	7	6	6	NUM
cjfa-8193	462	8	)	)	PUNCT
cjfa-8193	462	9	,	,	PUNCT
cjfa-8193	462	10	499	499	NUM
cjfa-8193	462	11	-	-	SYM
cjfa-8193	462	12	504	504	NUM
cjfa-8193	462	13	.	.	PUNCT
cjfa-8193	463	1	http://dx.doi	http://dx.doi	NOUN
cjfa-8193	463	2	.	.	PUNCT
cjfa-8193	464	1	org/10.1002/1099	org/10.1002/1099	NUM
cjfa-8193	464	2	-	-	PUNCT
cjfa-8193	464	3	131x(200011)19:6%3c499::aid	131x(200011)19:6%3c499::aid	NUM
cjfa-8193	464	4	-	-	PUNCT
cjfa-8193	464	5	for745%3e3.0.co;2	for745%3e3.0.co;2	NOUN
cjfa-8193	464	6	-	-	PUNCT
cjfa-8193	464	7	p.	p.	PROPN
cjfa-8193	464	8	hansen	hansen	PROPN
cjfa-8193	464	9	,	,	PUNCT
cjfa-8193	464	10	p.	p.	PROPN
cjfa-8193	464	11	r.	r.	PROPN
cjfa-8193	464	12	(	(	PUNCT
cjfa-8193	464	13	2005	2005	NUM
cjfa-8193	464	14	)	)	PUNCT
cjfa-8193	464	15	.	.	PUNCT
cjfa-8193	465	1	a	a	DET
cjfa-8193	465	2	test	test	NOUN
cjfa-8193	465	3	for	for	ADP
cjfa-8193	465	4	superior	superior	ADJ
cjfa-8193	465	5	predictive	predictive	ADJ
cjfa-8193	465	6	ability	ability	NOUN
cjfa-8193	465	7	.	.	PUNCT
cjfa-8193	466	1	journal	journal	NOUN
cjfa-8193	466	2	of	of	ADP
cjfa-8193	466	3	business	business	PROPN
cjfa-8193	466	4	&	&	CCONJ
cjfa-8193	466	5	economic	economic	ADJ
cjfa-8193	466	6	statistics	statistic	NOUN
cjfa-8193	466	7	,	,	PUNCT
cjfa-8193	466	8	23	23	NUM
cjfa-8193	466	9	(	(	PUNCT
cjfa-8193	466	10	4	4	NUM
cjfa-8193	466	11	)	)	PUNCT
cjfa-8193	466	12	,	,	PUNCT
cjfa-8193	466	13	365	365	NUM
cjfa-8193	466	14	-	-	SYM
cjfa-8193	466	15	380	380	NUM
cjfa-8193	466	16	.	.	PUNCT
cjfa-8193	467	1	http://dx.doi.org/10.1198/073500105000000063	http://dx.doi.org/10.1198/073500105000000063	PROPN
cjfa-8193	467	2	.	.	PUNCT
cjfa-8193	468	1	hansen	hansen	PROPN
cjfa-8193	468	2	,	,	PUNCT
cjfa-8193	468	3	p.	p.	PROPN
cjfa-8193	468	4	r.	r.	PROPN
cjfa-8193	468	5	,	,	PUNCT
cjfa-8193	468	6	&	&	CCONJ
cjfa-8193	468	7	lunde	lunde	PROPN
cjfa-8193	468	8	,	,	PUNCT
cjfa-8193	468	9	a.	a.	NOUN
cjfa-8193	468	10	(	(	PUNCT
cjfa-8193	468	11	2005	2005	NUM
cjfa-8193	468	12	)	)	PUNCT
cjfa-8193	468	13	.	.	PUNCT
cjfa-8193	469	1	a	a	DET
cjfa-8193	469	2	forecast	forecast	NOUN
cjfa-8193	469	3	comparison	comparison	NOUN
cjfa-8193	469	4	of	of	ADP
cjfa-8193	469	5	volatility	volatility	NOUN
cjfa-8193	469	6	models	model	NOUN
cjfa-8193	469	7	:	:	PUNCT
cjfa-8193	469	8	does	do	AUX
cjfa-8193	469	9	anything	anything	PRON
cjfa-8193	469	10	beat	beat	VERB
