id	sid	tid	token	lemma	pos
ejpam-462	1	1	3_xxx_howe.dvi	3_xxx_howe.dvi	NUM
ejpam-462	1	2	european	european	ADJ
ejpam-462	1	3	journal	journal	NOUN
ejpam-462	1	4	of	of	ADP
ejpam-462	1	5	pure	pure	ADJ
ejpam-462	1	6	and	and	CCONJ
ejpam-462	1	7	applied	apply	VERB
ejpam-462	1	8	mathematics	mathematic	NOUN
ejpam-462	1	9	vol	vol	NOUN
ejpam-462	1	10	.	.	PUNCT
ejpam-462	2	1	3	3	NUM
ejpam-462	2	2	,	,	PUNCT
ejpam-462	2	3	no	no	INTJ
ejpam-462	2	4	.	.	NOUN
ejpam-462	2	5	3	3	NUM
ejpam-462	2	6	,	,	PUNCT
ejpam-462	2	7	2010	2010	NUM
ejpam-462	2	8	,	,	PUNCT
ejpam-462	2	9	382	382	NUM
ejpam-462	2	10	-	-	SYM
ejpam-462	2	11	405	405	NUM
ejpam-462	2	12	issn	issn	PROPN
ejpam-462	2	13	1307	1307	NUM
ejpam-462	2	14	-	-	SYM
ejpam-462	2	15	5543	5543	NUM
ejpam-462	2	16	–	–	PUNCT
ejpam-462	2	17	www.ejpam.com	www.ejpam.com	X
ejpam-462	2	18	special	special	ADJ
ejpam-462	2	19	issue	issue	NOUN
ejpam-462	2	20	on	on	ADP
ejpam-462	2	21	granger	granger	PROPN
ejpam-462	2	22	econometrics	econometric	NOUN
ejpam-462	2	23	and	and	CCONJ
ejpam-462	2	24	statistical	statistical	ADJ
ejpam-462	2	25	modeling	modeling	NOUN
ejpam-462	2	26	dedicated	dedicate	VERB
ejpam-462	2	27	to	to	ADP
ejpam-462	2	28	the	the	DET
ejpam-462	2	29	memory	memory	NOUN
ejpam-462	2	30	of	of	ADP
ejpam-462	2	31	prof	prof	NOUN
ejpam-462	2	32	.	.	PUNCT
ejpam-462	3	1	sir	sir	PROPN
ejpam-462	3	2	clive	clive	PROPN
ejpam-462	3	3	w.j	w.j	PROPN
ejpam-462	3	4	.	.	PROPN
ejpam-462	4	1	granger	granger	PROPN
ejpam-462	4	2	predictive	predictive	PROPN
ejpam-462	4	3	subset	subset	NOUN
ejpam-462	4	4	var	var	NOUN
ejpam-462	4	5	modeling	modeling	NOUN
ejpam-462	4	6	using	use	VERB
ejpam-462	4	7	the	the	DET
ejpam-462	4	8	genetic	genetic	ADJ
ejpam-462	4	9	algorithm	algorithm	NOUN
ejpam-462	4	10	and	and	CCONJ
ejpam-462	4	11	information	information	NOUN
ejpam-462	4	12	complexity	complexity	NOUN
ejpam-462	4	13	j.	j.	PROPN
ejpam-462	4	14	andrew	andrew	PROPN
ejpam-462	4	15	howe1∗	howe1∗	PROPN
ejpam-462	4	16	and	and	CCONJ
ejpam-462	4	17	hamparsum	hamparsum	VERB
ejpam-462	4	18	bozdogan2	bozdogan2	PROPN
ejpam-462	4	19	1	1	NUM
ejpam-462	4	20	tennessee	tennessee	PROPN
ejpam-462	4	21	valley	valley	PROPN
ejpam-462	4	22	authority	authority	PROPN
ejpam-462	4	23	,	,	PUNCT
ejpam-462	4	24	chattanooga	chattanooga	PROPN
ejpam-462	4	25	,	,	PUNCT
ejpam-462	4	26	tennessee	tennessee	PROPN
ejpam-462	4	27	,	,	PUNCT
ejpam-462	4	28	usa	usa	PROPN
ejpam-462	4	29	2	2	NUM
ejpam-462	4	30	university	university	PROPN
ejpam-462	4	31	of	of	ADP
ejpam-462	4	32	tennessee	tennessee	PROPN
ejpam-462	4	33	,	,	PUNCT
ejpam-462	4	34	knoxville	knoxville	PROPN
ejpam-462	4	35	,	,	PUNCT
ejpam-462	4	36	department	department	PROPN
ejpam-462	4	37	of	of	ADP
ejpam-462	4	38	statistics	statistic	NOUN
ejpam-462	4	39	,	,	PUNCT
ejpam-462	4	40	operations	operation	NOUN
ejpam-462	4	41	,	,	PUNCT
ejpam-462	4	42	and	and	CCONJ
ejpam-462	4	43	management	management	NOUN
ejpam-462	4	44	science	science	NOUN
ejpam-462	4	45	,	,	PUNCT
ejpam-462	4	46	stokely	stokely	PROPN
ejpam-462	4	47	management	management	NOUN
ejpam-462	4	48	center	center	PROPN
ejpam-462	4	49	,	,	PUNCT
ejpam-462	4	50	knoxville	knoxville	PROPN
ejpam-462	4	51	,	,	PUNCT
ejpam-462	4	52	tennessee	tennessee	PROPN
ejpam-462	4	53	37996	37996	NUM
ejpam-462	4	54	,	,	PUNCT
ejpam-462	4	55	usa	usa	PROPN
ejpam-462	4	56	abstract	abstract	NOUN
ejpam-462	4	57	.	.	PUNCT
ejpam-462	5	1	can	can	AUX
ejpam-462	5	2	we	we	PRON
ejpam-462	5	3	use	use	VERB
ejpam-462	5	4	lagged	lag	VERB
ejpam-462	5	5	values	value	NOUN
ejpam-462	5	6	of	of	ADP
ejpam-462	5	7	major	major	ADJ
ejpam-462	5	8	stock	stock	NOUN
ejpam-462	5	9	market	market	NOUN
ejpam-462	5	10	indices	index	NOUN
ejpam-462	5	11	to	to	PART
ejpam-462	5	12	provide	provide	VERB
ejpam-462	5	13	useful	useful	ADJ
ejpam-462	5	14	predictions	prediction	NOUN
ejpam-462	5	15	as	as	ADP
ejpam-462	5	16	a	a	DET
ejpam-462	5	17	standard	standard	ADJ
ejpam-462	5	18	vector	vector	NOUN
ejpam-462	5	19	autoregressive	autoregressive	ADJ
ejpam-462	5	20	model	model	NOUN
ejpam-462	5	21	?	?	PUNCT
ejpam-462	6	1	underlying	underlie	VERB
ejpam-462	6	2	this	this	DET
ejpam-462	6	3	application	application	NOUN
ejpam-462	6	4	,	,	PUNCT
ejpam-462	6	5	of	of	ADP
ejpam-462	6	6	course	course	NOUN
ejpam-462	6	7	,	,	PUNCT
ejpam-462	6	8	is	be	AUX
ejpam-462	6	9	the	the	DET
ejpam-462	6	10	question	question	NOUN
ejpam-462	6	11	of	of	ADP
ejpam-462	6	12	finding	find	VERB
ejpam-462	6	13	a	a	DET
ejpam-462	6	14	vector	vector	NOUN
ejpam-462	6	15	autoregressive	autoregressive	ADJ
ejpam-462	6	16	model	model	NOUN
ejpam-462	6	17	which	which	PRON
ejpam-462	6	18	makes	make	VERB
ejpam-462	6	19	accurate	accurate	ADJ
ejpam-462	6	20	and	and	CCONJ
ejpam-462	6	21	efficient	efficient	ADJ
ejpam-462	6	22	forecasts	forecast	NOUN
ejpam-462	6	23	.	.	PUNCT
ejpam-462	7	1	in	in	ADP
ejpam-462	7	2	this	this	DET
ejpam-462	7	3	paper	paper	NOUN
ejpam-462	7	4	,	,	PUNCT
ejpam-462	7	5	we	we	PRON
ejpam-462	7	6	use	use	VERB
ejpam-462	7	7	the	the	DET
ejpam-462	7	8	genetic	genetic	ADJ
ejpam-462	7	9	algorithm	algorithm	NOUN
ejpam-462	7	10	with	with	ADP
ejpam-462	7	11	information	information	NOUN
ejpam-462	7	12	complexity	complexity	NOUN
ejpam-462	7	13	criteria	criterion	NOUN
ejpam-462	7	14	as	as	ADP
ejpam-462	7	15	the	the	DET
ejpam-462	7	16	fitness	fitness	NOUN
ejpam-462	7	17	function	function	NOUN
ejpam-462	7	18	to	to	PART
ejpam-462	7	19	drive	drive	VERB
ejpam-462	7	20	subset	subset	NOUN
ejpam-462	7	21	selection	selection	NOUN
ejpam-462	7	22	and	and	CCONJ
ejpam-462	7	23	parameter	parameter	NOUN
ejpam-462	7	24	estimation	estimation	NOUN
ejpam-462	7	25	.	.	PUNCT
ejpam-462	8	1	in	in	ADP
ejpam-462	8	2	the	the	DET
ejpam-462	8	3	testing	testing	NOUN
ejpam-462	8	4	period	period	NOUN
ejpam-462	8	5	when	when	SCONJ
ejpam-462	8	6	the	the	DET
ejpam-462	8	7	target	target	NOUN
ejpam-462	8	8	index	index	NOUN
ejpam-462	8	9	lost	lose	VERB
ejpam-462	8	10	more	more	ADJ
ejpam-462	8	11	than	than	ADP
ejpam-462	8	12	15	15	NUM
ejpam-462	8	13	%	%	NOUN
ejpam-462	8	14	,	,	PUNCT
ejpam-462	8	15	the	the	DET
ejpam-462	8	16	identified	identify	VERB
ejpam-462	8	17	subset	subset	NOUN
ejpam-462	8	18	var	var	NOUN
ejpam-462	8	19	model	model	NOUN
ejpam-462	8	20	gained	gain	VERB
ejpam-462	8	21	over	over	ADP
ejpam-462	8	22	17	17	NUM
ejpam-462	8	23	%	%	NOUN
ejpam-462	8	24	.	.	PUNCT
ejpam-462	9	1	the	the	DET
ejpam-462	9	2	prediction	prediction	NOUN
ejpam-462	9	3	error	error	NOUN
ejpam-462	9	4	bands	band	NOUN
ejpam-462	9	5	built	build	VERB
ejpam-462	9	6	around	around	ADP
ejpam-462	9	7	the	the	DET
ejpam-462	9	8	forecasts	forecast	NOUN
ejpam-462	9	9	are	be	AUX
ejpam-462	9	10	half	half	ADV
ejpam-462	9	11	as	as	ADV
ejpam-462	9	12	wide	wide	ADJ
ejpam-462	9	13	as	as	ADP
ejpam-462	9	14	those	those	PRON
ejpam-462	9	15	obtained	obtain	VERB
ejpam-462	9	16	by	by	ADP
ejpam-462	9	17	the	the	DET
ejpam-462	9	18	saturated	saturate	VERB
ejpam-462	9	19	model	model	NOUN
ejpam-462	9	20	.	.	PUNCT
ejpam-462	10	1	using	use	VERB
ejpam-462	10	2	both	both	CCONJ
ejpam-462	10	3	simulation	simulation	NOUN
ejpam-462	10	4	and	and	CCONJ
ejpam-462	10	5	application	application	NOUN
ejpam-462	10	6	studies	study	NOUN
ejpam-462	10	7	,	,	PUNCT
ejpam-462	10	8	we	we	PRON
ejpam-462	10	9	present	present	VERB
ejpam-462	10	10	evidence	evidence	NOUN
ejpam-462	10	11	that	that	SCONJ
ejpam-462	10	12	even	even	ADV
ejpam-462	10	13	when	when	SCONJ
ejpam-462	10	14	the	the	DET
ejpam-462	10	15	typical	typical	ADJ
ejpam-462	10	16	regression	regression	NOUN
ejpam-462	10	17	assumptions	assumption	NOUN
ejpam-462	10	18	seem	seem	VERB
ejpam-462	10	19	to	to	PART
ejpam-462	10	20	be	be	AUX
ejpam-462	10	21	met	meet	VERB
ejpam-462	10	22	,	,	PUNCT
ejpam-462	10	23	the	the	DET
ejpam-462	10	24	var	var	NOUN
ejpam-462	10	25	model	model	NOUN
ejpam-462	10	26	is	be	AUX
ejpam-462	10	27	misspecified	misspecifie	VERB
ejpam-462	10	28	.	.	PUNCT
ejpam-462	11	1	2000	2000	NUM
ejpam-462	11	2	mathematics	mathematic	NOUN
ejpam-462	11	3	subject	subject	NOUN
ejpam-462	11	4	classifications	classification	NOUN
ejpam-462	11	5	:	:	PUNCT
ejpam-462	11	6	62hxx,62mxx,91bxx	62hxx,62mxx,91bxx	NUM
ejpam-462	11	7	key	key	ADJ
ejpam-462	11	8	words	word	NOUN
ejpam-462	11	9	and	and	CCONJ
ejpam-462	11	10	phrases	phrase	NOUN
ejpam-462	11	11	:	:	PUNCT
ejpam-462	11	12	model	model	NOUN
ejpam-462	11	13	selection	selection	NOUN
ejpam-462	11	14	,	,	PUNCT
ejpam-462	11	15	multivariate	multivariate	NOUN
ejpam-462	11	16	time	time	NOUN
ejpam-462	11	17	series	series	PROPN
ejpam-462	11	18	,	,	PUNCT
ejpam-462	11	19	forecast	forecast	NOUN
ejpam-462	11	20	evaluation	evaluation	NOUN
ejpam-462	11	21	,	,	PUNCT
ejpam-462	11	22	robustness	robustness	NOUN
ejpam-462	11	23	,	,	PUNCT
ejpam-462	11	24	information	information	NOUN
ejpam-462	11	25	criteria	criterion	NOUN
ejpam-462	11	26	,	,	PUNCT
ejpam-462	11	27	stochastic	stochastic	ADJ
ejpam-462	11	28	search	search	NOUN
ejpam-462	11	29	1	1	NUM
ejpam-462	11	30	.	.	PUNCT
ejpam-462	12	1	introduction	introduction	NOUN
ejpam-462	12	2	when	when	SCONJ
ejpam-462	12	3	considering	consider	VERB
ejpam-462	12	4	multivariate	multivariate	NOUN
ejpam-462	12	5	time	time	NOUN
ejpam-462	12	6	series	series	NOUN
ejpam-462	12	7	in	in	ADP
ejpam-462	12	8	the	the	DET
ejpam-462	12	9	context	context	NOUN
ejpam-462	12	10	of	of	ADP
ejpam-462	12	11	dynamic	dynamic	ADJ
ejpam-462	12	12	vector	vector	NOUN
ejpam-462	12	13	autoregressive	autoregressive	ADJ
ejpam-462	12	14	(	(	PUNCT
ejpam-462	12	15	var	var	NOUN
ejpam-462	12	16	)	)	PUNCT
ejpam-462	12	17	modeling	modeling	NOUN
ejpam-462	12	18	,	,	PUNCT
ejpam-462	12	19	how	how	SCONJ
ejpam-462	12	20	do	do	AUX
ejpam-462	12	21	we	we	PRON
ejpam-462	12	22	determine	determine	VERB
ejpam-462	12	23	the	the	DET
ejpam-462	12	24	structure	structure	NOUN
ejpam-462	12	25	of	of	ADP
ejpam-462	12	26	the	the	DET
ejpam-462	12	27	relationships	relationship	NOUN
ejpam-462	12	28	?	?	PUNCT
ejpam-462	13	1	in	in	ADP
ejpam-462	13	2	the	the	DET
ejpam-462	13	3	simple	simple	ADJ
ejpam-462	13	4	case	case	NOUN
ejpam-462	13	5	of	of	ADP
ejpam-462	13	6	2	2	NUM
ejpam-462	13	7	variables	variable	NOUN
ejpam-462	13	8	,	,	PUNCT
ejpam-462	13	9	say	say	VERB
ejpam-462	13	10	x	x	PUNCT
ejpam-462	13	11	and	and	CCONJ
ejpam-462	13	12	y	y	PROPN
ejpam-462	13	13	,	,	PUNCT
ejpam-462	13	14	and	and	CCONJ
ejpam-462	13	15	few	few	ADJ
ejpam-462	13	16	lags	lag	NOUN
ejpam-462	13	17	under	under	ADP
ejpam-462	13	18	consideration	consideration	NOUN
ejpam-462	13	19	,	,	PUNCT
ejpam-462	13	20	the	the	DET
ejpam-462	13	21	problem	problem	NOUN
ejpam-462	13	22	is	be	AUX
ejpam-462	13	23	relatively	relatively	ADV
ejpam-462	13	24	straightforward	straightforward	ADJ
ejpam-462	13	25	.	.	PUNCT
ejpam-462	14	1	for	for	ADP
ejpam-462	14	2	few	few	ADJ
ejpam-462	14	3	predictors	predictor	NOUN
ejpam-462	14	4	and	and	CCONJ
ejpam-462	14	5	lags	lag	NOUN
ejpam-462	14	6	,	,	PUNCT
ejpam-462	14	7	combinatorial	combinatorial	ADJ
ejpam-462	14	8	evaluation	evaluation	NOUN
ejpam-462	14	9	of	of	ADP
ejpam-462	14	10	all	all	DET
ejpam-462	14	11	possible	possible	ADJ
ejpam-462	14	12	subsets	subset	NOUN
ejpam-462	14	13	of	of	ADP
ejpam-462	14	14	responses	response	NOUN
ejpam-462	14	15	and	and	CCONJ
ejpam-462	14	16	predictors	predictor	NOUN
ejpam-462	14	17	is	be	AUX
ejpam-462	14	18	not	not	PART
ejpam-462	14	19	very	very	ADV
ejpam-462	14	20	computationally	computationally	ADV
ejpam-462	14	21	intensive	intensive	ADJ
ejpam-462	14	22	.	.	PUNCT
ejpam-462	15	1	as	as	ADV
ejpam-462	15	2	long	long	ADV
ejpam-462	15	3	as	as	SCONJ
ejpam-462	15	4	both	both	DET
ejpam-462	15	5	variables	variable	NOUN
ejpam-462	15	6	are	be	AUX
ejpam-462	15	7	∗corresponding	∗corresponde	VERB
ejpam-462	15	8	author	author	NOUN
ejpam-462	15	9	.	.	PUNCT
ejpam-462	16	1	email	email	NOUN
ejpam-462	16	2	addresses	address	NOUN
ejpam-462	16	3	:	:	PUNCT
ejpam-462	16	4	ahowe42	ahowe42	X
ejpam-462	16	5	�	�	NOUN
ejpam-462	16	6	gmail	gmail	NOUN
ejpam-462	16	7	.	.	PUNCT
ejpam-462	17	1	om	om	PROPN
ejpam-462	17	2	(	(	PUNCT
ejpam-462	17	3	a.	a.	NOUN
ejpam-462	17	4	howe	howe	PROPN
ejpam-462	17	5	)	)	PUNCT
ejpam-462	17	6	,	,	PUNCT
ejpam-462	17	7	bozdogan�utk.edu	bozdogan�utk.edu	PROPN
ejpam-462	17	8	(	(	PUNCT
ejpam-462	17	9	h.	h.	PROPN
ejpam-462	17	10	bozdogan	bozdogan	PROPN
ejpam-462	17	11	)	)	PUNCT
ejpam-462	17	12	http://www.ejpam.com	http://www.ejpam.com	X
ejpam-462	18	1	382	382	NUM
ejpam-462	19	1	c	c	X
ejpam-462	19	2	©	©	PROPN
ejpam-462	19	3	2010	2010	NUM
ejpam-462	19	4	ejpam	ejpam	NOUN
ejpam-462	19	5	all	all	DET
ejpam-462	19	6	rights	right	NOUN
ejpam-462	19	7	reserved	reserve	VERB
ejpam-462	19	8	.	.	PUNCT
ejpam-462	20	1	a.	a.	NOUN
ejpam-462	20	2	howe	howe	PROPN
ejpam-462	20	3	and	and	CCONJ
ejpam-462	20	4	h.	h.	PROPN
ejpam-462	20	5	bozdogan	bozdogan	PROPN
ejpam-462	20	6	/	/	SYM
ejpam-462	20	7	eur	eur	PROPN
ejpam-462	20	8	.	.	PUNCT
ejpam-462	21	1	j.	j.	PROPN
ejpam-462	21	2	pure	pure	PROPN
ejpam-462	21	3	appl	appl	PROPN
ejpam-462	21	4	.	.	PROPN
ejpam-462	21	5	math	math	PROPN
ejpam-462	21	6	,	,	PUNCT
ejpam-462	21	7	3	3	NUM
ejpam-462	21	8	(	(	PUNCT
ejpam-462	21	9	2010	2010	NUM
ejpam-462	21	10	)	)	PUNCT
ejpam-462	21	11	,	,	PUNCT
ejpam-462	21	12	382	382	NUM
ejpam-462	21	13	-	-	SYM
ejpam-462	21	14	405	405	NUM
ejpam-462	21	15	383	383	NUM
ejpam-462	21	16	stationary	stationary	NOUN
ejpam-462	21	17	,	,	PUNCT
ejpam-462	21	18	or	or	CCONJ
ejpam-462	21	19	integrated	integrate	VERB
ejpam-462	21	20	of	of	ADP
ejpam-462	21	21	order	order	NOUN
ejpam-462	21	22	1	1	NUM
ejpam-462	21	23	(	(	PUNCT
ejpam-462	21	24	i	i	PRON
ejpam-462	21	25	(	(	PUNCT
ejpam-462	21	26	0	0	NUM
ejpam-462	21	27	)	)	PUNCT
ejpam-462	21	28	)	)	PUNCT
ejpam-462	22	1	,	,	PUNCT
ejpam-462	22	2	we	we	PRON
ejpam-462	22	3	can	can	AUX
ejpam-462	22	4	use	use	VERB
ejpam-462	22	5	multivariate	multivariate	NOUN
ejpam-462	22	6	least	least	ADJ
ejpam-462	22	7	squares	square	NOUN
ejpam-462	22	8	regression	regression	NOUN
ejpam-462	22	9	.	.	PUNCT
ejpam-462	23	1	under	under	ADP
ejpam-462	23	2	the	the	DET
ejpam-462	23	3	usual	usual	ADJ
ejpam-462	23	4	assumption	assumption	NOUN
ejpam-462	23	5	of	of	ADP
ejpam-462	23	6	gaussianity	gaussianity	NOUN
ejpam-462	23	7	,	,	PUNCT
ejpam-462	23	8	the	the	DET
ejpam-462	23	9	var(q	var(q	PROPN
ejpam-462	23	10	)	)	PUNCT
ejpam-462	23	11	model	model	NOUN
ejpam-462	23	12	is	be	AUX
ejpam-462	23	13	given	give	VERB
ejpam-462	23	14	by	by	ADP
ejpam-462	23	15	(	(	PUNCT
ejpam-462	23	16	1	1	NUM
ejpam-462	23	17	):	):	PUNCT
ejpam-462	23	18	�	�	PROPN
ejpam-462	23	19	y	y	NOUN
ejpam-462	23	20	′t	′t	NOUN
ejpam-462	23	21	x	x	PUNCT
ejpam-462	23	22	′t	′t	PROPN
ejpam-462	23	23	�	�	PROPN
ejpam-462	23	24	=	=	SYM
ejpam-462	23	25	�	�	PROPN
ejpam-462	23	26	b01	b01	PROPN
ejpam-462	23	27	b02	b02	PROPN
ejpam-462	23	28	�	�	PROPN
ejpam-462	24	1	+	+	CCONJ
ejpam-462	24	2	q∑	q∑	PROPN
ejpam-462	25	1	i=1	i=1	PROPN
ejpam-462	25	2	�	�	PROPN
ejpam-462	26	1	φi11	φi11	PROPN
ejpam-462	26	2	φi12	φi12	PROPN
ejpam-462	26	3	φi21	φi21	PROPN
ejpam-462	26	4	φi21	φi21	PROPN
ejpam-462	26	5	�	�	PROPN
ejpam-462	26	6	�	�	PROPN
ejpam-462	26	7	y	y	PROPN
ejpam-462	26	8	′t−i	′t−i	NOUN
ejpam-462	26	9	x	x	X
ejpam-462	26	10	′t−i	′t−i	VERB
ejpam-462	26	11	�	�	PROPN
ejpam-462	26	12	+	+	CCONJ
ejpam-462	26	13	�	�	PROPN
ejpam-462	26	14	ǫ′y	ǫ′y	PROPN
ejpam-462	26	15	t	t	PROPN
ejpam-462	26	16	ǫ′x	ǫ′x	NUM
ejpam-462	26	17	t	t	PROPN
ejpam-462	26	18	�	�	PROPN
ejpam-462	26	19	.	.	PUNCT
ejpam-462	27	1	(	(	PUNCT
ejpam-462	27	2	1	1	X
ejpam-462	27	3	)	)	PUNCT
ejpam-462	27	4	the	the	DET
ejpam-462	27	5	ǫ	ǫ	NOUN
ejpam-462	27	6	are	be	AUX
ejpam-462	27	7	error	error	NOUN
ejpam-462	27	8	terms	term	NOUN
ejpam-462	27	9	drawn	draw	VERB
ejpam-462	27	10	from	from	ADP
ejpam-462	27	11	homoskedastic	homoskedastic	ADJ
ejpam-462	27	12	multivariate	multivariate	NOUN
ejpam-462	27	13	white	white	ADJ
ejpam-462	27	14	noise	noise	NOUN
ejpam-462	27	15	.	.	PUNCT
ejpam-462	28	1	the	the	DET
ejpam-462	28	2	principle	principle	NOUN
ejpam-462	28	3	of	of	ADP
ejpam-462	28	4	parsimony	parsimony	NOUN
ejpam-462	28	5	drives	drive	VERB
ejpam-462	28	6	us	we	PRON
ejpam-462	28	7	to	to	PART
ejpam-462	28	8	prefer	prefer	VERB
ejpam-462	28	9	small	small	ADJ
ejpam-462	28	10	q.	q.	NOUN
ejpam-462	28	11	doing	do	VERB
ejpam-462	28	12	so	so	ADV
ejpam-462	28	13	can	can	AUX
ejpam-462	28	14	protect	protect	VERB
ejpam-462	28	15	against	against	ADP
ejpam-462	28	16	overfitting	overfitte	VERB
ejpam-462	28	17	and	and	CCONJ
ejpam-462	28	18	lead	lead	VERB
ejpam-462	28	19	to	to	ADP
ejpam-462	28	20	more	more	ADV
ejpam-462	28	21	efficient	efficient	ADJ
ejpam-462	28	22	forecasts	forecast	NOUN
ejpam-462	28	23	;	;	PUNCT
ejpam-462	28	24	additionally	additionally	ADV
ejpam-462	28	25	,	,	PUNCT
ejpam-462	28	26	it	it	PRON
ejpam-462	28	27	is	be	AUX
ejpam-462	28	28	generally	generally	ADV
ejpam-462	28	29	unlikely	unlikely	ADJ
ejpam-462	28	30	that	that	SCONJ
ejpam-462	28	31	higher	high	ADJ
ejpam-462	28	32	-	-	PUNCT
ejpam-462	28	33	order	order	NOUN
ejpam-462	28	34	autoregressions	autoregression	NOUN
ejpam-462	28	35	are	be	AUX
ejpam-462	28	36	in	in	ADP
ejpam-462	28	37	effect	effect	NOUN
ejpam-462	28	38	for	for	ADP
ejpam-462	28	39	most	most	ADJ
ejpam-462	28	40	econometric	econometric	ADJ
ejpam-462	28	41	data	datum	NOUN
ejpam-462	28	42	.	.	PUNCT
ejpam-462	29	1	what	what	PRON
ejpam-462	29	2	can	can	AUX
ejpam-462	29	3	the	the	DET
ejpam-462	29	4	researcher	researcher	NOUN
ejpam-462	29	5	do	do	AUX
ejpam-462	29	6	,	,	PUNCT
ejpam-462	29	7	however	however	ADV
ejpam-462	29	8	,	,	PUNCT
ejpam-462	29	9	if	if	SCONJ
ejpam-462	29	10	there	there	PRON
ejpam-462	29	11	are	be	VERB
ejpam-462	29	12	many	many	ADJ
ejpam-462	29	13	time	time	NOUN
ejpam-462	29	14	series	series	NOUN
ejpam-462	29	15	under	under	ADP
ejpam-462	29	16	consideration	consideration	NOUN
ejpam-462	29	17	?	?	PUNCT
ejpam-462	30	1	for	for	ADP
ejpam-462	30	2	example	example	NOUN
ejpam-462	30	3	,	,	PUNCT
ejpam-462	30	4	consider	consider	VERB
ejpam-462	30	5	a	a	DET
ejpam-462	30	6	mere	mere	ADJ
ejpam-462	30	7	p	p	NOUN
ejpam-462	30	8	=	=	SYM
ejpam-462	30	9	2	2	NUM
ejpam-462	30	10	variables	variable	NOUN
ejpam-462	30	11	with	with	ADP
ejpam-462	30	12	lags	lag	NOUN
ejpam-462	30	13	from	from	ADP
ejpam-462	30	14	one	one	NUM
ejpam-462	30	15	to	to	ADP
ejpam-462	30	16	four	four	NUM
ejpam-462	30	17	;	;	PUNCT
ejpam-462	30	18	for	for	ADP
ejpam-462	30	19	ols	ol	NOUN
ejpam-462	30	20	the	the	DET
ejpam-462	30	21	researcher	researcher	NOUN
ejpam-462	30	22	has	have	VERB
ejpam-462	30	23	two	two	NUM
ejpam-462	30	24	responses	response	NOUN
ejpam-462	30	25	and	and	CCONJ
ejpam-462	30	26	eight	eight	NUM
ejpam-462	30	27	potential	potential	ADJ
ejpam-462	30	28	predictors	predictor	NOUN
ejpam-462	30	29	.	.	PUNCT
ejpam-462	31	1	along	along	ADP
ejpam-462	31	2	with	with	ADP
ejpam-462	31	3	an	an	DET
ejpam-462	31	4	intercept	intercept	NOUN
ejpam-462	31	5	term	term	NOUN
ejpam-462	31	6	to	to	PART
ejpam-462	31	7	estimate	estimate	VERB
ejpam-462	31	8	,	,	PUNCT
ejpam-462	31	9	there	there	PRON
ejpam-462	31	10	are	be	VERB
ejpam-462	31	11	218−1=	218−1=	NUM
ejpam-462	31	12	262,143	262,143	NUM
ejpam-462	31	13	asymmetric	asymmetric	ADJ
ejpam-462	31	14	subset	subset	VERB
ejpam-462	31	15	var	var	NOUN
ejpam-462	31	16	models	model	NOUN
ejpam-462	31	17	.	.	PUNCT
ejpam-462	32	1	thus	thus	ADV
ejpam-462	32	2	,	,	PUNCT
ejpam-462	32	3	as	as	ADP
ejpam-462	32	4	the	the	DET
ejpam-462	32	5	size	size	NOUN
ejpam-462	32	6	of	of	ADP
ejpam-462	32	7	the	the	DET
ejpam-462	32	8	likely	likely	ADJ
ejpam-462	32	9	universe	universe	NOUN
ejpam-462	32	10	increases	increase	VERB
ejpam-462	32	11	linearly	linearly	ADV
ejpam-462	32	12	,	,	PUNCT
ejpam-462	32	13	the	the	DET
ejpam-462	32	14	number	number	NOUN
ejpam-462	32	15	of	of	ADP
ejpam-462	32	16	combinations	combination	NOUN
ejpam-462	32	17	increases	increase	NOUN
ejpam-462	32	18	exponentially	exponentially	ADV
ejpam-462	32	19	;	;	PUNCT
ejpam-462	32	20	performing	perform	VERB
ejpam-462	32	21	complete	complete	ADJ
ejpam-462	32	22	enumerative	enumerative	ADJ
ejpam-462	32	23	subset	subset	NOUN
ejpam-462	32	24	analysis	analysis	NOUN
ejpam-462	32	25	quickly	quickly	ADV
ejpam-462	32	26	becomes	become	VERB
ejpam-462	32	27	impossible	impossible	ADJ
ejpam-462	32	28	.	.	PUNCT
ejpam-462	33	1	in	in	ADP
ejpam-462	33	2	the	the	DET
ejpam-462	33	3	realm	realm	NOUN
ejpam-462	33	4	of	of	ADP
ejpam-462	33	5	statistical	statistical	ADJ
ejpam-462	33	6	modeling	modeling	NOUN
ejpam-462	33	7	and	and	CCONJ
ejpam-462	33	8	data	datum	NOUN
ejpam-462	33	9	mining	mining	NOUN
ejpam-462	33	10	,	,	PUNCT
ejpam-462	33	11	this	this	DET
ejpam-462	33	12	situation	situation	NOUN
ejpam-462	33	13	is	be	AUX
ejpam-462	33	14	known	know	VERB
ejpam-462	33	15	as	as	ADP
ejpam-462	33	16	the	the	DET
ejpam-462	33	17	“	"	PUNCT
ejpam-462	33	18	curse	curse	NOUN
ejpam-462	33	19	of	of	ADP
ejpam-462	33	20	dimensionality	dimensionality	NOUN
ejpam-462	33	21	”	"	PUNCT
ejpam-462	33	22	.	.	PUNCT
ejpam-462	34	1	in	in	ADP
ejpam-462	34	2	most	most	ADJ
ejpam-462	34	3	applications	application	NOUN
ejpam-462	34	4	,	,	PUNCT
ejpam-462	34	5	a	a	DET
ejpam-462	34	6	priori	priori	ADJ
ejpam-462	34	7	information	information	NOUN
ejpam-462	34	8	useful	useful	ADJ
ejpam-462	34	9	for	for	ADP
ejpam-462	34	10	restricting	restrict	VERB
ejpam-462	34	11	terms	term	NOUN
ejpam-462	34	12	to	to	ADP
ejpam-462	34	13	0	0	NUM
ejpam-462	34	14	is	be	AUX
ejpam-462	34	15	rare	rare	ADJ
ejpam-462	34	16	.	.	PUNCT
ejpam-462	35	1	several	several	ADJ
ejpam-462	35	2	approaches	approach	NOUN
ejpam-462	35	3	have	have	AUX
ejpam-462	35	4	been	be	AUX
ejpam-462	35	5	proposed	propose	VERB
ejpam-462	35	6	to	to	PART
ejpam-462	35	7	impose	impose	VERB
ejpam-462	35	8	restrictions	restriction	NOUN
ejpam-462	35	9	,	,	PUNCT
ejpam-462	35	10	in	in	ADP
ejpam-462	35	11	an	an	DET
ejpam-462	35	12	effort	effort	NOUN
ejpam-462	35	13	to	to	PART
ejpam-462	35	14	make	make	VERB
ejpam-462	35	15	the	the	DET
ejpam-462	35	16	problem	problem	NOUN
ejpam-462	35	17	more	more	ADV
ejpam-462	35	18	tractable	tractable	ADJ
ejpam-462	35	19	.	.	PUNCT
ejpam-462	36	1	unfortunately	unfortunately	ADV
ejpam-462	36	2	,	,	PUNCT
ejpam-462	36	3	these	these	DET
ejpam-462	36	4	existing	exist	VERB
ejpam-462	36	5	attempts	attempt	NOUN
ejpam-462	36	6	bring	bring	VERB
ejpam-462	36	7	their	their	PRON
ejpam-462	36	8	own	own	ADJ
ejpam-462	36	9	problems	problem	NOUN
ejpam-462	36	10	.	.	PUNCT
ejpam-462	37	1	in	in	ADP
ejpam-462	37	2	this	this	DET
ejpam-462	37	3	paper	paper	NOUN
ejpam-462	37	4	,	,	PUNCT
ejpam-462	37	5	we	we	PRON
ejpam-462	37	6	propose	propose	VERB
ejpam-462	37	7	and	and	CCONJ
ejpam-462	37	8	present	present	VERB
ejpam-462	37	9	the	the	DET
ejpam-462	37	10	efficacy	efficacy	NOUN
ejpam-462	37	11	of	of	ADP
ejpam-462	37	12	a	a	DET
ejpam-462	37	13	stochastic	stochastic	ADJ
ejpam-462	37	14	search	search	NOUN
ejpam-462	37	15	procedure	procedure	NOUN
ejpam-462	37	16	known	know	VERB
ejpam-462	37	17	as	as	ADP
ejpam-462	37	18	the	the	DET
ejpam-462	37	19	genetic	genetic	ADJ
ejpam-462	37	20	algorithm	algorithm	NOUN
ejpam-462	37	21	(	(	PUNCT
ejpam-462	37	22	ga	ga	PROPN
ejpam-462	37	23	)	)	PUNCT
ejpam-462	37	24	.	.	PUNCT
ejpam-462	38	1	of	of	ADP
ejpam-462	38	2	course	course	NOUN
ejpam-462	38	3	,	,	PUNCT
ejpam-462	38	4	the	the	DET
ejpam-462	38	5	effectiveness	effectiveness	NOUN
ejpam-462	38	6	of	of	ADP
ejpam-462	38	7	any	any	DET
ejpam-462	38	8	search	search	NOUN
ejpam-462	38	9	algorithm	algorithm	NOUN
ejpam-462	38	10	is	be	AUX
ejpam-462	38	11	strongly	strongly	ADV
ejpam-462	38	12	affected	affect	VERB
ejpam-462	38	13	by	by	ADP
ejpam-462	38	14	the	the	DET
ejpam-462	38	15	choice	choice	NOUN
ejpam-462	38	16	of	of	ADP
ejpam-462	38	17	the	the	DET
ejpam-462	38	18	fitness	fitness	NOUN
ejpam-462	38	19	function	function	NOUN
ejpam-462	38	20	which	which	PRON
ejpam-462	38	21	is	be	AUX
ejpam-462	38	22	to	to	PART
ejpam-462	38	23	be	be	AUX
ejpam-462	38	24	optimized	optimize	VERB
ejpam-462	38	25	.	.	PUNCT
ejpam-462	39	1	to	to	PART
ejpam-462	39	2	drive	drive	VERB
ejpam-462	39	3	the	the	DET
ejpam-462	39	4	model	model	NOUN
ejpam-462	39	5	selection	selection	NOUN
ejpam-462	39	6	process	process	NOUN