cjfa-8193	469	11	a	a	DET
cjfa-8193	469	12	garch	garch	NOUN
cjfa-8193	469	13	(	(	PUNCT
cjfa-8193	469	14	1	1	NUM
cjfa-8193	469	15	,	,	PUNCT
cjfa-8193	469	16	1	1	NUM
cjfa-8193	469	17	)	)	PUNCT
cjfa-8193	469	18	?	?	PUNCT
cjfa-8193	469	19	.	.	PUNCT
cjfa-8193	470	1	journal	journal	PROPN
cjfa-8193	470	2	of	of	ADP
cjfa-8193	470	3	applied	applied	ADJ
cjfa-8193	470	4	econometrics	econometric	NOUN
cjfa-8193	470	5	,	,	PUNCT
cjfa-8193	470	6	20	20	NUM
cjfa-8193	470	7	(	(	PUNCT
cjfa-8193	470	8	7	7	NUM
cjfa-8193	470	9	)	)	PUNCT
cjfa-8193	470	10	,	,	PUNCT
cjfa-8193	470	11	873	873	NUM
cjfa-8193	470	12	-	-	NUM
cjfa-8193	470	13	889	889	NUM
cjfa-8193	470	14	.	.	PUNCT
cjfa-8193	471	1	http://	http://	PROPN
cjfa-8193	471	2	dx.doi.org/10.1002/jae.800	dx.doi.org/10.1002/jae.800	PROPN
cjfa-8193	471	3	.	.	PUNCT
cjfa-8193	472	1	hansen	hansen	PROPN
cjfa-8193	472	2	,	,	PUNCT
cjfa-8193	472	3	p.	p.	PROPN
cjfa-8193	472	4	r.	r.	PROPN
cjfa-8193	472	5	,	,	PUNCT
cjfa-8193	472	6	&	&	CCONJ
cjfa-8193	472	7	lunde	lunde	PROPN
cjfa-8193	472	8	,	,	PUNCT
cjfa-8193	472	9	a.	a.	NOUN
cjfa-8193	472	10	(	(	PUNCT
cjfa-8193	472	11	2014	2014	NUM
cjfa-8193	472	12	)	)	PUNCT
cjfa-8193	472	13	.	.	PUNCT
cjfa-8193	473	1	mulcom	mulcom	PROPN
cjfa-8193	473	2	3.00	3.00	NUM
cjfa-8193	473	3	.	.	PUNCT
cjfa-8193	474	1	econometric	econometric	ADJ
cjfa-8193	474	2	toolkit	toolkit	NOUN
cjfa-8193	474	3	for	for	ADP
cjfa-8193	474	4	multiple	multiple	ADJ
cjfa-8193	474	5	comparisons	comparison	NOUN
cjfa-8193	474	6	.	.	PUNCT
cjfa-8193	475	1	unpublished	unpublished	ADJ
cjfa-8193	475	2	working	working	NOUN
cjfa-8193	475	3	paper	paper	NOUN
cjfa-8193	475	4	.	.	PUNCT
cjfa-8193	476	1	hansen	hansen	PROPN
cjfa-8193	476	2	,	,	PUNCT
cjfa-8193	476	3	p.	p.	PROPN
cjfa-8193	476	4	r.	r.	PROPN
cjfa-8193	476	5	,	,	PUNCT
cjfa-8193	476	6	lunde	lunde	PROPN
cjfa-8193	476	7	,	,	PUNCT
cjfa-8193	476	8	a.	a.	PROPN
cjfa-8193	476	9	,	,	PUNCT
cjfa-8193	476	10	&	&	CCONJ
cjfa-8193	476	11	nason	nason	PROPN
cjfa-8193	476	12	,	,	PUNCT
cjfa-8193	476	13	j.	j.	PROPN
cjfa-8193	476	14	m.	m.	PROPN
cjfa-8193	476	15	(	(	PUNCT
cjfa-8193	476	16	2011	2011	NUM
cjfa-8193	476	17	)	)	PUNCT
cjfa-8193	476	18	.	.	PUNCT
cjfa-8193	477	1	the	the	DET
cjfa-8193	477	2	model	model	NOUN
cjfa-8193	477	3	confidence	confidence	NOUN
cjfa-8193	477	4	set	set	VERB
cjfa-8193	477	5	.	.	PUNCT
cjfa-8193	478	1	econometrica	econometrica	PROPN