ejpam-462	39	7	,	,	PUNCT
ejpam-462	39	8	we	we	PRON
ejpam-462	39	9	use	use	VERB
ejpam-462	39	10	the	the	DET
ejpam-462	39	11	information	information	NOUN
ejpam-462	39	12	complexity	complexity	NOUN
ejpam-462	39	13	criterion	criterion	NOUN
ejpam-462	39	14	icom	icom	PROPN
ejpam-462	39	15	p	p	X
ejpam-462	39	16	;	;	PUNCT
ejpam-462	39	17	in	in	ADP
ejpam-462	39	18	the	the	DET
ejpam-462	39	19	spirit	spirit	NOUN
ejpam-462	39	20	of	of	ADP
ejpam-462	39	21	the	the	DET
ejpam-462	39	22	well	well	ADV
ejpam-462	39	23	known	know	VERB
ejpam-462	39	24	aic	aic	PROPN
ejpam-462	39	25	and	and	CCONJ
ejpam-462	39	26	sbc	sbc	PROPN
ejpam-462	39	27	criteria	criterion	NOUN
ejpam-462	39	28	.	.	PUNCT
ejpam-462	40	1	icom	icom	PROPN
ejpam-462	40	2	p	p	PROPN
ejpam-462	40	3	was	be	AUX
ejpam-462	40	4	first	first	ADV
ejpam-462	40	5	introduced	introduce	VERB
ejpam-462	40	6	by	by	ADP
ejpam-462	40	7	[	[	X
ejpam-462	40	8	5	5	NUM
ejpam-462	40	9	]	]	PUNCT
ejpam-462	40	10	.	.	PUNCT
ejpam-462	41	1	in	in	ADP
ejpam-462	41	2	our	our	PRON
ejpam-462	41	3	numerical	numerical	ADJ
ejpam-462	41	4	examples	example	NOUN
ejpam-462	41	5	,	,	PUNCT
ejpam-462	41	6	we	we	PRON
ejpam-462	41	7	first	first	ADV
ejpam-462	41	8	demonstrate	demonstrate	VERB
ejpam-462	41	9	our	our	PRON
ejpam-462	41	10	methods	method	NOUN
ejpam-462	41	11	with	with	ADP
ejpam-462	41	12	a	a	DET
ejpam-462	41	13	monte	monte	PROPN
ejpam-462	41	14	carlo	carlo	PROPN
ejpam-462	41	15	simulation	simulation	PROPN
ejpam-462	41	16	study	study	PROPN
ejpam-462	41	17	,	,	PUNCT
ejpam-462	41	18	in	in	ADP
ejpam-462	41	19	which	which	PRON
ejpam-462	41	20	we	we	PRON
ejpam-462	41	21	show	show	VERB
ejpam-462	41	22	that	that	SCONJ
ejpam-462	41	23	the	the	DET
ejpam-462	41	24	estimated	estimate	VERB
ejpam-462	41	25	subset	subset	VERB
ejpam-462	41	26	var	var	NOUN
ejpam-462	41	27	model	model	NOUN
ejpam-462	41	28	outperforms	outperform	VERB
ejpam-462	41	29	the	the	DET
ejpam-462	41	30	saturated	saturated	ADJ
ejpam-462	41	31	(	(	PUNCT
ejpam-462	41	32	all	all	DET
ejpam-462	41	33	predictors	predictor	NOUN
ejpam-462	41	34	included	include	VERB
ejpam-462	41	35	)	)	PUNCT
ejpam-462	41	36	model	model	NOUN
ejpam-462	41	37	.	.	PUNCT
ejpam-462	42	1	secondly	secondly	ADV
ejpam-462	42	2	,	,	PUNCT
ejpam-462	42	3	we	we	PRON
ejpam-462	42	4	apply	apply	VERB
ejpam-462	42	5	the	the	DET
ejpam-462	42	6	methods	method	NOUN
ejpam-462	42	7	to	to	ADP
ejpam-462	42	8	the	the	DET
ejpam-462	42	9	practical	practical	ADJ
ejpam-462	42	10	stock	stock	NOUN
ejpam-462	42	11	-	-	PUNCT
ejpam-462	42	12	market	market	NOUN
ejpam-462	42	13	movement	movement	NOUN
ejpam-462	42	14	prediction	prediction	NOUN
ejpam-462	42	15	problem	problem	NOUN
ejpam-462	42	16	.	.	PUNCT
ejpam-462	43	1	given	give	VERB
ejpam-462	43	2	a	a	DET
ejpam-462	43	3	subset	subset	NOUN
ejpam-462	43	4	of	of	ADP
ejpam-462	43	5	major	major	ADJ
ejpam-462	43	6	stock	stock	NOUN
ejpam-462	43	7	market	market	NOUN
ejpam-462	43	8	indices	index	NOUN
ejpam-462	43	9	,	,	PUNCT
ejpam-462	43	10	can	can	AUX
ejpam-462	43	11	we	we	PRON
ejpam-462	43	12	use	use	VERB
ejpam-462	43	13	their	their	PRON
ejpam-462	43	14	lagged	lag	VERB
ejpam-462	43	15	values	value	NOUN
ejpam-462	43	16	to	to	PART
ejpam-462	43	17	provide	provide	VERB
ejpam-462	43	18	useful	useful	ADJ
ejpam-462	43	19	predictions	prediction	NOUN
ejpam-462	43	20	for	for	ADP
ejpam-462	43	21	themselves	themselves	PRON
ejpam-462	43	22	as	as	ADP
ejpam-462	43	23	a	a	DET
ejpam-462	43	24	standard	standard	ADJ
ejpam-462	43	25	var	var	NOUN
ejpam-462	43	26	model	model	NOUN
ejpam-462	43	27	?	?	PUNCT
ejpam-462	44	1	the	the	DET
ejpam-462	44	2	indices	index	NOUN
ejpam-462	44	3	we	we	PRON
ejpam-462	44	4	use	use	VERB
ejpam-462	44	5	are	be	AUX
ejpam-462	44	6	:	:	PUNCT
ejpam-462	44	7	dj20	dj20	PROPN
ejpam-462	44	8	:	:	PUNCT
ejpam-462	44	9	dow	dow	PROPN
ejpam-462	44	10	jones	jones	PROPN
ejpam-462	44	11	20	20	NUM
ejpam-462	44	12	mid	mid	PROPN
ejpam-462	44	13	:	:	PUNCT
ejpam-462	44	14	amex	amex	PROPN
ejpam-462	44	15	midcap	midcap	PROPN
ejpam-462	44	16	400	400	NUM
ejpam-462	44	17	ndx	ndx	NOUN
ejpam-462	44	18	:	:	PUNCT
ejpam-462	44	19	nasdaq	nasdaq	PROPN
ejpam-462	44	20	100	100	NUM
ejpam-462	44	21	rut	rut	NOUN
ejpam-462	44	22	:	:	PUNCT
ejpam-462	44	23	russell	russell	PROPN
ejpam-462	44	24	2000	2000	NUM
ejpam-462	44	25	spx	spx	PROPN
ejpam-462	44	26	:	:	PUNCT
ejpam-462	44	27	standard	standard	PROPN
ejpam-462	44	28	&	&	CCONJ
ejpam-462	44	29	poor	poor	PROPN
ejpam-462	44	30	’s	’s	PART
ejpam-462	44	31	s&p	s&p	PROPN
ejpam-462	44	32	500	500	NUM
ejpam-462	44	33	xau	xau	ADV
ejpam-462	44	34	:	:	PUNCT
ejpam-462	44	35	amex	amex	PROPN
ejpam-462	44	36	gold	gold	NOUN
ejpam-462	44	37	producers	producer	NOUN
ejpam-462	44	38	using	use	VERB
ejpam-462	44	39	our	our	PRON
ejpam-462	44	40	methods	method	NOUN
ejpam-462	44	41	,	,	PUNCT
ejpam-462	44	42	we	we	PRON
ejpam-462	44	43	obtain	obtain	VERB
ejpam-462	44	44	accurate	accurate	ADJ
ejpam-462	44	45	and	and	CCONJ
ejpam-462	44	46	efficient	efficient	ADJ
ejpam-462	44	47	forecasts	forecast	NOUN
ejpam-462	44	48	.	.	PUNCT
ejpam-462	45	1	to	to	PART
ejpam-462	45	2	set	set	VERB
ejpam-462	45	3	the	the	DET
ejpam-462	45	4	stage	stage	NOUN
ejpam-462	45	5	,	,	PUNCT
ejpam-462	45	6	the	the	DET
ejpam-462	45	7	remainder	remainder	NOUN
ejpam-462	45	8	of	of	ADP
ejpam-462	45	9	this	this	DET
ejpam-462	45	10	paper	paper	NOUN
ejpam-462	45	11	is	be	AUX
ejpam-462	45	12	organized	organize	VERB
ejpam-462	45	13	as	as	SCONJ
ejpam-462	45	14	follows	follow	VERB
ejpam-462	45	15	.	.	PUNCT
ejpam-462	46	1	in	in	ADP
ejpam-462	46	2	section	section	NOUN
ejpam-462	46	3	2	2	NUM
ejpam-462	46	4	,	,	PUNCT
ejpam-462	46	5	we	we	PRON
ejpam-462	46	6	discuss	discuss	VERB
ejpam-462	46	7	vector	vector	NOUN
ejpam-462	46	8	autoregressive	autoregressive	ADJ
ejpam-462	46	9	modeling	modeling	NOUN
ejpam-462	46	10	,	,	PUNCT
ejpam-462	46	11	and	and	CCONJ
ejpam-462	46	12	some	some	PRON
ejpam-462	46	13	of	of	ADP
ejpam-462	46	14	the	the	DET
ejpam-462	46	15	issues	issue	NOUN
ejpam-462	46	16	that	that	PRON
ejpam-462	46	17	must	must	AUX
ejpam-462	46	18	be	be	AUX
ejpam-462	46	19	addressed	address	VERB
ejpam-462	46	20	.	.	PUNCT
ejpam-462	47	1	section	section	NOUN
ejpam-462	47	2	3	3	NUM
ejpam-462	47	3	gives	give	VERB
ejpam-462	47	4	background	background	NOUN
ejpam-462	47	5	information	information	NOUN
ejpam-462	47	6	a.	a.	NOUN
ejpam-462	47	7	howe	howe	PROPN
ejpam-462	47	8	and	and	CCONJ
ejpam-462	47	9	h.	h.	PROPN
ejpam-462	47	10	bozdogan	bozdogan	PROPN
ejpam-462	47	11	/	/	SYM
ejpam-462	47	12	eur	eur	PROPN
ejpam-462	47	13	.	.	PUNCT
ejpam-462	48	1	j.	j.	PROPN
ejpam-462	48	2	pure	pure	PROPN
ejpam-462	48	3	appl	appl	PROPN
ejpam-462	48	4	.	.	PROPN
ejpam-462	48	5	math	math	PROPN
ejpam-462	48	6	,	,	PUNCT
ejpam-462	48	7	3	3	NUM
ejpam-462	48	8	(	(	PUNCT
ejpam-462	48	9	2010	2010	NUM
ejpam-462	48	10	)	)	PUNCT
ejpam-462	48	11	,	,	PUNCT
ejpam-462	48	12	382	382	NUM
ejpam-462	48	13	-	-	SYM
ejpam-462	48	14	405	405	NUM
ejpam-462	48	15	384	384	NUM
ejpam-462	48	16	on	on	ADP
ejpam-462	48	17	the	the	DET
ejpam-462	48	18	genetic	genetic	ADJ
ejpam-462	48	19	algorithm	algorithm	NOUN
ejpam-462	48	20	.	.	PUNCT
ejpam-462	49	1	we	we	PRON
ejpam-462	49	2	discuss	discuss	VERB
ejpam-462	49	3	and	and	CCONJ
ejpam-462	49	4	give	give	VERB
ejpam-462	49	5	the	the	DET
ejpam-462	49	6	derived	derive	VERB
ejpam-462	49	7	forms	form	NOUN
ejpam-462	49	8	of	of	ADP
ejpam-462	49	9	information	information	NOUN
ejpam-462	49	10	criteria	criterion	NOUN
ejpam-462	49	11	and	and	CCONJ
ejpam-462	49	12	complexity	complexity	NOUN
ejpam-462	49	13	in	in	ADP
ejpam-462	49	14	section	section	NOUN
ejpam-462	49	15	4	4	NUM
ejpam-462	49	16	.	.	PUNCT
ejpam-462	50	1	in	in	ADP
ejpam-462	50	2	section	section	NOUN
ejpam-462	50	3	5	5	NUM
ejpam-462	50	4	,	,	PUNCT
ejpam-462	50	5	we	we	PRON
ejpam-462	50	6	provide	provide	VERB
ejpam-462	50	7	numerical	numerical	ADJ
ejpam-462	50	8	results	result	NOUN
ejpam-462	50	9	on	on	ADP
ejpam-462	50	10	both	both	CCONJ
ejpam-462	50	11	a	a	DET
ejpam-462	50	12	monte	monte	PROPN
ejpam-462	50	13	carlo	carlo	PROPN
ejpam-462	50	14	simulation	simulation	PROPN
ejpam-462	50	15	study	study	PROPN
ejpam-462	50	16	and	and	CCONJ
ejpam-462	50	17	the	the	DET
ejpam-462	50	18	aforementioned	aforementioned	ADJ
ejpam-462	50	19	stock	stock	NOUN
ejpam-462	50	20	market	market	NOUN
ejpam-462	50	21	prediction	prediction	NOUN
ejpam-462	50	22	problem	problem	NOUN
ejpam-462	50	23	.	.	PUNCT
ejpam-462	51	1	section	section	NOUN
ejpam-462	51	2	6	6	NUM
ejpam-462	51	3	concludes	conclude	VERB
ejpam-462	51	4	the	the	DET
ejpam-462	51	5	paper	paper	NOUN
ejpam-462	51	6	with	with	ADP
ejpam-462	51	7	remarks	remark	NOUN
ejpam-462	51	8	.	.	PUNCT
ejpam-462	52	1	2	2	X
ejpam-462	52	2	.	.	X
ejpam-462	52	3	vector	vector	NOUN
ejpam-462	52	4	autoregressive	autoregressive	ADJ
ejpam-462	52	5	(	(	PUNCT
ejpam-462	52	6	var	var	NOUN
ejpam-462	52	7	)	)	PUNCT
ejpam-462	52	8	modeling	model	VERB
ejpam-462	52	9	the	the	DET
ejpam-462	52	10	purpose	purpose	NOUN
ejpam-462	52	11	of	of	ADP
ejpam-462	52	12	developing	develop	VERB
ejpam-462	52	13	a	a	DET
ejpam-462	52	14	vector	vector	NOUN
ejpam-462	52	15	autoregressive	autoregressive	ADJ
ejpam-462	52	16	model	model	NOUN
ejpam-462	52	17	is	be	AUX
ejpam-462	52	18	to	to	PART
ejpam-462	52	19	identify	identify	VERB
ejpam-462	52	20	the	the	DET
ejpam-462	52	21	relationships	relationship	NOUN
ejpam-462	52	22	between	between	ADP
ejpam-462	52	23	a	a	DET
ejpam-462	52	24	set	set	NOUN
ejpam-462	52	25	of	of	ADP
ejpam-462	52	26	linear	linear	ADJ
ejpam-462	52	27	time	time	NOUN
ejpam-462	52	28	series	series	NOUN
ejpam-462	52	29	so	so	SCONJ
ejpam-462	52	30	as	as	SCONJ
ejpam-462	52	31	to	to	PART
ejpam-462	52	32	develop	develop	VERB
ejpam-462	52	33	accurate	accurate	ADJ
ejpam-462	52	34	and	and	CCONJ
ejpam-462	52	35	precise	precise	ADJ
ejpam-462	52	36	forecasts	forecast	NOUN
ejpam-462	52	37	for	for	ADP
ejpam-462	52	38	the	the	DET
ejpam-462	52	39	series	series	NOUN
ejpam-462	52	40	included	include	VERB
ejpam-462	52	41	.	.	PUNCT
ejpam-462	53	1	in	in	ADP
ejpam-462	53	2	a	a	DET
ejpam-462	53	3	structural	structural	ADJ
ejpam-462	53	4	var	var	NOUN
ejpam-462	53	5	model	model	NOUN
ejpam-462	53	6	,	,	PUNCT
ejpam-462	53	7	the	the	DET
ejpam-462	53	8	time	time	NOUN
ejpam-462	53	9	path	path	NOUN
ejpam-462	53	10	of	of	ADP
ejpam-462	53	11	each	each	DET
ejpam-462	53	12	variable	variable	NOUN
ejpam-462	53	13	is	be	AUX
ejpam-462	53	14	influenced	influence	VERB
ejpam-462	53	15	by	by	ADP
ejpam-462	53	16	the	the	DET
ejpam-462	53	17	lags	lag	NOUN
ejpam-462	53	18	of	of	ADP
ejpam-462	53	19	all	all	DET
ejpam-462	53	20	included	include	VERB
ejpam-462	53	21	variables	variable	NOUN
ejpam-462	53	22	.	.	PUNCT
ejpam-462	54	1	for	for	ADP
ejpam-462	54	2	example	example	NOUN
ejpam-462	54	3	,	,	PUNCT
ejpam-462	54	4	consider	consider	VERB
ejpam-462	54	5	(	(	PUNCT
ejpam-462	54	6	2	2	NUM
ejpam-462	54	7	)	)	PUNCT
ejpam-462	54	8	,	,	PUNCT
ejpam-462	54	9	with	with	ADP
ejpam-462	54	10	a	a	DET
ejpam-462	54	11	simple	simple	ADJ
ejpam-462	54	12	var(2	var(2	NOUN
ejpam-462	54	13	)	)	PUNCT
ejpam-462	54	14	model	model	NOUN
ejpam-462	54	15	in	in	ADP
ejpam-462	54	16	standard	standard	ADJ
ejpam-462	54	17	form	form	NOUN
ejpam-462	54	18	(	(	PUNCT
ejpam-462	54	19	contemporaneous	contemporaneous	ADJ
ejpam-462	54	20	effects	effect	NOUN
ejpam-462	54	21	removed	remove	VERB
ejpam-462	54	22	)	)	PUNCT
ejpam-462	54	23	.	.	PUNCT
ejpam-462	55	1	yt	yt	PROPN
ejpam-462	55	2	=	=	PUNCT
ejpam-462	55	3	a10	a10	NOUN
ejpam-462	55	4	+	+	CCONJ
ejpam-462	55	5	a1_11	a1_11	PROPN
ejpam-462	55	6	yt−1	yt−1	PROPN
ejpam-462	55	7	+	+	PROPN
ejpam-462	55	8	a1_12zt−1	a1_12zt−1	PROPN
ejpam-462	56	1	+	+	CCONJ
ejpam-462	56	2	a2_11	a2_11	ADJ
ejpam-462	56	3	yt−2	yt−2	NOUN
ejpam-462	56	4	+	+	CCONJ
ejpam-462	56	5	a2_12zt−2	a2_12zt−2	PROPN
ejpam-462	56	6	+	+	NUM
ejpam-462	56	7	e1	e1	PROPN
ejpam-462	56	8	t	t	NOUN
ejpam-462	56	9	zt	zt	PROPN
ejpam-462	56	10	=	=	SYM
ejpam-462	56	11	a20	a20	PROPN
ejpam-462	56	12	+	+	CCONJ
ejpam-462	56	13	a1_21	a1_21	PROPN
ejpam-462	56	14	yt−1	yt−1	PROPN
ejpam-462	56	15	+	+	PROPN
ejpam-462	56	16	a1_22zt−1	a1_22zt−1	PROPN
ejpam-462	56	17	+	+	CCONJ
ejpam-462	56	18	a2_21	a2_21	PROPN
ejpam-462	56	19	yt−2	yt−2	NOUN
ejpam-462	56	20	+	+	CCONJ
ejpam-462	56	21	a2_22zt−2	a2_22zt−2	PROPN
ejpam-462	56	22	+	+	NUM
ejpam-462	56	23	e2	e2	PROPN
ejpam-462	56	24	t	t	PROPN
ejpam-462	56	25	.	.	PUNCT
ejpam-462	57	1	(	(	PUNCT
ejpam-462	57	2	2	2	X
ejpam-462	57	3	)	)	PUNCT
ejpam-462	57	4	a	a	DET
ejpam-462	57	5	symmetric	symmetric	ADJ
ejpam-462	57	6	var	var	NOUN
ejpam-462	57	7	model	model	NOUN
ejpam-462	57	8	is	be	AUX
ejpam-462	57	9	one	one	NUM
ejpam-462	57	10	in	in	ADP
ejpam-462	57	11	which	which	PRON
ejpam-462	57	12	a	a	DET
ejpam-462	57	13	lag	lag	NOUN
ejpam-462	57	14	of	of	ADP
ejpam-462	57	15	a	a	DET
ejpam-462	57	16	specific	specific	ADJ
ejpam-462	57	17	variable	variable	NOUN
ejpam-462	57	18	is	be	AUX
ejpam-462	57	19	included	include	VERB
ejpam-462	57	20	for	for	ADP
ejpam-462	57	21	all	all	DET
ejpam-462	57	22	variables	variable	NOUN
ejpam-462	57	23	.	.	PUNCT
ejpam-462	58	1	for	for	ADP
ejpam-462	58	2	example	example	NOUN
ejpam-462	58	3	,	,	PUNCT
ejpam-462	58	4	if	if	SCONJ
ejpam-462	58	5	a1_11	a1_11	PROPN
ejpam-462	58	6	6=	6=	PROPN
ejpam-462	58	7	0	0	NUM
ejpam-462	58	8	,	,	PUNCT
ejpam-462	58	9	a1_21	a1_21	PROPN
ejpam-462	58	10	6=	6=	ADP
ejpam-462	58	11	0	0	NUM
ejpam-462	58	12	.	.	PUNCT
ejpam-462	59	1	on	on	ADP
ejpam-462	59	2	the	the	DET
ejpam-462	59	3	other	other	ADJ
ejpam-462	59	4	hand	hand	NOUN
ejpam-462	59	5	,	,	PUNCT
ejpam-462	59	6	an	an	DET
ejpam-462	59	7	asymmetric	asymmetric	ADJ
ejpam-462	59	8	var	var	NOUN
ejpam-462	59	9	model	model	NOUN
ejpam-462	59	10	does	do	AUX
ejpam-462	59	11	not	not	PART
ejpam-462	59	12	share	share	VERB
ejpam-462	59	13	this	this	DET
ejpam-462	59	14	restriction	restriction	NOUN
ejpam-462	59	15	.	.	PUNCT
ejpam-462	60	1	in	in	ADP
ejpam-462	60	2	this	this	DET
ejpam-462	60	3	case	case	NOUN
ejpam-462	60	4	,	,	PUNCT
ejpam-462	60	5	we	we	PRON
ejpam-462	60	6	could	could	AUX
ejpam-462	60	7	possibly	possibly	ADV
ejpam-462	60	8	have	have	VERB
ejpam-462	60	9	yt	yt	NOUN
ejpam-462	60	10	=	=	PUNCT
ejpam-462	60	11	a10	a10	NOUN
ejpam-462	60	12	+	+	CCONJ
ejpam-462	60	13	a1_12zt−1	a1_12zt−1	NOUN
ejpam-462	60	14	+	+	CCONJ
ejpam-462	60	15	a2_11	a2_11	ADJ
ejpam-462	60	16	yt−2	yt−2	PROPN
ejpam-462	60	17	+	+	NUM
ejpam-462	60	18	e1	e1	PROPN
ejpam-462	60	19	t	t	NOUN
ejpam-462	60	20	zt	zt	PROPN
ejpam-462	60	21	=	=	SYM
ejpam-462	60	22	a20	a20	PROPN
ejpam-462	60	23	+	+	CCONJ
ejpam-462	60	24	a1_21	a1_21	PROPN
ejpam-462	60	25	yt−1	yt−1	PROPN
ejpam-462	60	26	+	+	PROPN
ejpam-462	60	27	a2_22zt−2	a2_22zt−2	PROPN
ejpam-462	60	28	+	+	NUM
ejpam-462	60	29	e2	e2	PROPN
ejpam-462	60	30	t	t	PROPN
ejpam-462	60	31	.	.	PUNCT
ejpam-462	61	1	(	(	PUNCT
ejpam-462	61	2	3	3	X
ejpam-462	61	3	)	)	PUNCT
ejpam-462	61	4	despite	despite	SCONJ
ejpam-462	61	5	the	the	DET
ejpam-462	61	6	value	value	NOUN
ejpam-462	61	7	of	of	ADP
ejpam-462	61	8	modeling	model	VERB
ejpam-462	61	9	a	a	DET
ejpam-462	61	10	set	set	NOUN
ejpam-462	61	11	of	of	ADP
ejpam-462	61	12	autoregressive	autoregressive	ADJ
ejpam-462	61	13	time	time	NOUN
ejpam-462	61	14	series	series	NOUN
ejpam-462	61	15	in	in	ADP
ejpam-462	61	16	parallel	parallel	NOUN
ejpam-462	61	17	,	,	PUNCT
ejpam-462	61	18	there	there	PRON
ejpam-462	61	19	is	be	VERB
ejpam-462	61	20	no	no	DET
ejpam-462	61	21	free	free	ADJ
ejpam-462	61	22	lunch	lunch	NOUN
ejpam-462	61	23	,	,	PUNCT
ejpam-462	61	24	and	and	CCONJ
ejpam-462	61	25	the	the	DET
ejpam-462	61	26	cost	cost	NOUN
ejpam-462	61	27	of	of	ADP
ejpam-462	61	28	var	var	NOUN
ejpam-462	61	29	modeling	modeling	NOUN
ejpam-462	61	30	is	be	AUX
ejpam-462	61	31	that	that	SCONJ
ejpam-462	61	32	,	,	PUNCT
ejpam-462	61	33	in	in	ADP
ejpam-462	61	34	the	the	DET
ejpam-462	61	35	absence	absence	NOUN
ejpam-462	61	36	of	of	ADP
ejpam-462	61	37	a	a	DET
ejpam-462	61	38	priori	priori	ADJ
ejpam-462	61	39	restrictions	restriction	NOUN
ejpam-462	61	40	,	,	PUNCT
ejpam-462	61	41	the	the	DET
ejpam-462	61	42	model	model	NOUN
ejpam-462	61	43	can	can	AUX
ejpam-462	61	44	easily	easily	ADV
ejpam-462	61	45	become	become	VERB
ejpam-462	61	46	overparameterized	overparameterized	ADJ
ejpam-462	61	47	.	.	PUNCT
ejpam-462	62	1	this	this	PRON
ejpam-462	62	2	leads	lead	VERB
ejpam-462	62	3	to	to	ADP
ejpam-462	62	4	highly	highly	ADV
ejpam-462	62	5	biased	biased	ADJ
ejpam-462	62	6	regression	regression	NOUN
ejpam-462	62	7	coefficients	coefficient	NOUN
ejpam-462	62	8	and	and	CCONJ
ejpam-462	62	9	large	large	ADJ
ejpam-462	62	10	out	out	ADJ
ejpam-462	62	11	-	-	PUNCT
ejpam-462	62	12	of	of	ADP
ejpam-462	62	13	-	-	PUNCT
ejpam-462	62	14	sample	sample	NOUN
ejpam-462	62	15	forecast	forecast	NOUN
ejpam-462	62	16	errors	error	NOUN
ejpam-462	62	17	.	.	PUNCT
ejpam-462	63	1	2.1	2.1	NUM
ejpam-462	63	2	.	.	PUNCT
ejpam-462	63	3	attempts	attempt	NOUN
ejpam-462	63	4	to	to	PART
ejpam-462	63	5	make	make	VERB
ejpam-462	63	6	var	var	NOUN
ejpam-462	63	7	modeling	model	VERB
ejpam-462	63	8	more	more	ADV
ejpam-462	63	9	tractable	tractable	ADJ
ejpam-462	63	10	over	over	ADP
ejpam-462	63	11	the	the	DET
ejpam-462	63	12	years	year	NOUN
ejpam-462	63	13	,	,	PUNCT
ejpam-462	63	14	several	several	ADJ
ejpam-462	63	15	suggestions	suggestion	NOUN
ejpam-462	63	16	have	have	AUX
ejpam-462	63	17	been	be	AUX
ejpam-462	63	18	put	put	VERB
ejpam-462	63	19	forth	forth	ADP
ejpam-462	63	20	in	in	ADP
ejpam-462	63	21	the	the	DET
ejpam-462	63	22	literature	literature	NOUN
ejpam-462	63	23	,	,	PUNCT
ejpam-462	63	24	in	in	ADP
ejpam-462	63	25	order	order	NOUN
ejpam-462	63	26	to	to	PART
ejpam-462	63	27	solve	solve	VERB
ejpam-462	63	28	these	these	DET
ejpam-462	63	29	issues	issue	NOUN
ejpam-462	63	30	.	.	PUNCT
ejpam-462	64	1	both	both	DET
ejpam-462	64	2	lutkepohl	lutkepohl	ADJ
ejpam-462	65	1	[	[	X
ejpam-462	65	2	14	14	NUM
ejpam-462	65	3	]	]	PUNCT
ejpam-462	65	4	and	and	CCONJ
ejpam-462	65	5	penm	penm	VERB
ejpam-462	65	6	and	and	CCONJ
ejpam-462	65	7	terrell	terrell	PRON
ejpam-462	65	8	[	[	X
ejpam-462	65	9	18	18	NUM
ejpam-462	65	10	]	]	PUNCT
ejpam-462	65	11	recommend	recommend	VERB
ejpam-462	65	12	subset	subset	NOUN
ejpam-462	65	13	var	var	NOUN
ejpam-462	65	14	models	model	NOUN
ejpam-462	65	15	which	which	PRON
ejpam-462	65	16	are	be	AUX
ejpam-462	65	17	basically	basically	ADV
ejpam-462	65	18	saturated	saturate	VERB
ejpam-462	65	19	var(q∗	var(q∗	NOUN
ejpam-462	65	20	)	)	PUNCT
ejpam-462	65	21	models	model	NOUN
ejpam-462	65	22	,	,	PUNCT
ejpam-462	65	23	where	where	SCONJ
ejpam-462	65	24	q∗	q∗	NOUN
ejpam-462	65	25	<	<	X
ejpam-462	65	26	order	order	NOUN
ejpam-462	65	27	of	of	ADP
ejpam-462	65	28	full	full	ADJ
ejpam-462	65	29	saturated	saturate	VERB
ejpam-462	65	30	model	model	NOUN
ejpam-462	65	31	.	.	PUNCT
ejpam-462	66	1	the	the	DET
ejpam-462	66	2	vector	vector	NOUN
ejpam-462	66	3	error	error	NOUN
ejpam-462	66	4	correction	correction	NOUN
ejpam-462	66	5	model	model	NOUN
ejpam-462	66	6	has	have	AUX
ejpam-462	66	7	also	also	ADV
ejpam-462	66	8	gained	gain	VERB
ejpam-462	66	9	popularity	popularity	NOUN
ejpam-462	66	10	,	,	PUNCT
ejpam-462	66	11	though	though	SCONJ
ejpam-462	66	12	it	it	PRON
ejpam-462	66	13	can	can	AUX
ejpam-462	66	14	only	only	ADV
ejpam-462	66	15	be	be	AUX
ejpam-462	66	16	applied	apply	VERB
ejpam-462	66	17	to	to	ADP
ejpam-462	66	18	time	time	NOUN
ejpam-462	66	19	series	series	NOUN
ejpam-462	66	20	that	that	PRON
ejpam-462	66	21	are	be	AUX
ejpam-462	66	22	cointegrated	cointegrate	VERB
ejpam-462	66	23	.	.	PUNCT
ejpam-462	67	1	using	use	VERB
ejpam-462	67	2	the	the	DET
ejpam-462	67	3	definition	definition	NOUN
ejpam-462	67	4	of	of	ADP
ejpam-462	67	5	the	the	DET
ejpam-462	67	6	well	well	ADV
ejpam-462	67	7	-	-	PUNCT
ejpam-462	67	8	known	know	VERB
ejpam-462	67	9	[	[	NOUN
ejpam-462	67	10	8	8	NUM
ejpam-462	67	11	]	]	X
ejpam-462	67	12	paper	paper	NOUN
ejpam-462	67	13	by	by	ADP
ejpam-462	67	14	engle	engle	PROPN
ejpam-462	67	15	and	and	CCONJ
ejpam-462	67	16	granger	granger	PROPN
ejpam-462	67	17	,	,	PUNCT
ejpam-462	67	18	the	the	DET
ejpam-462	67	19	components	component	NOUN
ejpam-462	67	20	of	of	ADP
ejpam-462	67	21	a	a	DET
ejpam-462	67	22	vector	vector	NOUN
ejpam-462	67	23	x	x	PUNCT
ejpam-462	67	24	of	of	ADP
ejpam-462	67	25	t	t	PROPN
ejpam-462	67	26	time	time	NOUN
ejpam-462	67	27	series	series	PROPN
ejpam-462	67	28	are	be	AUX
ejpam-462	67	29	said	say	VERB
ejpam-462	67	30	to	to	PART
ejpam-462	67	31	be	be	AUX
ejpam-462	67	32	cointegrated	cointegrate	VERB
ejpam-462	67	33	of	of	ADP
ejpam-462	67	34	order	order	NOUN
ejpam-462	67	35	d	d	NOUN
ejpam-462	67	36	,	,	PUNCT
ejpam-462	67	37	b	b	PROPN
ejpam-462	67	38	(	(	PUNCT
ejpam-462	67	39	x	x	X
ejpam-462	67	40	∼	∼	NOUN
ejpam-462	67	41	c	c	NOUN
ejpam-462	68	1	i	i	PRON
ejpam-462	68	2	(	(	PUNCT
ejpam-462	68	3	d	d	PROPN
ejpam-462	68	4	,	,	PUNCT
ejpam-462	68	5	b	b	NOUN
ejpam-462	68	6	)	)	PUNCT
ejpam-462	68	7	)	)	PUNCT
ejpam-462	68	8	if	if	SCONJ
ejpam-462	68	9	the	the	DET
ejpam-462	68	10	following	follow	VERB
ejpam-462	68	11	restrictions	restriction	NOUN
ejpam-462	68	12	apply	apply	VERB
ejpam-462	68	13	.	.	PUNCT
ejpam-462	69	1	1	1	X
ejpam-462	69	2	.	.	X
ejpam-462	69	3	each	each	DET
ejpam-462	69	4	series	series	NOUN
ejpam-462	69	5	exhibits	exhibit	VERB
ejpam-462	69	6	the	the	DET
ejpam-462	69	7	same	same	ADJ
ejpam-462	69	8	order	order	NOUN
ejpam-462	69	9	of	of	ADP
ejpam-462	69	10	integration	integration	NOUN
ejpam-462	69	11	:	:	PUNCT
ejpam-462	69	12	x	x	X
ejpam-462	69	13	t	t	NOUN
ejpam-462	69	14	∼	∼	NOUN
ejpam-462	69	15	i	i	PRON
ejpam-462	69	16	(	(	PUNCT
ejpam-462	69	17	d	d	PROPN
ejpam-462	69	18	)	)	PUNCT
ejpam-462	69	19	,	,	PUNCT
ejpam-462	69	20	t	t	NOUN
ejpam-462	69	21	=	=	SYM
ejpam-462	69	22	1	1	NUM
ejpam-462	69	23	.	.	PUNCT
ejpam-462	69	24	.	.	PUNCT
ejpam-462	69	25	.	.	PUNCT
ejpam-462	70	1	t	t	NOUN
ejpam-462	70	2	.	.	PUNCT
ejpam-462	71	1	2	2	X
ejpam-462	71	2	.	.	X
ejpam-462	71	3	there	there	PRON
ejpam-462	71	4	exists	exist	VERB
ejpam-462	71	5	a	a	DET
ejpam-462	71	6	vector	vector	NOUN
ejpam-462	71	7	β	β	X
ejpam-462	71	8	(	(	PUNCT
ejpam-462	71	9	called	call	VERB
ejpam-462	71	10	the	the	DET
ejpam-462	71	11	cointegrating	cointegrate	VERB
ejpam-462	71	12	vector	vector	NOUN
ejpam-462	71	13	)	)	PUNCT
ejpam-462	71	14	such	such	ADJ
ejpam-462	71	15	that	that	SCONJ
ejpam-462	71	16	the	the	DET
ejpam-462	71	17	linear	linear	ADJ
ejpam-462	71	18	combination	combination	NOUN
ejpam-462	71	19	xβ	xβ	NOUN
ejpam-462	71	20	is	be	AUX
ejpam-462	71	21	integrated	integrate	VERB
ejpam-462	71	22	at	at	ADP
ejpam-462	71	23	a	a	DET
ejpam-462	71	24	lower	low	ADJ
ejpam-462	71	25	order	order	NOUN
ejpam-462	71	26	:	:	PUNCT
ejpam-462	71	27	xβ	xβ	ADV
ejpam-462	71	28	∼	∼	VERB
ejpam-462	71	29	i	i	PRON
ejpam-462	71	30	(	(	PUNCT
ejpam-462	71	31	d	d	PROPN
ejpam-462	71	32	−	−	PROPN
ejpam-462	71	33	b	b	PROPN
ejpam-462	71	34	)	)	PUNCT
ejpam-462	71	35	,	,	PUNCT
ejpam-462	71	36	b	b	X
ejpam-462	71	37	>	>	X
ejpam-462	71	38	0	0	X
ejpam-462	71	39	.	.	PUNCT
ejpam-462	72	1	this	this	PRON
ejpam-462	72	2	is	be	AUX
ejpam-462	72	3	a	a	DET
ejpam-462	72	4	special	special	ADJ
ejpam-462	72	5	situation	situation	NOUN
ejpam-462	72	6	;	;	PUNCT
ejpam-462	72	7	it	it	PRON
ejpam-462	72	8	is	be	AUX
ejpam-462	72	9	generally	generally	ADV
ejpam-462	72	10	the	the	DET
ejpam-462	72	11	case	case	NOUN
ejpam-462	72	12	that	that	SCONJ
ejpam-462	72	13	a	a	DET
ejpam-462	72	14	linear	linear	ADJ
ejpam-462	72	15	combination	combination	NOUN
ejpam-462	72	16	of	of	ADP
ejpam-462	72	17	i	i	PRON
ejpam-462	72	18	(	(	PUNCT
ejpam-462	72	19	d	d	X
ejpam-462	72	20	)	)	PUNCT
ejpam-462	72	21	variables	variable	NOUN
ejpam-462	72	22	remains	remain	VERB
ejpam-462	72	23	i	i	PRON
ejpam-462	72	24	(	(	PUNCT
ejpam-462	72	25	d	d	NOUN
ejpam-462	72	26	)	)	PUNCT
ejpam-462	72	27	,	,	PUNCT
ejpam-462	72	28	and	and	CCONJ
ejpam-462	72	29	they	they	PRON
ejpam-462	72	30	are	be	AUX
ejpam-462	72	31	not	not	PART
ejpam-462	72	32	cointegrated	cointegrate	VERB
ejpam-462	72	33	.	.	PUNCT
ejpam-462	73	1	a.	a.	NOUN
ejpam-462	73	2	howe	howe	PROPN