cjfa-8193	478	2	,	,	PUNCT
cjfa-8193	478	3	79	79	NUM
cjfa-8193	478	4	(	(	PUNCT
cjfa-8193	478	5	2	2	NUM
cjfa-8193	478	6	)	)	PUNCT
cjfa-8193	478	7	,	,	PUNCT
cjfa-8193	478	8	453	453	NUM
cjfa-8193	478	9	-	-	SYM
cjfa-8193	478	10	497	497	NUM
cjfa-8193	478	11	.	.	PUNCT
cjfa-8193	479	1	http://dx.doi.org/10.3982/ecta5771	http://dx.doi.org/10.3982/ecta5771	NOUN
cjfa-8193	479	2	.	.	PUNCT
cjfa-8193	480	1	heynen	heynen	PROPN
cjfa-8193	480	2	,	,	PUNCT
cjfa-8193	480	3	r.	r.	PROPN
cjfa-8193	480	4	c.	c.	PROPN
cjfa-8193	480	5	,	,	PUNCT
cjfa-8193	480	6	&	&	CCONJ
cjfa-8193	480	7	kat	kat	PROPN
cjfa-8193	480	8	,	,	PUNCT
cjfa-8193	480	9	h.	h.	PROPN
cjfa-8193	480	10	m.	m.	PROPN
cjfa-8193	480	11	(	(	PUNCT
cjfa-8193	480	12	1994	1994	NUM
cjfa-8193	480	13	)	)	PUNCT
cjfa-8193	480	14	.	.	PUNCT
cjfa-8193	481	1	volatility	volatility	NOUN
cjfa-8193	481	2	prediction	prediction	NOUN
cjfa-8193	481	3	:	:	PUNCT
cjfa-8193	481	4	a	a	DET
cjfa-8193	481	5	comparison	comparison	NOUN
cjfa-8193	481	6	of	of	ADP
cjfa-8193	481	7	the	the	DET
cjfa-8193	481	8	stochastic	stochastic	ADJ
cjfa-8193	481	9	volatility	volatility	NOUN
cjfa-8193	481	10	,	,	PUNCT
cjfa-8193	481	11	garch	garch	NOUN
cjfa-8193	481	12	(	(	PUNCT
cjfa-8193	481	13	1	1	NUM
cjfa-8193	481	14	,	,	PUNCT
cjfa-8193	481	15	1	1	NUM
cjfa-8193	481	16	)	)	PUNCT
cjfa-8193	481	17	and	and	CCONJ
cjfa-8193	481	18	egarch	egarch	NOUN
cjfa-8193	481	19	(	(	PUNCT
cjfa-8193	481	20	1	1	NUM
cjfa-8193	481	21	,	,	PUNCT
cjfa-8193	481	22	1	1	NUM
cjfa-8193	481	23	)	)	PUNCT
cjfa-8193	481	24	models	model	NOUN
cjfa-8193	481	25	.	.	PUNCT
cjfa-8193	482	1	the	the	DET
cjfa-8193	482	2	journal	journal	NOUN
cjfa-8193	482	3	of	of	ADP
cjfa-8193	482	4	derivatives	derivative	NOUN
cjfa-8193	482	5	,	,	PUNCT
cjfa-8193	482	6	2	2	NUM
cjfa-8193	482	7	(	(	PUNCT
cjfa-8193	482	8	2	2	NUM
cjfa-8193	482	9	)	)	PUNCT
cjfa-8193	482	10	,	,	PUNCT
cjfa-8193	482	11	50	50	NUM
cjfa-8193	482	12	–	–	PUNCT
cjfa-8193	482	13	–	–	PUNCT
cjfa-8193	482	14	65	65	NUM
cjfa-8193	482	15	.	.	PUNCT
cjfa-8193	483	1	http://dx.doi.org/10.3905/jod.1994.407912	http://dx.doi.org/10.3905/jod.1994.407912	PROPN
cjfa-8193	483	2	.	.	PUNCT
cjfa-8193	484	1	liu	liu	PROPN
cjfa-8193	484	2	,	,	PUNCT
cjfa-8193	484	3	h.	h.	PROPN
cjfa-8193	484	4	c.	c.	PROPN
cjfa-8193	484	5	,	,	PUNCT
cjfa-8193	484	6	&	&	CCONJ
cjfa-8193	484	7	hung	hung	PROPN
cjfa-8193	484	8	,	,	PUNCT