ejpam-462	73	3	and	and	CCONJ
ejpam-462	73	4	h.	h.	PROPN
ejpam-462	73	5	bozdogan	bozdogan	PROPN
ejpam-462	73	6	/	/	SYM
ejpam-462	73	7	eur	eur	PROPN
ejpam-462	73	8	.	.	PUNCT
ejpam-462	74	1	j.	j.	PROPN
ejpam-462	74	2	pure	pure	PROPN
ejpam-462	74	3	appl	appl	PROPN
ejpam-462	74	4	.	.	PROPN
ejpam-462	74	5	math	math	PROPN
ejpam-462	74	6	,	,	PUNCT
ejpam-462	74	7	3	3	NUM
ejpam-462	74	8	(	(	PUNCT
ejpam-462	74	9	2010	2010	NUM
ejpam-462	74	10	)	)	PUNCT
ejpam-462	74	11	,	,	PUNCT
ejpam-462	74	12	382	382	NUM
ejpam-462	74	13	-	-	SYM
ejpam-462	74	14	405	405	NUM
ejpam-462	74	15	385	385	NUM
ejpam-462	74	16	cointegrated	cointegrate	VERB
ejpam-462	74	17	variables	variable	NOUN
ejpam-462	74	18	share	share	VERB
ejpam-462	74	19	a	a	DET
ejpam-462	74	20	common	common	ADJ
ejpam-462	74	21	stochastic	stochastic	ADJ
ejpam-462	74	22	trend	trend	NOUN
ejpam-462	74	23	;	;	PUNCT
ejpam-462	74	24	for	for	ADP
ejpam-462	74	25	a	a	DET
ejpam-462	74	26	set	set	NOUN
ejpam-462	74	27	of	of	ADP
ejpam-462	74	28	cointegrated	cointegrated	ADJ
ejpam-462	74	29	variables	variable	NOUN
ejpam-462	74	30	,	,	PUNCT
ejpam-462	74	31	a	a	DET
ejpam-462	74	32	valid	valid	ADJ
ejpam-462	74	33	error	error	NOUN
ejpam-462	74	34	correction	correction	NOUN
ejpam-462	74	35	can	can	AUX
ejpam-462	74	36	be	be	AUX
ejpam-462	74	37	written	write	VERB
ejpam-462	74	38	which	which	PRON
ejpam-462	74	39	will	will	AUX
ejpam-462	74	40	react	react	VERB
ejpam-462	74	41	to	to	PART
ejpam-462	74	42	correct	correct	VERB
ejpam-462	74	43	short	short	ADJ
ejpam-462	74	44	term	term	NOUN
ejpam-462	74	45	departures	departure	NOUN
ejpam-462	74	46	from	from	ADP
ejpam-462	74	47	the	the	DET
ejpam-462	74	48	common	common	ADJ
ejpam-462	74	49	trend	trend	NOUN
ejpam-462	74	50	.	.	PUNCT
ejpam-462	75	1	additionally	additionally	ADV
ejpam-462	75	2	,	,	PUNCT
ejpam-462	75	3	bayesian	bayesian	NOUN
ejpam-462	75	4	vector	vector	NOUN
ejpam-462	75	5	autoregression	autoregression	NOUN
ejpam-462	75	6	has	have	AUX
ejpam-462	75	7	been	be	AUX
ejpam-462	75	8	developed	develop	VERB
ejpam-462	75	9	by	by	ADP
ejpam-462	75	10	several	several	ADJ
ejpam-462	75	11	researchers	researcher	NOUN
ejpam-462	75	12	,	,	PUNCT
ejpam-462	75	13	both	both	PRON
ejpam-462	75	14	for	for	ADP
ejpam-462	75	15	cointegrated	cointegrate	VERB
ejpam-462	75	16	[	[	X
ejpam-462	75	17	2	2	NUM
ejpam-462	75	18	,	,	PUNCT
ejpam-462	75	19	also	also	ADV
ejpam-462	75	20	see	see	VERB
ejpam-462	75	21	the	the	DET
ejpam-462	75	22	unpublished	unpublished	ADJ
ejpam-462	75	23	manuscript	manuscript	NOUN
ejpam-462	75	24	of	of	ADP
ejpam-462	75	25	kleibergen	kleibergen	PROPN
ejpam-462	75	26	and	and	CCONJ
ejpam-462	75	27	van	van	PROPN
ejpam-462	75	28	dijk	dijk	PROPN
ejpam-462	75	29	]	]	PUNCT
ejpam-462	75	30	and	and	CCONJ
ejpam-462	75	31	non	non	ADJ
ejpam-462	75	32	-	-	ADJ
ejpam-462	75	33	cointegrated	cointegrated	ADJ
ejpam-462	75	34	[	[	PUNCT
ejpam-462	75	35	13	13	NUM
ejpam-462	75	36	]	]	PUNCT
ejpam-462	75	37	data	datum	NOUN
ejpam-462	75	38	.	.	PUNCT
ejpam-462	76	1	many	many	ADJ
ejpam-462	76	2	of	of	ADP
ejpam-462	76	3	these	these	DET
ejpam-462	76	4	attempts	attempt	NOUN
ejpam-462	76	5	to	to	PART
ejpam-462	76	6	deal	deal	VERB
ejpam-462	76	7	with	with	ADP
ejpam-462	76	8	the	the	DET
ejpam-462	76	9	curse	curse	NOUN
ejpam-462	76	10	of	of	ADP
ejpam-462	76	11	dimensionality	dimensionality	NOUN
ejpam-462	76	12	come	come	VERB
ejpam-462	76	13	with	with	ADP
ejpam-462	76	14	their	their	PRON
ejpam-462	76	15	own	own	ADJ
ejpam-462	76	16	shortcomings	shortcoming	NOUN
ejpam-462	76	17	.	.	PUNCT
ejpam-462	77	1	we	we	PRON
ejpam-462	77	2	can	can	AUX
ejpam-462	77	3	use	use	VERB
ejpam-462	77	4	likelihood	likelihood	NOUN
ejpam-462	77	5	ratio	ratio	NOUN
ejpam-462	77	6	hypothesis	hypothesis	NOUN
ejpam-462	77	7	testing	testing	NOUN
ejpam-462	77	8	to	to	PART
ejpam-462	77	9	determine	determine	VERB
ejpam-462	77	10	the	the	DET
ejpam-462	77	11	maximum	maximum	ADJ
ejpam-462	77	12	lags	lag	NOUN
ejpam-462	77	13	to	to	ADP
ejpam-462	77	14	model	model	NOUN
ejpam-462	77	15	,	,	PUNCT
ejpam-462	77	16	but	but	CCONJ
ejpam-462	77	17	the	the	DET
ejpam-462	77	18	test	test	NOUN
ejpam-462	77	19	statistic	statistic	NOUN
ejpam-462	77	20	often	often	ADV
ejpam-462	77	21	does	do	AUX
ejpam-462	77	22	not	not	PART
ejpam-462	77	23	follow	follow	VERB
ejpam-462	77	24	the	the	DET
ejpam-462	77	25	asymptotic	asymptotic	ADJ
ejpam-462	77	26	chi	chi	ADJ
ejpam-462	77	27	-	-	PUNCT
ejpam-462	77	28	squared	square	VERB
ejpam-462	77	29	distribution	distribution	NOUN
ejpam-462	77	30	under	under	ADP
ejpam-462	77	31	the	the	DET
ejpam-462	77	32	null	null	ADJ
ejpam-462	77	33	hypothesis	hypothesis	NOUN
ejpam-462	77	34	.	.	PUNCT
ejpam-462	78	1	this	this	DET
ejpam-462	78	2	approach	approach	NOUN
ejpam-462	78	3	also	also	ADV
ejpam-462	78	4	restricts	restrict	VERB
ejpam-462	78	5	the	the	DET
ejpam-462	78	6	researcher	researcher	NOUN
ejpam-462	78	7	to	to	ADP
ejpam-462	78	8	considering	consider	VERB
ejpam-462	78	9	sequential	sequential	ADJ
ejpam-462	78	10	lags	lag	NOUN
ejpam-462	78	11	(	(	PUNCT
ejpam-462	78	12	∆1,∆2	∆1,∆2	ADJ
ejpam-462	78	13	,	,	PUNCT
ejpam-462	78	14	.	.	PUNCT
ejpam-462	78	15	.	.	PUNCT
ejpam-462	78	16	.	.	PUNCT
ejpam-462	79	1	,	,	PUNCT
ejpam-462	79	2	∆q∗	∆q∗	NOUN
ejpam-462	79	3	)	)	PUNCT
ejpam-462	79	4	,	,	PUNCT
ejpam-462	79	5	where	where	SCONJ
ejpam-462	79	6	a	a	DET
ejpam-462	79	7	better	well	ADJ
ejpam-462	79	8	model	model	NOUN
ejpam-462	79	9	may	may	AUX
ejpam-462	79	10	skip	skip	VERB
ejpam-462	79	11	certain	certain	ADJ
ejpam-462	79	12	lags	lag	NOUN
ejpam-462	79	13	.	.	PUNCT
ejpam-462	80	1	granger	granger	PROPN
ejpam-462	80	2	causality	causality	PROPN
ejpam-462	80	3	tests	test	VERB
ejpam-462	80	4	[	[	X
ejpam-462	80	5	9	9	NUM
ejpam-462	80	6	,	,	PUNCT
ejpam-462	80	7	23	23	NUM
ejpam-462	80	8	]	]	PUNCT
ejpam-462	80	9	could	could	AUX
ejpam-462	80	10	also	also	ADV
ejpam-462	80	11	be	be	AUX
ejpam-462	80	12	used	use	VERB
ejpam-462	80	13	to	to	PART
ejpam-462	80	14	reduce	reduce	VERB
ejpam-462	80	15	the	the	DET
ejpam-462	80	16	dimensionality	dimensionality	NOUN
ejpam-462	80	17	of	of	ADP
ejpam-462	80	18	the	the	DET
ejpam-462	80	19	var	var	NOUN
ejpam-462	80	20	model	model	NOUN
ejpam-462	80	21	,	,	PUNCT
ejpam-462	80	22	but	but	CCONJ
ejpam-462	80	23	this	this	DET
ejpam-462	80	24	approach	approach	NOUN
ejpam-462	80	25	fails	fail	VERB
ejpam-462	80	26	to	to	PART
ejpam-462	80	27	exploit	exploit	VERB
ejpam-462	80	28	potential	potential	ADJ
ejpam-462	80	29	asymmetric	asymmetric	ADJ
ejpam-462	80	30	relationships	relationship	NOUN
ejpam-462	80	31	.	.	PUNCT
ejpam-462	81	1	[	[	X
ejpam-462	81	2	18	18	NUM
ejpam-462	81	3	]	]	PUNCT
ejpam-462	81	4	suggest	suggest	AUX
ejpam-462	81	5	restricting	restrict	VERB
ejpam-462	81	6	the	the	DET
ejpam-462	81	7	φ	φ	PROPN
ejpam-462	81	8	matrices	matrix	NOUN
ejpam-462	81	9	to	to	PART
ejpam-462	81	10	be	be	AUX
ejpam-462	81	11	complete	complete	ADJ
ejpam-462	81	12	a	a	DET
ejpam-462	81	13	given	give	VERB
ejpam-462	81	14	lag	lag	NOUN
ejpam-462	81	15	is	be	AUX
ejpam-462	81	16	either	either	CCONJ
ejpam-462	81	17	used	use	VERB
ejpam-462	81	18	for	for	ADP
ejpam-462	81	19	all	all	DET
ejpam-462	81	20	series	series	NOUN
ejpam-462	81	21	,	,	PUNCT
ejpam-462	81	22	or	or	CCONJ
ejpam-462	81	23	it	it	PRON
ejpam-462	81	24	’s	’s	AUX
ejpam-462	81	25	not	not	PART
ejpam-462	81	26	used	use	VERB
ejpam-462	81	27	at	at	ADV
ejpam-462	81	28	all	all	ADV
ejpam-462	81	29	.	.	PUNCT
ejpam-462	82	1	this	this	DET
ejpam-462	82	2	method	method	NOUN
ejpam-462	82	3	risks	risk	NOUN
ejpam-462	82	4	including	include	VERB
ejpam-462	82	5	useless	useless	ADJ
ejpam-462	82	6	predictors	predictor	NOUN
ejpam-462	82	7	at	at	ADP
ejpam-462	82	8	the	the	DET
ejpam-462	82	9	expense	expense	NOUN
ejpam-462	82	10	of	of	ADP
ejpam-462	82	11	useful	useful	ADJ
ejpam-462	82	12	ones	one	NOUN
ejpam-462	82	13	;	;	PUNCT
ejpam-462	82	14	leading	lead	VERB
ejpam-462	82	15	to	to	ADP
ejpam-462	82	16	larger	large	ADJ
ejpam-462	82	17	forecast	forecast	NOUN
ejpam-462	82	18	errors	error	NOUN
ejpam-462	82	19	.	.	PUNCT
ejpam-462	83	1	2.2	2.2	NUM
ejpam-462	83	2	.	.	PUNCT
ejpam-462	83	3	subset	subset	VERB
ejpam-462	83	4	var	var	NOUN
ejpam-462	83	5	models	model	NOUN
ejpam-462	83	6	with	with	ADP
ejpam-462	83	7	robust	robust	ADJ
ejpam-462	83	8	covariance	covariance	NOUN
ejpam-462	83	9	estimation	estimation	NOUN
ejpam-462	83	10	the	the	DET
ejpam-462	83	11	typical	typical	ADJ
ejpam-462	83	12	gaussian	gaussian	ADJ
ejpam-462	83	13	var	var	NOUN
ejpam-462	83	14	model	model	NOUN
ejpam-462	83	15	,	,	PUNCT
ejpam-462	83	16	in	in	ADP
ejpam-462	83	17	standard	standard	ADJ
ejpam-462	83	18	form	form	NOUN
ejpam-462	83	19	,	,	PUNCT
ejpam-462	83	20	can	can	AUX
ejpam-462	83	21	be	be	AUX
ejpam-462	83	22	written	write	VERB
ejpam-462	83	23	as	as	ADP
ejpam-462	83	24	a	a	DET
ejpam-462	83	25	multivariate	multivariate	NOUN
ejpam-462	83	26	regression	regression	NOUN
ejpam-462	83	27	problem	problem	NOUN
ejpam-462	83	28	:	:	PUNCT
ejpam-462	83	29	y	y	PROPN
ejpam-462	83	30	=	=	PUNCT
ejpam-462	83	31	x	x	PUNCT
ejpam-462	83	32	b+e	b+e	NUM
ejpam-462	83	33	,	,	PUNCT
ejpam-462	83	34	where	where	SCONJ
ejpam-462	83	35	y	y	PROPN
ejpam-462	83	36	∈	∈	PROPN
ejpam-462	83	37	rn×p	rn×p	PROPN
ejpam-462	83	38	is	be	AUX
ejpam-462	83	39	the	the	DET
ejpam-462	83	40	matrix	matrix	NOUN
ejpam-462	83	41	of	of	ADP
ejpam-462	83	42	p	p	NOUN
ejpam-462	83	43	responses	response	NOUN
ejpam-462	83	44	across	across	ADP
ejpam-462	83	45	n	n	DET
ejpam-462	83	46	observations	observation	NOUN
ejpam-462	83	47	.	.	PUNCT
ejpam-462	84	1	assuming	assume	VERB
ejpam-462	84	2	k	k	PROPN
ejpam-462	84	3	lags	lag	NOUN
ejpam-462	84	4	of	of	ADP
ejpam-462	84	5	y	y	PROPN
ejpam-462	84	6	,	,	PUNCT
ejpam-462	84	7	x	x	PUNCT
ejpam-462	84	8	∈	∈	NOUN
ejpam-462	84	9	rn×(pk+1	rn×(pk+1	NOUN
ejpam-462	84	10	)	)	PUNCT
ejpam-462	84	11	all	all	DET
ejpam-462	84	12	the	the	DET
ejpam-462	84	13	appropriate	appropriate	ADJ
ejpam-462	84	14	lags	lag	NOUN
ejpam-462	84	15	of	of	ADP
ejpam-462	84	16	each	each	DET
ejpam-462	84	17	response	response	NOUN
ejpam-462	84	18	,	,	PUNCT
ejpam-462	84	19	plus	plus	CCONJ
ejpam-462	84	20	a	a	DET
ejpam-462	84	21	constant	constant	ADJ
ejpam-462	84	22	term	term	NOUN
ejpam-462	84	23	.	.	PUNCT
ejpam-462	85	1	the	the	DET
ejpam-462	85	2	error	error	NOUN
ejpam-462	85	3	terms	term	NOUN
ejpam-462	85	4	are	be	AUX
ejpam-462	85	5	assumed	assume	VERB
ejpam-462	85	6	to	to	PART
ejpam-462	85	7	be	be	AUX
ejpam-462	85	8	drawn	draw	VERB
ejpam-462	85	9	from	from	ADP
ejpam-462	85	10	a	a	DET
ejpam-462	85	11	multivariate	multivariate	NOUN
ejpam-462	85	12	gaussian	gaussian	ADJ
ejpam-462	85	13	white	white	ADJ
ejpam-462	85	14	noise	noise	NOUN
ejpam-462	85	15	process	process	NOUN
ejpam-462	85	16	,	,	PUNCT
ejpam-462	85	17	with	with	ADP
ejpam-462	85	18	mean	mean	PROPN
ejpam-462	85	19	vector	vector	NOUN
ejpam-462	85	20	µ	µ	X
ejpam-462	85	21	=	=	SYM
ejpam-462	85	22	0	0	NUM
ejpam-462	85	23	and	and	CCONJ
ejpam-462	85	24	constant	constant	ADJ
ejpam-462	85	25	covariance	covariance	NOUN
ejpam-462	85	26	matrix	matrix	NOUN
ejpam-462	85	27	σ	σ	PROPN
ejpam-462	85	28	.	.	PUNCT
ejpam-462	86	1	finally	finally	ADV
ejpam-462	86	2	,	,	PUNCT
ejpam-462	86	3	b	b	X
ejpam-462	86	4	∈	∈	PROPN
ejpam-462	86	5	r(pk+1)×p	r(pk+1)×p	NOUN
ejpam-462	86	6	is	be	AUX
ejpam-462	86	7	the	the	DET
ejpam-462	86	8	matrix	matrix	NOUN
ejpam-462	86	9	of	of	ADP
ejpam-462	86	10	model	model	NOUN
ejpam-462	86	11	coefficients	coefficient	NOUN
ejpam-462	86	12	.	.	PUNCT
ejpam-462	87	1	of	of	ADP
ejpam-462	87	2	course	course	NOUN
ejpam-462	87	3	,	,	PUNCT
ejpam-462	87	4	there	there	PRON
ejpam-462	87	5	is	be	VERB
ejpam-462	87	6	potentially	potentially	ADV
ejpam-462	87	7	a	a	DET
ejpam-462	87	8	coefficient	coefficient	NOUN
ejpam-462	87	9	on	on	ADP
ejpam-462	87	10	each	each	DET
ejpam-462	87	11	lag	lag	NOUN
ejpam-462	87	12	of	of	ADP
ejpam-462	87	13	each	each	DET
ejpam-462	87	14	response	response	NOUN
ejpam-462	87	15	(	(	PUNCT
ejpam-462	87	16	plus	plus	CCONJ
ejpam-462	87	17	the	the	DET
ejpam-462	87	18	constant	constant	ADJ