cjfa-8193	484	9	j.	j.	PROPN
cjfa-8193	484	10	c.	c.	PROPN
cjfa-8193	484	11	(	(	PUNCT
cjfa-8193	484	12	2010	2010	NUM
cjfa-8193	484	13	)	)	PUNCT
cjfa-8193	484	14	.	.	PUNCT
cjfa-8193	485	1	forecasting	forecast	VERB
cjfa-8193	485	2	s&p-100	s&p-100	NUM
cjfa-8193	485	3	stock	stock	NOUN
cjfa-8193	485	4	index	index	NOUN
cjfa-8193	485	5	volatility	volatility	NOUN
cjfa-8193	485	6	:	:	PUNCT
cjfa-8193	485	7	the	the	DET
cjfa-8193	485	8	role	role	NOUN
cjfa-8193	485	9	of	of	ADP
cjfa-8193	485	10	volatility	volatility	NOUN
cjfa-8193	485	11	asymmetry	asymmetry	NOUN
cjfa-8193	485	12	and	and	CCONJ
cjfa-8193	485	13	distributional	distributional	ADJ
cjfa-8193	485	14	assumption	assumption	NOUN
cjfa-8193	485	15	in	in	ADP
cjfa-8193	485	16	garch	garch	NOUN
cjfa-8193	485	17	models	model	NOUN
cjfa-8193	485	18	.	.	PUNCT
cjfa-8193	486	1	expert	expert	NOUN
cjfa-8193	486	2	systems	system	NOUN
cjfa-8193	486	3	with	with	ADP
cjfa-8193	486	4	applications	application	NOUN
cjfa-8193	486	5	,	,	PUNCT
cjfa-8193	486	6	37	37	NUM
cjfa-8193	486	7	(	(	PUNCT
cjfa-8193	486	8	7	7	NUM
cjfa-8193	486	9	)	)	PUNCT
cjfa-8193	486	10	,	,	PUNCT
cjfa-8193	486	11	4928	4928	NUM
cjfa-8193	486	12	-	-	SYM
cjfa-8193	486	13	4934	4934	NUM
cjfa-8193	486	14	.	.	PUNCT
cjfa-8193	487	1	http://dx.doi.org/10.1016/j.eswa.2009.12.022	http://dx.doi.org/10.1016/j.eswa.2009.12.022	PROPN
cjfa-8193	487	2	.	.	PUNCT
cjfa-8193	487	3	marcucci	marcucci	PROPN
cjfa-8193	487	4	,	,	PUNCT
cjfa-8193	487	5	j.	j.	PROPN
cjfa-8193	487	6	(	(	PUNCT
cjfa-8193	487	7	2005	2005	NUM
cjfa-8193	487	8	)	)	PUNCT
cjfa-8193	487	9	.	.	PUNCT
cjfa-8193	488	1	forecasting	forecast	VERB
cjfa-8193	488	2	stock	stock	NOUN
cjfa-8193	488	3	market	market	NOUN
cjfa-8193	488	4	volatility	volatility	NOUN
cjfa-8193	488	5	with	with	ADP
cjfa-8193	488	6	regime	regime	NOUN
cjfa-8193	488	7	-	-	PUNCT
cjfa-8193	488	8	switching	switch	VERB
cjfa-8193	488	9	garch	garch	NOUN
cjfa-8193	488	10	models	model	NOUN
cjfa-8193	488	11	.	.	PUNCT
cjfa-8193	489	1	studies	study	NOUN
cjfa-8193	489	2	in	in	ADP
cjfa-8193	489	3	nonlinear	nonlinear	ADJ
cjfa-8193	489	4	dynamics	dynamic	NOUN
cjfa-8193	489	5	&	&	CCONJ
cjfa-8193	489	6	econometrics	econometric	NOUN
cjfa-8193	489	7	,	,	PUNCT
cjfa-8193	489	8	9(4	9(4	NUM
cjfa-8193	489	9	)	)	PUNCT
cjfa-8193	489	10	,	,	PUNCT
cjfa-8193	489	11	1	1	NUM
cjfa-8193	489	12	-	-	SYM