ejpam-462	87	19	)	)	PUNCT
ejpam-462	87	20	,	,	PUNCT
ejpam-462	87	21	for	for	ADP
ejpam-462	87	22	all	all	DET
ejpam-462	87	23	responses	response	NOUN
ejpam-462	87	24	.	.	PUNCT
ejpam-462	88	1	in	in	ADP
ejpam-462	88	2	order	order	NOUN
ejpam-462	88	3	to	to	PART
ejpam-462	88	4	perform	perform	VERB
ejpam-462	88	5	subsetting	subsette	VERB
ejpam-462	88	6	with	with	ADP
ejpam-462	88	7	asymmetric	asymmetric	ADJ
ejpam-462	88	8	restrictions	restriction	NOUN
ejpam-462	88	9	in	in	ADP
ejpam-462	88	10	this	this	DET
ejpam-462	88	11	context	context	NOUN
ejpam-462	88	12	,	,	PUNCT
ejpam-462	88	13	we	we	PRON
ejpam-462	88	14	need	need	VERB
ejpam-462	88	15	to	to	PART
ejpam-462	88	16	rearrange	rearrange	VERB
ejpam-462	88	17	the	the	DET
ejpam-462	88	18	data	datum	NOUN
ejpam-462	88	19	slightly	slightly	ADV
ejpam-462	88	20	.	.	PUNCT
ejpam-462	89	1	following	follow	VERB
ejpam-462	89	2	[	[	X
ejpam-462	89	3	3	3	NUM
ejpam-462	89	4	]	]	PUNCT
ejpam-462	89	5	,	,	PUNCT
ejpam-462	89	6	the	the	DET
ejpam-462	89	7	first	first	ADJ
ejpam-462	89	8	step	step	NOUN
ejpam-462	89	9	is	be	AUX
ejpam-462	89	10	to	to	PART
ejpam-462	89	11	transform	transform	VERB
ejpam-462	89	12	y	y	PROPN
ejpam-462	89	13	from	from	ADP
ejpam-462	89	14	an	an	DET
ejpam-462	89	15	�	�	PROPN
ejpam-462	89	16	n×	n×	PROPN
ejpam-462	89	17	p	p	PROPN
ejpam-462	89	18	�	�	PROPN
ejpam-462	89	19	matrix	matrix	NOUN
ejpam-462	89	20	into	into	ADP
ejpam-462	89	21	an	an	DET
ejpam-462	89	22	�	�	PROPN
ejpam-462	89	23	np×	np×	ADJ
ejpam-462	89	24	1	1	NUM
ejpam-462	89	25	�	�	PROPN
ejpam-462	89	26	yvec	yvec	PROPN
ejpam-462	89	27	vector	vector	NOUN
ejpam-462	89	28	using	use	VERB
ejpam-462	89	29	the	the	DET
ejpam-462	89	30	vec	vec	PROPN
ejpam-462	89	31	(	(	PUNCT
ejpam-462	89	32	·	·	PUNCT
ejpam-462	89	33	)	)	PUNCT
ejpam-462	89	34	operator	operator	NOUN
ejpam-462	89	35	,	,	PUNCT
ejpam-462	89	36	which	which	PRON
ejpam-462	89	37	vertically	vertically	ADV
ejpam-462	89	38	catenates	catenate	VERB
ejpam-462	89	39	columns	column	NOUN
ejpam-462	89	40	of	of	ADP
ejpam-462	89	41	a	a	DET
ejpam-462	89	42	matrix	matrix	NOUN
ejpam-462	89	43	.	.	PUNCT
ejpam-462	90	1	secondly	secondly	ADV
ejpam-462	90	2	,	,	PUNCT
ejpam-462	90	3	we	we	PRON
ejpam-462	90	4	use	use	VERB
ejpam-462	90	5	the	the	DET
ejpam-462	90	6	kronecker	kronecker	NOUN
ejpam-462	90	7	product	product	NOUN
ejpam-462	90	8	,	,	PUNCT
ejpam-462	90	9	which	which	PRON
ejpam-462	90	10	multiplies	multiply	VERB
ejpam-462	90	11	all	all	DET
ejpam-462	90	12	elements	element	NOUN
ejpam-462	90	13	of	of	ADP
ejpam-462	90	14	two	two	NUM
ejpam-462	90	15	matrices	matrix	NOUN
ejpam-462	90	16	,	,	PUNCT
ejpam-462	90	17	to	to	PART
ejpam-462	90	18	create	create	VERB
ejpam-462	90	19	xsup	xsup	NOUN
ejpam-462	90	20	=	=	SYM
ejpam-462	90	21	ip	ip	NOUN
ejpam-462	90	22	⊗	⊗	PROPN
ejpam-462	90	23	x	x	X
ejpam-462	90	24	;	;	PUNCT
ejpam-462	90	25	xsup	xsup	NOUN
ejpam-462	90	26	is	be	AUX
ejpam-462	90	27	an	an	DET
ejpam-462	90	28	�	�	PROPN
ejpam-462	90	29	np×	np×	PROPN
ejpam-462	90	30	p	p	PROPN
ejpam-462	90	31	�	�	PROPN
ejpam-462	90	32	pk+	pk+	PROPN
ejpam-462	90	33	1	1	NUM
ejpam-462	90	34	�	�	PROPN
ejpam-462	90	35	�	�	PROPN
ejpam-462	90	36	matrix	matrix	NOUN
ejpam-462	90	37	.	.	PUNCT
ejpam-462	91	1	with	with	ADP
ejpam-462	91	2	these	these	DET
ejpam-462	91	3	transformations	transformation	NOUN
ejpam-462	91	4	,	,	PUNCT
ejpam-462	91	5	both	both	CCONJ
ejpam-462	91	6	the	the	DET
ejpam-462	91	7	coefficient	coefficient	NOUN
ejpam-462	91	8	and	and	CCONJ
ejpam-462	91	9	error	error	NOUN
ejpam-462	91	10	matrices	matrix	NOUN
ejpam-462	91	11	become	become	VERB
ejpam-462	91	12	vectors	vector	NOUN
ejpam-462	91	13	.	.	PUNCT
ejpam-462	92	1	the	the	DET
ejpam-462	92	2	relationship	relationship	NOUN
ejpam-462	92	3	then	then	ADV
ejpam-462	92	4	becomes	become	VERB
ejpam-462	92	5	yvec︸︷︷︸	yvec︸︷︷︸	ADV
ejpam-462	92	6	np×1	np×1	PROPN
ejpam-462	92	7	=	=	SYM
ejpam-462	92	8	xsup︸︷︷︸	xsup︸︷︷︸	NOUN
ejpam-462	92	9	np×p(pk+1	np×p(pk+1	NOUN
ejpam-462	92	10	)	)	PUNCT
ejpam-462	92	11	β︸︷︷︸	β︸︷︷︸	NOUN
ejpam-462	93	1	p(pk+1)×1	p(pk+1)×1	NOUN
ejpam-462	94	1	+	+	CCONJ
ejpam-462	94	2	ǫ︸︷︷︸	ǫ︸︷︷︸	ADV
ejpam-462	94	3	np×1	np×1	INTJ
ejpam-462	94	4	.	.	PUNCT
ejpam-462	95	1	(	(	PUNCT
ejpam-462	95	2	4	4	X
ejpam-462	95	3	)	)	PUNCT
ejpam-462	95	4	at	at	ADP
ejpam-462	95	5	this	this	DET
ejpam-462	95	6	point	point	NOUN
ejpam-462	95	7	,	,	PUNCT
ejpam-462	95	8	subset	subset	ADJ
ejpam-462	95	9	selection	selection	NOUN
ejpam-462	95	10	becomes	become	VERB
ejpam-462	95	11	simple	simple	ADJ
ejpam-462	95	12	each	each	DET
ejpam-462	95	13	column	column	NOUN
ejpam-462	95	14	of	of	ADP
ejpam-462	95	15	the	the	DET
ejpam-462	95	16	sparse	sparse	ADJ
ejpam-462	95	17	xsup	xsup	NOUN
ejpam-462	95	18	matrix	matrix	NOUN
ejpam-462	95	19	represents	represent	VERB
ejpam-462	95	20	a	a	DET
ejpam-462	95	21	specific	specific	ADJ
ejpam-462	95	22	predictor	predictor	NOUN
ejpam-462	95	23	used	use	VERB
ejpam-462	95	24	for	for	ADP
ejpam-462	95	25	a	a	DET
ejpam-462	95	26	specific	specific	ADJ
ejpam-462	95	27	response	response	NOUN
ejpam-462	95	28	.	.	PUNCT
ejpam-462	96	1	for	for	ADP
ejpam-462	96	2	example	example	NOUN
ejpam-462	96	3	,	,	PUNCT
ejpam-462	96	4	if	if	SCONJ
ejpam-462	96	5	p	p	NOUN
ejpam-462	96	6	=	=	SYM
ejpam-462	96	7	2	2	NUM
ejpam-462	96	8	and	and	CCONJ
ejpam-462	96	9	k	k	NOUN
ejpam-462	96	10	=	=	SYM
ejpam-462	96	11	3	3	NUM
ejpam-462	96	12	,	,	PUNCT
ejpam-462	96	13	the	the	DET
ejpam-462	96	14	1st	1st	PROPN
ejpam-462	96	15	&	&	CCONJ
ejpam-462	96	16	7th	7th	ADJ
ejpam-462	96	17	columns	column	NOUN
ejpam-462	96	18	are	be	AUX
ejpam-462	96	19	the	the	DET
ejpam-462	96	20	constant	constant	ADJ
ejpam-462	96	21	applied	apply	VERB
ejpam-462	96	22	to	to	ADP
ejpam-462	96	23	the	the	DET
ejpam-462	96	24	1st	1st	ADJ
ejpam-462	96	25	&	&	CCONJ
ejpam-462	96	26	2nd	2nd	ADJ
ejpam-462	96	27	predictors	predictor	NOUN
ejpam-462	96	28	,	,	PUNCT
ejpam-462	96	29	respectively	respectively	ADV
ejpam-462	96	30	.	.	PUNCT
ejpam-462	97	1	a	a	DET
ejpam-462	97	2	binary	binary	ADJ
ejpam-462	97	3	string	string	NOUN
ejpam-462	97	4	of	of	ADP
ejpam-462	97	5	length	length	NOUN
ejpam-462	97	6	p	p	PROPN
ejpam-462	97	7	�	�	PROPN
ejpam-462	97	8	pk+	pk+	NOUN
ejpam-462	97	9	1	1	NUM
ejpam-462	97	10	�	�	PROPN
ejpam-462	97	11	,	,	PUNCT
ejpam-462	97	12	indicates	indicate	VERB
ejpam-462	97	13	the	the	DET
ejpam-462	97	14	presence	presence	NOUN
ejpam-462	97	15	or	or	CCONJ
ejpam-462	97	16	absence	absence	NOUN
ejpam-462	97	17	of	of	ADP
ejpam-462	97	18	a	a	DET
ejpam-462	97	19	specific	specific	ADJ
ejpam-462	97	20	predictor	predictor	NOUN
ejpam-462	97	21	used	use	VERB
ejpam-462	97	22	for	for	ADP
ejpam-462	97	23	a	a	DET
ejpam-462	97	24	specific	specific	ADJ
ejpam-462	97	25	response	response	NOUN
ejpam-462	97	26	exactly	exactly	ADV
ejpam-462	97	27	how	how	SCONJ
ejpam-462	97	28	the	the	DET
ejpam-462	97	29	ga	ga	PROPN
ejpam-462	97	30	operates	operate	VERB
ejpam-462	97	31	(	(	PUNCT
ejpam-462	97	32	more	more	ADV
ejpam-462	97	33	later	later	ADV
ejpam-462	97	34	)	)	PUNCT
ejpam-462	97	35	.	.	PUNCT
ejpam-462	98	1	following	follow	VERB
ejpam-462	98	2	[	[	X
ejpam-462	98	3	14	14	NUM
ejpam-462	98	4	]	]	PUNCT
ejpam-462	98	5	,	,	PUNCT
ejpam-462	98	6	we	we	PRON
ejpam-462	98	7	apply	apply	VERB
ejpam-462	98	8	feasible	feasible	ADJ
ejpam-462	98	9	generalized	generalized	ADJ
ejpam-462	98	10	least	least	ADJ
ejpam-462	98	11	squares	square	NOUN
ejpam-462	98	12	(	(	PUNCT
ejpam-462	98	13	fgls	fgls	PROPN
ejpam-462	98	14	)	)	PUNCT
ejpam-462	98	15	,	,	PUNCT
ejpam-462	98	16	which	which	PRON
ejpam-462	98	17	is	be	AUX
ejpam-462	98	18	asymptotically	asymptotically	ADV
ejpam-462	98	19	equivalent	equivalent	ADJ
ejpam-462	98	20	to	to	ADP
ejpam-462	98	21	ols	ol	NOUN
ejpam-462	98	22	.	.	PUNCT
ejpam-462	99	1	for	for	ADP
ejpam-462	99	2	fgls	fgls	NUM
ejpam-462	99	3	estimation	estimation	NOUN
ejpam-462	99	4	of	of	ADP
ejpam-462	99	5	the	the	DET
ejpam-462	99	6	subset	subset	NOUN
ejpam-462	99	7	var	var	PROPN
ejpam-462	99	8	model	model	PROPN
ejpam-462	99	9	,	,	PUNCT
ejpam-462	99	10	we	we	PRON
ejpam-462	99	11	can	can	AUX
ejpam-462	99	12	follow	follow	VERB
ejpam-462	99	13	a	a	DET
ejpam-462	99	14	simple	simple	ADJ
ejpam-462	99	15	two	two	NUM
ejpam-462	99	16	-	-	PUNCT
ejpam-462	99	17	step	step	NOUN
ejpam-462	99	18	procedure	procedure	NOUN
ejpam-462	99	19	:	:	PUNCT
ejpam-462	99	20	1	1	X
ejpam-462	99	21	.	.	X
ejpam-462	99	22	compute	compute	VERB
ejpam-462	99	23	a	a	DET
ejpam-462	99	24	consistent	consistent	ADJ
ejpam-462	99	25	estimate	estimate	NOUN
ejpam-462	99	26	of	of	ADP
ejpam-462	99	27	ω̂	ω̂	NUM
ejpam-462	99	28	:	:	PUNCT
ejpam-462	99	29	a.	a.	NOUN
ejpam-462	99	30	howe	howe	PROPN
ejpam-462	99	31	and	and	CCONJ
ejpam-462	99	32	h.	h.	PROPN
ejpam-462	99	33	bozdogan	bozdogan	PROPN
ejpam-462	99	34	/	/	SYM
ejpam-462	99	35	eur	eur	PROPN
ejpam-462	99	36	.	.	PUNCT
ejpam-462	100	1	j.	j.	PROPN
ejpam-462	100	2	pure	pure	PROPN
ejpam-462	100	3	appl	appl	PROPN
ejpam-462	100	4	.	.	PROPN
ejpam-462	100	5	math	math	PROPN
ejpam-462	100	6	,	,	PUNCT
ejpam-462	100	7	3	3	NUM
ejpam-462	100	8	(	(	PUNCT
ejpam-462	100	9	2010	2010	NUM
ejpam-462	100	10	)	)	PUNCT
ejpam-462	100	11	,	,	PUNCT
ejpam-462	100	12	382	382	NUM
ejpam-462	100	13	-	-	SYM
ejpam-462	100	14	405	405	NUM
ejpam-462	100	15	386	386	NUM
ejpam-462	100	16	•	•	NOUN
ejpam-462	100	17	estimate	estimate	NOUN
ejpam-462	100	18	the	the	DET
ejpam-462	100	19	coefficients	coefficient	NOUN
ejpam-462	100	20	:	:	PUNCT
ejpam-462	100	21	β̂1	β̂1	PUNCT
ejpam-462	100	22	=	=	SYM
ejpam-462	100	23	�	�	PROPN
ejpam-462	100	24	x	x	SYM
ejpam-462	100	25	′supxsup	′supxsup	ADJ
ejpam-462	100	26	�	�	PROPN
ejpam-462	100	27	−1	−1	NOUN
ejpam-462	100	28	x	x	SYM
ejpam-462	100	29	′supyvec	′supyvec	NOUN
ejpam-462	100	30	,	,	PUNCT
ejpam-462	100	31	•	•	ADV
ejpam-462	100	32	get	get	VERB
ejpam-462	100	33	the	the	DET
ejpam-462	100	34	estimated	estimate	VERB
ejpam-462	100	35	residuals	residual	NOUN
ejpam-462	100	36	:	:	PUNCT
ejpam-462	100	37	ǫ̂	ǫ̂	X
ejpam-462	100	38	=	=	SYM
ejpam-462	100	39	yvec	yvec	PROPN
ejpam-462	100	40	−	−	PROPN
ejpam-462	100	41	xsupβ̂1	xsupβ̂1	NOUN
ejpam-462	100	42	,	,	PUNCT
ejpam-462	100	43	•	•	ADV
ejpam-462	100	44	construct	construct	VERB
ejpam-462	100	45	an	an	DET
ejpam-462	100	46	estimate	estimate	NOUN
ejpam-462	100	47	of	of	ADP
ejpam-462	100	48	the	the	DET
ejpam-462	100	49	covariance	covariance	NOUN
ejpam-462	100	50	matrix	matrix	NOUN
ejpam-462	100	51	after	after	ADP
ejpam-462	100	52	reshaping	reshape	VERB
ejpam-462	100	53	ǫ̂	ǫ̂	NUM
ejpam-462	100	54	so	so	SCONJ
ejpam-462	100	55	that	that	SCONJ
ejpam-462	100	56	ǫ̂	ǫ̂	NUM
ejpam-462	100	57	∈	∈	NOUN
ejpam-462	100	58	rn×p	rn×p	NOUN
ejpam-462	100	59	:	:	PUNCT
ejpam-462	100	60	σ̂1	σ̂1	NOUN
ejpam-462	100	61	=	=	SYM
ejpam-462	100	62	1	1	NUM
ejpam-462	100	63	n	n	NUM
ejpam-462	100	64	ǫ̂′ǫ̂	ǫ̂′ǫ̂	NUM
ejpam-462	100	65	,	,	PUNCT
ejpam-462	100	66	•	•	NUM
ejpam-462	100	67	compute	compute	NOUN
ejpam-462	100	68	:	:	PUNCT
ejpam-462	100	69	ω̂	ω̂	PUNCT
ejpam-462	100	70	=	=	SYM
ejpam-462	100	71	σ̂1	σ̂1	NOUN
ejpam-462	100	72	⊗	⊗	NOUN
ejpam-462	100	73	in	in	ADP
ejpam-462	100	74	.	.	PUNCT
ejpam-462	101	1	2	2	X
ejpam-462	101	2	.	.	X
ejpam-462	101	3	compute	compute	VERB
ejpam-462	101	4	the	the	DET
ejpam-462	101	5	fgls	fgls	NOUN
ejpam-462	101	6	estimates	estimate	VERB
ejpam-462	101	7	:	:	PUNCT
ejpam-462	101	8	β̂fgls	β̂fgls	X
ejpam-462	102	1	=	=	SYM
ejpam-462	102	2	(	(	PUNCT
ejpam-462	102	3	x	x	SYM
ejpam-462	102	4	′	′	NOUN
ejpam-462	102	5	supω̂	supω̂	NOUN
ejpam-462	102	6	−1xsup	−1xsup	NOUN
ejpam-462	102	7	)	)	PUNCT
ejpam-462	102	8	−1x	−1x	PROPN
ejpam-462	102	9	′supω̂	′supω̂	NOUN
ejpam-462	102	10	−1yvec	−1yvec	NOUN
ejpam-462	102	11	,	,	PUNCT
ejpam-462	102	12	(	(	PUNCT
ejpam-462	102	13	5	5	NUM
ejpam-462	102	14	)	)	PUNCT
ejpam-462	102	15	ǫ̂fgls	ǫ̂fgls	NOUN
ejpam-462	102	16	=	=	SYM
ejpam-462	102	17	yvec	yvec	PROPN
ejpam-462	102	18	−	−	PROPN
ejpam-462	102	19	xsupβ̂fgls	xsupβ̂fgls	PROPN
ejpam-462	102	20	,	,	PUNCT
ejpam-462	102	21	(	(	PUNCT
ejpam-462	102	22	6	6	NUM
ejpam-462	102	23	)	)	PUNCT
ejpam-462	102	24	σ̂fgls	σ̂fgl	NOUN
ejpam-462	102	25	=	=	SYM
ejpam-462	102	26	1	1	NUM
ejpam-462	102	27	n	n	NUM
ejpam-462	102	28	ǫ̂′fglsǫ̂fgls	ǫ̂′fglsǫ̂fgls	NOUN
ejpam-462	102	29	.	.	PUNCT
ejpam-462	103	1	(	(	PUNCT
ejpam-462	103	2	7	7	X
ejpam-462	103	3	)	)	PUNCT
ejpam-462	103	4	this	this	PRON
ejpam-462	103	5	is	be	AUX
ejpam-462	103	6	the	the	DET
ejpam-462	103	7	estimation	estimation	NOUN
ejpam-462	103	8	method	method	NOUN
ejpam-462	103	9	proposed	propose	VERB
ejpam-462	103	10	in	in	ADP
ejpam-462	103	11	[	[	X
ejpam-462	103	12	3	3	NUM
ejpam-462	103	13	]	]	PUNCT
ejpam-462	103	14	.	.	PUNCT
ejpam-462	104	1	under	under	ADP
ejpam-462	104	2	the	the	DET
ejpam-462	104	3	assumption	assumption	NOUN
ejpam-462	104	4	of	of	ADP
ejpam-462	104	5	gaussianity	gaussianity	NOUN
ejpam-462	104	6	of	of	ADP
ejpam-462	104	7	the	the	DET
ejpam-462	104	8	error	error	NOUN
ejpam-462	104	9	terms	term	NOUN
ejpam-462	104	10	,	,	PUNCT
ejpam-462	104	11	the	the	DET
ejpam-462	104	12	fgls	fgls	NOUN
ejpam-462	104	13	estimators	estimator	NOUN
ejpam-462	104	14	have	have	VERB
ejpam-462	104	15	the	the	DET
ejpam-462	104	16	same	same	ADJ
ejpam-462	104	17	asymptotic	asymptotic	ADJ
ejpam-462	104	18	distribution	distribution	NOUN
ejpam-462	104	19	as	as	ADP
ejpam-462	104	20	the	the	DET
ejpam-462	104	21	traditional	traditional	ADJ
ejpam-462	104	22	maximum	maximum	ADJ
ejpam-462	104	23	likelihood	likelihood	NOUN
ejpam-462	104	24	estimators	estimator	NOUN
ejpam-462	104	25	.	.	PUNCT
ejpam-462	105	1	there	there	PRON
ejpam-462	105	2	is	be	VERB
ejpam-462	105	3	one	one	NUM
ejpam-462	105	4	slight	slight	ADJ
ejpam-462	105	5	modification	modification	NOUN
ejpam-462	105	6	that	that	PRON
ejpam-462	105	7	needs	need	VERB
ejpam-462	105	8	to	to	PART
ejpam-462	105	9	be	be	AUX
ejpam-462	105	10	made	make	VERB
ejpam-462	105	11	to	to	ADP
ejpam-462	105	12	the	the	DET
ejpam-462	105	13	3rd	3rd	ADJ
ejpam-462	105	14	items	item	NOUN
ejpam-462	105	15	in	in	ADP
ejpam-462	105	16	each	each	PRON
ejpam-462	105	17	of	of	ADP
ejpam-462	105	18	the	the	DET
ejpam-462	105	19	steps	step	NOUN
ejpam-462	105	20	above	above	ADV
ejpam-462	105	21	.	.	PUNCT
ejpam-462	106	1	in	in	ADP
ejpam-462	106	2	many	many	ADJ
ejpam-462	106	3	real	real	ADJ
ejpam-462	106	4	-	-	PUNCT
ejpam-462	106	5	life	life	NOUN
ejpam-462	106	6	problems	problem	NOUN
ejpam-462	106	7	,	,	PUNCT
ejpam-462	106	8	covariance	covariance	NOUN
ejpam-462	106	9	matrices	matrix	NOUN
ejpam-462	106	10	can	can	AUX
ejpam-462	106	11	become	become	VERB
ejpam-462	106	12	ill	ill	ADV
ejpam-462	106	13	-	-	PUNCT
ejpam-462	106	14	conditioned	condition	VERB
ejpam-462	106	15	,	,	PUNCT
ejpam-462	106	16	non	non	ADJ
ejpam-462	106	17	-	-	ADJ
ejpam-462	106	18	positive	positive	ADJ
ejpam-462	106	19	definite	definite	ADJ
ejpam-462	106	20	,	,	PUNCT
ejpam-462	106	21	or	or	CCONJ
ejpam-462	106	22	singular	singular	NOUN
ejpam-462	106	23	.	.	PUNCT
ejpam-462	107	1	this	this	PRON
ejpam-462	107	2	is	be	AUX
ejpam-462	107	3	especially	especially	ADV
ejpam-462	107	4	true	true	ADJ
ejpam-462	107	5	in	in	ADP
ejpam-462	107	6	cases	case	NOUN
ejpam-462	107	7	of	of	ADP
ejpam-462	107	8	regression	regression	NOUN
ejpam-462	107	9	with	with	ADP
ejpam-462	107	10	highly	highly	ADV
ejpam-462	107	11	collinear	collinear	ADJ
ejpam-462	107	12	predictors	predictor	NOUN
ejpam-462	107	13	.	.	PUNCT
ejpam-462	108	1	as	as	SCONJ
ejpam-462	108	2	can	can	AUX
ejpam-462	108	3	be	be	AUX
ejpam-462	108	4	seen	see	VERB
ejpam-462	108	5	in	in	ADP
ejpam-462	108	6	table	table	NOUN
ejpam-462	108	7	1	1	NUM
ejpam-462	108	8	,	,	PUNCT
ejpam-462	108	9	there	there	PRON
ejpam-462	108	10	is	be	VERB
ejpam-462	108	11	a	a	DET
ejpam-462	108	12	high	high	ADJ
ejpam-462	108	13	degree	degree	NOUN
ejpam-462	108	14	of	of	ADP
ejpam-462	108	15	multicollinearity	multicollinearity	NOUN
ejpam-462	108	16	among	among	ADP
ejpam-462	108	17	the	the	DET
ejpam-462	108	18	daily	daily	ADJ
ejpam-462	108	19	changes	change	NOUN
ejpam-462	108	20	of	of	ADP
ejpam-462	108	21	the	the	DET
ejpam-462	108	22	first	first	ADJ
ejpam-462	108	23	five	five	NUM
ejpam-462	108	24	indices	index	NOUN
ejpam-462	108	25	used	use	VERB
ejpam-462	108	26	in	in	ADP
ejpam-462	108	27	our	our	PRON
ejpam-462	108	28	application	application	NOUN
ejpam-462	108	29	.	.	PUNCT
ejpam-462	109	1	the	the	DET
ejpam-462	109	2	usual	usual	ADJ
ejpam-462	109	3	responsetable	responsetable	ADJ
ejpam-462	109	4	1	1	NUM
ejpam-462	109	5	:	:	PUNCT
ejpam-462	109	6	correlation	correlation	NOUN
ejpam-462	109	7	matrix	matrix	NOUN
ejpam-462	109	8	for	for	ADP
ejpam-462	109	9	indi	indi	PROPN
ejpam-462	109	10	es	es	PROPN
ejpam-462	109	11	used	use	VERB
ejpam-462	109	12	.	.	PUNCT
ejpam-462	110	1	dj20	dj20	PROPN
ejpam-462	110	2	mid	mid	ADJ
ejpam-462	110	3	ndx	ndx	PROPN
ejpam-462	110	4	rut	rut	NOUN
ejpam-462	110	5	spx	spx	PROPN
ejpam-462	110	6	xau	xau	PROPN
ejpam-462	110	7	dj20	dj20	PROPN
ejpam-462	110	8	1.000	1.000	NUM
ejpam-462	110	9	0.736	0.736	NUM
ejpam-462	110	10	0.613	0.613	NUM
ejpam-462	110	11	0.702	0.702	NUM
ejpam-462	110	12	0.693	0.693	NUM
ejpam-462	110	13	−0.107	−0.107	VERB
ejpam-462	110	14	mid	mid	ADJ
ejpam-462	110	15	1.000	1.000	NUM
ejpam-462	110	16	0.881	0.881	NUM
ejpam-462	110	17	0.935	0.935	NUM
ejpam-462	110	18	0.924	0.924	NUM
ejpam-462	110	19	−0.158	−0.158	NOUN
ejpam-462	110	20	ndx	ndx	PROPN
ejpam-462	110	21	1.000	1.000	NUM
ejpam-462	110	22	0.886	0.886	NUM
ejpam-462	110	23	0.877	0.877	NUM
ejpam-462	110	24	−0.231	−0.231	ADJ
ejpam-462	110	25	rut	rut	NOUN
ejpam-462	110	26	1.000	1.000	NUM
ejpam-462	110	27	0.869	0.869	NUM
ejpam-462	110	28	−0.151	−0.151	NOUN
ejpam-462	110	29	spx	spx	NUM
ejpam-462	110	30	1.000	1.000	NUM
ejpam-462	110	31	−0.179	−0.179	PROPN
ejpam-462	110	32	xau	xau	PROPN
ejpam-462	110	33	1.000	1.000	NUM
ejpam-462	110	34	to	to	ADP
ejpam-462	110	35	singular	singular	NOUN
ejpam-462	110	36	or	or	CCONJ
ejpam-462	110	37	ill	ill	ADV
ejpam-462	110	38	-	-	PUNCT
ejpam-462	110	39	conditioned	condition	VERB
ejpam-462	110	40	covariance	covariance	NOUN
ejpam-462	110	41	matrix	matrix	NOUN
ejpam-462	110	42	estimates	estimate	NOUN
ejpam-462	110	43	is	be	AUX
ejpam-462	110	44	ridge	ridge	NOUN
ejpam-462	110	45	regularization	regularization	NOUN
ejpam-462	110	46	,	,	PUNCT
ejpam-462	110	47	which	which	PRON
ejpam-462	110	48	works	work	VERB
ejpam-462	110	49	to	to	PART
ejpam-462	110	50	counteract	counteract	VERB
ejpam-462	110	51	the	the	DET
ejpam-462	110	52	ill	ill	ADJ
ejpam-462	110	53	-	-	PUNCT
ejpam-462	110	54	conditionedness	conditionedness	NOUN
ejpam-462	110	55	by	by	ADP
ejpam-462	110	56	adjusting	adjust	VERB
ejpam-462	110	57	the	the	DET
ejpam-462	110	58	eigenvalues	eigenvalue	NOUN
ejpam-462	110	59	of	of	ADP
ejpam-462	110	60	σ̂.	σ̂.	NOUN
ejpam-462	110	61	usually	usually	ADV
ejpam-462	110	62	,	,	PUNCT
ejpam-462	110	63	the	the	DET
ejpam-462	110	64	ridge	ridge	NOUN
ejpam-462	110	65	parameter	parameter	PROPN
ejpam-462	110	66	α	α	PROPN
ejpam-462	110	67	is	be	AUX
ejpam-462	110	68	chosen	choose	VERB
ejpam-462	110	69	to	to	PART
ejpam-462	110	70	be	be	AUX
ejpam-462	110	71	very	very	ADV
ejpam-462	110	72	small	small	ADJ
ejpam-462	110	73	.	.	PUNCT
ejpam-462	111	1	this	this	PRON
ejpam-462	111	2	,	,	PUNCT
ejpam-462	111	3	of	of	ADP
ejpam-462	111	4	course	course	NOUN
ejpam-462	111	5	,	,	PUNCT
ejpam-462	111	6	begs	beg	VERB
ejpam-462	111	7	the	the	DET
ejpam-462	111	8	questions	question	NOUN
ejpam-462	111	9	•	•	ADP
ejpam-462	111	10	“	"	PUNCT
ejpam-462	111	11	how	how	SCONJ
ejpam-462	111	12	large	large	ADJ
ejpam-462	111	13	should	should	AUX
ejpam-462	111	14	α	α	PRON
ejpam-462	111	15	be	be	AUX
ejpam-462	111	16	?	?	PUNCT
ejpam-462	111	17	”	"	PUNCT
ejpam-462	112	1	•	•	ADP
ejpam-462	112	2	“	"	PUNCT
ejpam-462	112	3	how	how	SCONJ
ejpam-462	112	4	small	small	ADJ
ejpam-462	112	5	can	can	AUX
ejpam-462	112	6	α	α	PRON
ejpam-462	112	7	be	be	AUX
ejpam-462	112	8	?	?	PUNCT
ejpam-462	112	9	”	"	PUNCT
ejpam-462	113	1	the	the	DET
ejpam-462	113	2	answer	answer	NOUN
ejpam-462	113	3	to	to	ADP
ejpam-462	113	4	ridge	ridge	NOUN
ejpam-462	113	5	regularization	regularization	NOUN
ejpam-462	113	6	questions	question	NOUN
ejpam-462	113	7	is	be	AUX
ejpam-462	113	8	to	to	PART
ejpam-462	113	9	use	use	VERB
ejpam-462	113	10	a	a	DET
ejpam-462	113	11	robust	robust	ADJ
ejpam-462	113	12	covariance	covariance	NOUN
ejpam-462	113	13	estimator	estimator	NOUN
ejpam-462	113	14	that	that	PRON
ejpam-462	113	15	data	data	NOUN
ejpam-462	113	16	-	-	PUNCT
ejpam-462	113	17	adaptively	adaptively	ADV
ejpam-462	113	18	improves	improve	VERB
ejpam-462	113	19	ill	ill	ADV
ejpam-462	113	20	-	-	PUNCT
ejpam-462	113	21	conditioned	condition	VERB
ejpam-462	113	22	and/or	and/or	CCONJ
ejpam-462	113	23	singular	singular	ADJ
ejpam-462	113	24	covariance	covariance	NOUN
ejpam-462	113	25	matrix	matrix	NOUN
ejpam-462	113	26	estimates	estimate	NOUN
ejpam-462	113	27	.	.	PUNCT
ejpam-462	114	1	many	many	ADJ
ejpam-462	114	2	different	different	ADJ
ejpam-462	114	3	robust	robust	ADJ
ejpam-462	114	4	,	,	PUNCT
ejpam-462	114	5	or	or	CCONJ
ejpam-462	114	6	smoothed	smooth	VERB
ejpam-462	114	7	,	,	PUNCT
ejpam-462	114	8	covariance	covariance	NOUN
ejpam-462	114	9	estimators	estimator	NOUN
ejpam-462	114	10	have	have	AUX
ejpam-462	114	11	been	be	AUX
ejpam-462	114	12	developed	develop	VERB
ejpam-462	114	13	;	;	PUNCT
ejpam-462	114	14	several	several	ADJ
ejpam-462	114	15	of	of	ADP
ejpam-462	114	16	them	they	PRON
ejpam-462	114	17	work	work	VERB
ejpam-462	114	18	by	by	ADP
ejpam-462	114	19	the	the	DET
ejpam-462	114	20	same	same	ADJ
ejpam-462	114	21	mechanism	mechanism	NOUN
ejpam-462	114	22	as	as	SCONJ
ejpam-462	114	23	ridge	ridge	NOUN
ejpam-462	114	24	regularization	regularization	NOUN
ejpam-462	114	25	perturb	perturb	VERB
ejpam-462	114	26	the	the	DET
ejpam-462	114	27	diagonals	diagonal	NOUN
ejpam-462	114	28	,	,	PUNCT
ejpam-462	114	29	and	and	CCONJ
ejpam-462	114	30	hence	hence	ADV
ejpam-462	114	31	,	,	PUNCT
ejpam-462	114	32	a.	a.	NOUN
ejpam-462	114	33	howe	howe	NOUN
ejpam-462	114	34	and	and	CCONJ
ejpam-462	114	35	h.	h.	PROPN
ejpam-462	114	36	bozdogan	bozdogan	PROPN
ejpam-462	114	37	/	/	SYM
ejpam-462	114	38	eur	eur	PROPN
ejpam-462	114	39	.	.	PUNCT
ejpam-462	115	1	j.	j.	PROPN
ejpam-462	115	2	pure	pure	PROPN
ejpam-462	115	3	appl	appl	PROPN
ejpam-462	115	4	.	.	PROPN
ejpam-462	115	5	math	math	PROPN
ejpam-462	115	6	,	,	PUNCT
ejpam-462	115	7	3	3	NUM
ejpam-462	115	8	(	(	PUNCT
ejpam-462	115	9	2010	2010	NUM
ejpam-462	115	10	)	)	PUNCT
ejpam-462	115	11	,	,	PUNCT
ejpam-462	115	12	382	382	NUM
ejpam-462	115	13	-	-	SYM
ejpam-462	115	14	405	405	NUM
ejpam-462	115	15	387	387	NUM
ejpam-462	115	16	the	the	DET
ejpam-462	115	17	eigenvalues	eigenvalue	NOUN
ejpam-462	115	18	.	.	PUNCT
ejpam-462	116	1	in	in	ADP
ejpam-462	116	2	this	this	DET
ejpam-462	116	3	paper	paper	NOUN
ejpam-462	116	4	,	,	PUNCT
ejpam-462	116	5	we	we	PRON
ejpam-462	116	6	use	use	VERB
ejpam-462	116	7	the	the	DET
ejpam-462	116	8	maximum	maximum	ADJ
ejpam-462	116	9	likelihood	likelihood	NOUN
ejpam-462	116	10	/	/	SYM
ejpam-462	116	11	empirical	empirical	ADJ
ejpam-462	116	12	bayes	bayes	PROPN
ejpam-462	116	13	covariance	covariance	NOUN
ejpam-462	116	14	estimator	estimator	NOUN
ejpam-462	116	15	σ̂m	σ̂m	PROPN
ejpam-462	116	16	le	le	PROPN
ejpam-462	116	17	/	/	SYM
ejpam-462	116	18	eb	eb	PROPN
ejpam-462	116	19	=	=	SYM
ejpam-462	116	20	σ̂+	σ̂+	PROPN
ejpam-462	116	21	p−	p−	NOUN
ejpam-462	116	22	1	1	NUM
ejpam-462	116	23	(	(	PUNCT
ejpam-462	116	24	n	n	CCONJ
ejpam-462	116	25	)	)	PUNCT
ejpam-462	116	26	t	t	PROPN
ejpam-462	116	27	r(σ̂−1	r(σ̂−1	PROPN
ejpam-462	116	28	)	)	PUNCT
ejpam-462	116	29	ip	ip	NOUN
ejpam-462	116	30	,	,	PUNCT
ejpam-462	116	31	(	(	PUNCT
ejpam-462	116	32	8)	8)	NUM
ejpam-462	116	33	which	which	PRON
ejpam-462	116	34	is	be	AUX
ejpam-462	116	35	ridge	ridge	NOUN
ejpam-462	116	36	regularization	regularization	NOUN
ejpam-462	116	37	,	,	PUNCT
ejpam-462	116	38	where	where	SCONJ
ejpam-462	116	39	the	the	DET
ejpam-462	116	40	ridge	ridge	NOUN
ejpam-462	116	41	parameter	parameter	PROPN
ejpam-462	116	42	α	α	PROPN
ejpam-462	116	43	is	be	AUX
ejpam-462	116	44	determined	determine	VERB