cjfa-8193	489	13	53	53	NUM
cjfa-8193	489	14	.	.	PUNCT
cjfa-8193	489	15	http://dx.doi	http://dx.doi	NOUN
cjfa-8193	489	16	.	.	PUNCT
cjfa-8193	490	1	org/10.2202/1558	org/10.2202/1558	VERB
cjfa-8193	490	2	-	-	PUNCT
cjfa-8193	490	3	3708.1145	3708.1145	NOUN
cjfa-8193	490	4	.	.	PUNCT
cjfa-8193	491	1	h.	h.	PROPN
cjfa-8193	491	2	al	al	PROPN
cjfa-8193	491	3	-	-	PUNCT
cjfa-8193	491	4	hajieh	hajieh	PROPN
cjfa-8193	491	5	,	,	PUNCT
cjfa-8193	491	6	h.	h.	PROPN
cjfa-8193	491	7	alnemer	alnemer	PROPN
cjfa-8193	491	8	,	,	PUNCT
cjfa-8193	491	9	t.	t.	PROPN
cjfa-8193	491	10	rodgers	rodgers	PROPN
cjfa-8193	491	11	,	,	PUNCT
cjfa-8193	491	12	j.	j.	PROPN
cjfa-8193	491	13	niklewski26	niklewski26	PROPN
cjfa-8193	491	14	mcmillan	mcmillan	PROPN
cjfa-8193	491	15	,	,	PUNCT
cjfa-8193	491	16	d.	d.	PROPN
cjfa-8193	491	17	,	,	PUNCT
cjfa-8193	491	18	speight	speight	PROPN
cjfa-8193	491	19	,	,	PUNCT
cjfa-8193	491	20	a.	a.	PROPN
cjfa-8193	491	21	,	,	PUNCT
cjfa-8193	491	22	&	&	CCONJ
cjfa-8193	491	23	apgwilym	apgwilym	PROPN
cjfa-8193	491	24	,	,	PUNCT
cjfa-8193	491	25	o.	o.	NOUN
cjfa-8193	491	26	(	(	PUNCT
cjfa-8193	491	27	2000	2000	NUM
cjfa-8193	491	28	)	)	PUNCT
cjfa-8193	491	29	.	.	PUNCT
cjfa-8193	492	1	forecasting	forecast	VERB
cjfa-8193	492	2	uk	uk	PROPN
cjfa-8193	492	3	stock	stock	NOUN
cjfa-8193	492	4	market	market	NOUN
cjfa-8193	492	5	volatility	volatility	NOUN
cjfa-8193	492	6	.	.	PUNCT
cjfa-8193	493	1	applied	apply	VERB
cjfa-8193	493	2	financial	financial	ADJ
cjfa-8193	493	3	economics	economic	NOUN
cjfa-8193	493	4	,	,	PUNCT
cjfa-8193	493	5	10(4	10(4	NUM
cjfa-8193	493	6	)	)	PUNCT
cjfa-8193	493	7	,	,	PUNCT
cjfa-8193	493	8	435	435	NUM
cjfa-8193	493	9	-	-	SYM
cjfa-8193	493	10	448	448	NUM
cjfa-8193	493	11	.	.	PUNCT
cjfa-8193	494	1	http://dx.doi.org/10.1080/	http://dx.doi.org/10.1080/	NOUN
cjfa-8193	494	2	09603100050031561	09603100050031561	NUM
cjfa-8193	494	3	.	.	PUNCT
cjfa-8193	495	1	mittnik	mittnik	PROPN
cjfa-8193	495	2	,	,	PUNCT
cjfa-8193	495	3	s.	s.	PROPN
cjfa-8193	495	4	,	,	PUNCT
cjfa-8193	495	5	paolella	paolella	NOUN
cjfa-8193	495	6	,	,	PUNCT
cjfa-8193	495	7	m.	m.	NOUN
cjfa-8193	495	8	s.	s.	PROPN
cjfa-8193	495	9	,	,	PUNCT
cjfa-8193	495	10	&	&	CCONJ
cjfa-8193	495	11	rachev	rachev	VERB
cjfa-8193	495	12	,	,	PUNCT
cjfa-8193	495	13	s.	s.	PROPN
cjfa-8193	495	14	t.	t.	PROPN
cjfa-8193	495	15	(	(	PUNCT
cjfa-8193	495	16	2000	2000	NUM
cjfa-8193	495	17	)	)	PUNCT
cjfa-8193	495	18	.	.	PUNCT
cjfa-8193	496	1	diagnosing	diagnose	VERB
cjfa-8193	496	2	and	and	CCONJ
cjfa-8193	496	3	treating	treat	VERB
cjfa-8193	496	4	the	the	DET
cjfa-8193	496	5	fat	fat	ADJ
cjfa-8193	496	6	tails	tail	NOUN
cjfa-8193	496	7	in	in	ADP
cjfa-8193	496	8	financial	financial	ADJ
cjfa-8193	496	9	returns	return	NOUN
cjfa-8193	496	10	data	datum	NOUN
cjfa-8193	496	11	.	.	PUNCT
cjfa-8193	497	1	journal	journal	PROPN
cjfa-8193	497	2	of	of	ADP
cjfa-8193	497	3	empirical	empirical	ADJ
cjfa-8193	497	4	finance	finance	NOUN
cjfa-8193	497	5	,	,	PUNCT
cjfa-8193	497	6	7	7	NUM
cjfa-8193	497	7	(	(	PUNCT
cjfa-8193	497	8	3	3	NUM
cjfa-8193	497	9	)	)	PUNCT
cjfa-8193	497	10	,	,	PUNCT
cjfa-8193	497	11	389	389	NUM
cjfa-8193	497	12	-	-	SYM
cjfa-8193	497	13	416	416	NUM
cjfa-8193	497	14	.	.	PUNCT
cjfa-8193	498	1	http://dx.doi	http://dx.doi	NOUN
cjfa-8193	498	2	.	.	PUNCT
cjfa-8193	499	1	org/10.1016	org/10.1016	PROPN
cjfa-8193	499	2	/	/	SYM
cjfa-8193	499	3	s0927	s0927	PROPN
cjfa-8193	499	4	-	-	PUNCT
cjfa-8193	499	5	5398(00)00019	5398(00)00019	NUM
cjfa-8193	499	6	-	-	PUNCT
cjfa-8193	499	7	0	0	NUM
cjfa-8193	499	8	.	.	PUNCT
cjfa-8193	500	1	nelson	nelson	PROPN
cjfa-8193	500	2	,	,	PUNCT
cjfa-8193	500	3	d.	d.	PROPN
cjfa-8193	500	4	b.	b.	PROPN
cjfa-8193	500	5	(	(	PUNCT
cjfa-8193	500	6	1991	1991	NUM
cjfa-8193	500	7	)	)	PUNCT
cjfa-8193	500	8	.	.	PUNCT
cjfa-8193	501	1	conditional	conditional	ADJ
cjfa-8193	501	2	heteroskedasticity	heteroskedasticity	NOUN
cjfa-8193	501	3	in	in	ADP
cjfa-8193	501	4	asset	asset	NOUN
cjfa-8193	501	5	returns	return	NOUN
cjfa-8193	501	6	:	:	PUNCT
cjfa-8193	501	7	a	a	DET
cjfa-8193	501	8	new	new	ADJ
cjfa-8193	501	9	approach	approach	NOUN
cjfa-8193	501	10	.	.	PUNCT
cjfa-8193	502	1	econometrica	econometrica	PROPN
cjfa-8193	502	2	:	:	PUNCT
cjfa-8193	502	3	journal	journal	NOUN
cjfa-8193	502	4	of	of	ADP
cjfa-8193	502	5	the	the	DET
cjfa-8193	502	6	econometric	econometric	ADJ
cjfa-8193	502	7	society	society	NOUN
cjfa-8193	502	8	,	,	PUNCT
cjfa-8193	502	9	59(2	59(2	NUM
cjfa-8193	502	10	)	)	PUNCT
cjfa-8193	502	11	,	,	PUNCT
cjfa-8193	502	12	347	347	NUM
cjfa-8193	502	13	-	-	SYM
cjfa-8193	502	14	370	370	NUM
cjfa-8193	502	15	.	.	PUNCT
cjfa-8193	503	1	http://	http://	PROPN
cjfa-8193	503	2	dx.doi.org/10.2307/2938260	dx.doi.org/10.2307/2938260	PROPN
cjfa-8193	503	3	.	.	PUNCT