ejpam-462	116	45	by	by	ADP
ejpam-462	116	46	the	the	DET
ejpam-462	116	47	data	datum	NOUN
ejpam-462	116	48	not	not	PART
ejpam-462	116	49	a	a	DET
ejpam-462	116	50	subjective	subjective	ADJ
ejpam-462	116	51	decision	decision	NOUN
ejpam-462	116	52	.	.	PUNCT
ejpam-462	117	1	for	for	ADP
ejpam-462	117	2	various	various	ADJ
ejpam-462	117	3	other	other	ADJ
ejpam-462	117	4	robust	robust	ADJ
ejpam-462	117	5	covariance	covariance	NOUN
ejpam-462	117	6	estimators	estimator	NOUN
ejpam-462	117	7	we	we	PRON
ejpam-462	117	8	’ve	’ve	AUX
ejpam-462	117	9	found	find	VERB
ejpam-462	117	10	valuable	valuable	ADJ
ejpam-462	117	11	,	,	PUNCT
ejpam-462	117	12	see	see	VERB
ejpam-462	117	13	[	[	X
ejpam-462	117	14	22	22	NUM
ejpam-462	117	15	,	,	PUNCT
ejpam-462	117	16	19	19	NUM
ejpam-462	117	17	,	,	PUNCT
ejpam-462	117	18	7	7	NUM
ejpam-462	117	19	,	,	PUNCT
ejpam-462	117	20	25	25	NUM
ejpam-462	117	21	,	,	PUNCT
ejpam-462	117	22	12	12	NUM
ejpam-462	117	23	]	]	PUNCT
ejpam-462	117	24	.	.	PUNCT
ejpam-462	118	1	the	the	DET
ejpam-462	118	2	integration	integration	NOUN
ejpam-462	118	3	with	with	ADP
ejpam-462	118	4	fgls	fgls	NOUN
ejpam-462	118	5	estimation	estimation	NOUN
ejpam-462	118	6	is	be	AUX
ejpam-462	118	7	simple	simple	ADJ
ejpam-462	118	8	;	;	PUNCT
ejpam-462	118	9	assuming	assume	VERB
ejpam-462	118	10	we	we	PRON
ejpam-462	118	11	were	be	AUX
ejpam-462	118	12	using	use	VERB
ejpam-462	118	13	σ̂m	σ̂m	PROPN
ejpam-462	118	14	le	le	PROPN
ejpam-462	118	15	/	/	SYM
ejpam-462	118	16	eb	eb	PROPN
ejpam-462	118	17	,	,	PUNCT
ejpam-462	118	18	the	the	DET
ejpam-462	118	19	final	final	ADJ
ejpam-462	118	20	part	part	NOUN
ejpam-462	118	21	of	of	ADP
ejpam-462	118	22	step	step	NOUN
ejpam-462	118	23	1	1	NUM
ejpam-462	118	24	would	would	AUX
ejpam-462	118	25	entail	entail	VERB
ejpam-462	118	26	computing	compute	VERB
ejpam-462	118	27	ω̂	ω̂	PUNCT
ejpam-462	118	28	=	=	SYM
ejpam-462	118	29	σ̂m	σ̂m	X
ejpam-462	118	30	le	le	PROPN
ejpam-462	118	31	/	/	SYM
ejpam-462	118	32	eb⊗	eb⊗	NOUN
ejpam-462	118	33	in	in	ADV
ejpam-462	118	34	.	.	PUNCT
ejpam-462	119	1	finally	finally	ADV
ejpam-462	119	2	,	,	PUNCT
ejpam-462	119	3	after	after	SCONJ
ejpam-462	119	4	the	the	DET
ejpam-462	119	5	fgls	fgls	NOUN
ejpam-462	119	6	estimates	estimate	NOUN
ejpam-462	119	7	of	of	ADP
ejpam-462	119	8	the	the	DET
ejpam-462	119	9	coefficients	coefficient	NOUN
ejpam-462	119	10	have	have	AUX
ejpam-462	119	11	been	be	AUX
ejpam-462	119	12	computed	compute	VERB
ejpam-462	119	13	,	,	PUNCT
ejpam-462	119	14	we	we	PRON
ejpam-462	119	15	smooth	smooth	VERB
ejpam-462	119	16	the	the	DET
ejpam-462	119	17	σ̂∗fgls	σ̂∗fgls	NOUN
ejpam-462	119	18	using	use	VERB
ejpam-462	119	19	the	the	DET
ejpam-462	119	20	same	same	ADJ
ejpam-462	119	21	estimator	estimator	NOUN
ejpam-462	119	22	.	.	PUNCT
ejpam-462	120	1	in	in	ADP
ejpam-462	120	2	general	general	ADJ
ejpam-462	120	3	,	,	PUNCT
ejpam-462	120	4	we	we	PRON
ejpam-462	120	5	prefer	prefer	VERB
ejpam-462	120	6	to	to	PART
ejpam-462	120	7	not	not	PART
ejpam-462	120	8	change	change	VERB
ejpam-462	120	9	the	the	DET
ejpam-462	120	10	problem	problem	NOUN
ejpam-462	120	11	more	more	ADV
ejpam-462	120	12	than	than	ADP
ejpam-462	120	13	necessary	necessary	ADJ
ejpam-462	120	14	,	,	PUNCT
ejpam-462	120	15	so	so	ADV
ejpam-462	120	16	we	we	PRON
ejpam-462	120	17	perform	perform	VERB
ejpam-462	120	18	two	two	NUM
ejpam-462	120	19	tests	test	NOUN
ejpam-462	120	20	for	for	ADP
ejpam-462	120	21	matrix	matrix	NOUN
ejpam-462	120	22	condition	condition	NOUN
ejpam-462	120	23	before	before	ADP
ejpam-462	120	24	using	use	VERB
ejpam-462	120	25	the	the	DET
ejpam-462	120	26	selected	select	VERB
ejpam-462	120	27	robust	robust	ADJ
ejpam-462	120	28	covariance	covariance	NOUN
ejpam-462	120	29	estimator	estimator	NOUN
ejpam-462	120	30	if	if	SCONJ
ejpam-462	120	31	the	the	DET
ejpam-462	120	32	answer	answer	NOUN
ejpam-462	120	33	to	to	ADP
ejpam-462	120	34	either	either	DET
ejpam-462	120	35	question	question	NOUN
ejpam-462	120	36	is	be	AUX
ejpam-462	120	37	in	in	ADP
ejpam-462	120	38	the	the	DET
ejpam-462	120	39	affirmative	affirmative	NOUN
ejpam-462	120	40	,	,	PUNCT
ejpam-462	120	41	we	we	PRON
ejpam-462	120	42	instead	instead	ADV
ejpam-462	120	43	use	use	VERB
ejpam-462	120	44	the	the	DET
ejpam-462	120	45	robust	robust	ADJ
ejpam-462	120	46	estimator	estimator	NOUN
ejpam-462	120	47	:	:	PUNCT
ejpam-462	121	1	1	1	X
ejpam-462	121	2	.	.	PUNCT
ejpam-462	121	3	is	be	AUX
ejpam-462	121	4	the	the	DET
ejpam-462	121	5	reciprocal	reciprocal	NOUN
ejpam-462	121	6	of	of	ADP
ejpam-462	121	7	the	the	DET
ejpam-462	121	8	condition	condition	NOUN
ejpam-462	121	9	number	number	NOUN
ejpam-462	121	10	small	small	ADJ
ejpam-462	121	11	:	:	PUNCT
ejpam-462	121	12	κ−1(σ̂)≤	κ−1(σ̂)≤	NOUN
ejpam-462	121	13	1e−10	1e−10	NUM
ejpam-462	121	14	?	?	PUNCT
ejpam-462	122	1	2	2	NUM
ejpam-462	122	2	.	.	PUNCT
ejpam-462	122	3	is	be	AUX
ejpam-462	122	4	σ̂	σ̂	X
ejpam-462	122	5	nonpositive	nonpositive	ADJ
ejpam-462	122	6	definite	definite	ADJ
ejpam-462	122	7	?	?	PUNCT
ejpam-462	123	1	2.3	2.3	NUM
ejpam-462	123	2	.	.	PUNCT
ejpam-462	123	3	error	error	NOUN
ejpam-462	123	4	term	term	NOUN
ejpam-462	123	5	bootstrap	bootstrap	NOUN
ejpam-462	123	6	procedure	procedure	NOUN
ejpam-462	123	7	runkle	runkle	NOUN
ejpam-462	124	1	[	[	X
ejpam-462	124	2	21	21	NUM
ejpam-462	124	3	]	]	PUNCT
ejpam-462	124	4	identified	identify	VERB
ejpam-462	124	5	several	several	ADJ
ejpam-462	124	6	shortcomings	shortcoming	NOUN
ejpam-462	124	7	with	with	ADP
ejpam-462	124	8	the	the	DET
ejpam-462	124	9	ways	way	NOUN
ejpam-462	124	10	in	in	ADP
ejpam-462	124	11	which	which	PRON
ejpam-462	124	12	econometricians	econometrician	NOUN
ejpam-462	124	13	computed	compute	VERB
ejpam-462	124	14	and	and	CCONJ
ejpam-462	124	15	reported	report	VERB
ejpam-462	124	16	variance	variance	NOUN
ejpam-462	124	17	decompositions	decomposition	NOUN
ejpam-462	124	18	and	and	CCONJ
ejpam-462	124	19	impulse	impulse	ADJ
ejpam-462	124	20	response	response	NOUN
ejpam-462	124	21	functions	function	NOUN
ejpam-462	124	22	.	.	PUNCT
ejpam-462	125	1	chief	chief	NOUN
ejpam-462	125	2	was	be	AUX
ejpam-462	125	3	that	that	PRON
ejpam-462	125	4	confidence	confidence	NOUN
ejpam-462	125	5	intervals	interval	NOUN
ejpam-462	125	6	around	around	ADP
ejpam-462	125	7	estimates	estimate	NOUN
ejpam-462	125	8	were	be	AUX
ejpam-462	125	9	missing	miss	VERB
ejpam-462	125	10	in	in	ADP
ejpam-462	125	11	the	the	DET
ejpam-462	125	12	literature	literature	NOUN
ejpam-462	125	13	.	.	PUNCT
ejpam-462	126	1	his	his	PRON
ejpam-462	126	2	claims	claim	NOUN
ejpam-462	126	3	were	be	AUX
ejpam-462	126	4	that	that	SCONJ
ejpam-462	126	5	error	error	NOUN
ejpam-462	126	6	bands	band	NOUN
ejpam-462	126	7	became	become	VERB
ejpam-462	126	8	so	so	ADV
ejpam-462	126	9	large	large	ADJ
ejpam-462	126	10	as	as	SCONJ
ejpam-462	126	11	to	to	PART
ejpam-462	126	12	make	make	VERB
ejpam-462	126	13	inference	inference	NOUN
ejpam-462	126	14	from	from	ADP
ejpam-462	126	15	point	point	NOUN
ejpam-462	126	16	estimates	estimate	NOUN
ejpam-462	126	17	useless	useless	ADJ
ejpam-462	126	18	and	and	CCONJ
ejpam-462	126	19	invalid	invalid	ADJ
ejpam-462	126	20	.	.	PUNCT
ejpam-462	127	1	he	he	PRON
ejpam-462	127	2	demonstrated	demonstrate	VERB
ejpam-462	127	3	,	,	PUNCT
ejpam-462	127	4	using	use	VERB
ejpam-462	127	5	the	the	DET
ejpam-462	127	6	example	example	NOUN
ejpam-462	127	7	from	from	ADP
ejpam-462	127	8	[	[	X
ejpam-462	127	9	24	24	NUM
ejpam-462	127	10	]	]	PUNCT
ejpam-462	127	11	,	,	PUNCT
ejpam-462	127	12	both	both	CCONJ
ejpam-462	127	13	an	an	DET
ejpam-462	127	14	analytical	analytical	ADJ
ejpam-462	127	15	and	and	CCONJ
ejpam-462	127	16	an	an	DET
ejpam-462	127	17	empirical	empirical	ADJ
ejpam-462	127	18	method	method	NOUN
ejpam-462	127	19	for	for	ADP
ejpam-462	127	20	computing	compute	VERB
ejpam-462	127	21	the	the	DET
ejpam-462	127	22	missing	miss	VERB
ejpam-462	127	23	confidence	confidence	NOUN
ejpam-462	127	24	intervals	interval	NOUN
ejpam-462	127	25	.	.	PUNCT
ejpam-462	128	1	we	we	PRON
ejpam-462	128	2	employ	employ	VERB
ejpam-462	128	3	a	a	DET
ejpam-462	128	4	variation	variation	NOUN
ejpam-462	128	5	of	of	ADP
ejpam-462	128	6	his	his	PRON
ejpam-462	128	7	bootstrap	bootstrap	NOUN
ejpam-462	128	8	procedure	procedure	NOUN
ejpam-462	128	9	here	here	ADV
ejpam-462	128	10	.	.	PUNCT
ejpam-462	129	1	the	the	DET
ejpam-462	129	2	fundamental	fundamental	ADJ
ejpam-462	129	3	insight	insight	NOUN
ejpam-462	129	4	is	be	AUX
ejpam-462	129	5	that	that	SCONJ
ejpam-462	129	6	,	,	PUNCT
ejpam-462	129	7	since	since	SCONJ
ejpam-462	129	8	the	the	DET
ejpam-462	129	9	estimated	estimate	VERB
ejpam-462	129	10	residuals	residual	NOUN
ejpam-462	129	11	from	from	ADP
ejpam-462	129	12	any	any	DET
ejpam-462	129	13	model	model	NOUN
ejpam-462	129	14	are	be	AUX
ejpam-462	129	15	assumed	assume	VERB
ejpam-462	129	16	to	to	PART
ejpam-462	129	17	be	be	AUX
ejpam-462	129	18	a	a	DET
ejpam-462	129	19	representative	representative	ADJ
ejpam-462	129	20	sample	sample	NOUN
ejpam-462	129	21	of	of	ADP
ejpam-462	129	22	the	the	DET
ejpam-462	129	23	true	true	ADJ
ejpam-462	129	24	disturbances	disturbance	NOUN
ejpam-462	129	25	,	,	PUNCT
ejpam-462	129	26	the	the	DET
ejpam-462	129	27	order	order	NOUN
ejpam-462	129	28	in	in	ADP
ejpam-462	129	29	which	which	PRON
ejpam-462	129	30	they	they	PRON
ejpam-462	129	31	occur	occur	VERB
ejpam-462	129	32	should	should	AUX
ejpam-462	129	33	not	not	PART
ejpam-462	129	34	matter	matter	VERB
ejpam-462	129	35	.	.	PUNCT
ejpam-462	130	1	this	this	PRON
ejpam-462	130	2	allows	allow	VERB
ejpam-462	130	3	us	we	PRON
ejpam-462	130	4	to	to	PART
ejpam-462	130	5	determine	determine	VERB
ejpam-462	130	6	an	an	DET
ejpam-462	130	7	empirical	empirical	ADJ
ejpam-462	130	8	distribution	distribution	NOUN
ejpam-462	130	9	(	(	PUNCT
ejpam-462	130	10	and	and	CCONJ
ejpam-462	130	11	mean	mean	VERB
ejpam-462	130	12	)	)	PUNCT
ejpam-462	130	13	by	by	ADP
ejpam-462	130	14	generating	generate	VERB
ejpam-462	130	15	many	many	ADJ
ejpam-462	130	16	artificial	artificial	ADJ
ejpam-462	130	17	observations	observation	NOUN
ejpam-462	130	18	of	of	ADP
ejpam-462	130	19	the	the	DET
ejpam-462	130	20	data	datum	NOUN
ejpam-462	130	21	using	use	VERB
ejpam-462	130	22	the	the	DET
ejpam-462	130	23	estimated	estimate	VERB
ejpam-462	130	24	residuals	residual	NOUN
ejpam-462	130	25	.	.	PUNCT
ejpam-462	131	1	with	with	ADP
ejpam-462	131	2	our	our	PRON
ejpam-462	131	3	modifications	modification	NOUN
ejpam-462	131	4	,	,	PUNCT
ejpam-462	131	5	the	the	DET
ejpam-462	131	6	procedure	procedure	NOUN
ejpam-462	131	7	iterates	iterate	VERB
ejpam-462	131	8	these	these	DET
ejpam-462	131	9	four	four	NUM
ejpam-462	131	10	steps	step	NOUN
ejpam-462	131	11	after	after	ADP
ejpam-462	131	12	estimating	estimate	VERB
ejpam-462	131	13	a	a	DET
ejpam-462	131	14	subset	subset	ADJ
ejpam-462	131	15	var	var	NOUN
ejpam-462	131	16	model	model	NOUN
ejpam-462	131	17	:	:	PUNCT
ejpam-462	131	18	1	1	X
ejpam-462	131	19	.	.	X
ejpam-462	131	20	draw	draw	VERB
ejpam-462	131	21	an	an	DET
ejpam-462	131	22	appropriate	appropriate	ADJ
ejpam-462	131	23	number	number	NOUN
ejpam-462	131	24	of	of	ADP
ejpam-462	131	25	bootstrapped	bootstrappe	VERB
ejpam-462	131	26	realizations	realization	NOUN
ejpam-462	131	27	from	from	ADP
ejpam-462	131	28	ǫ̂fgls	ǫ̂fgl	NOUN
ejpam-462	131	29	uniformly	uniformly	ADV
ejpam-462	131	30	and	and	CCONJ
ejpam-462	131	31	with	with	ADP
ejpam-462	131	32	replacement	replacement	NOUN
ejpam-462	131	33	.	.	PUNCT
ejpam-462	132	1	the	the	DET
ejpam-462	132	2	bootstrapped	bootstrappe	VERB
ejpam-462	132	3	matrix	matrix	NOUN
ejpam-462	132	4	is	be	AUX
ejpam-462	132	5	called	call	VERB
ejpam-462	132	6	ǫ̂fgls	ǫ̂fgl	NOUN
ejpam-462	132	7	,	,	PUNCT
ejpam-462	132	8	b	b	NOUN
ejpam-462	132	9	;	;	PUNCT
ejpam-462	132	10	the	the	DET
ejpam-462	132	11	number	number	NOUN
ejpam-462	132	12	of	of	ADP
ejpam-462	132	13	rows	row	NOUN
ejpam-462	132	14	it	it	PRON
ejpam-462	132	15	contains	contain	VERB
ejpam-462	132	16	is	be	AUX
ejpam-462	132	17	equal	equal	ADJ
ejpam-462	132	18	to	to	ADP
ejpam-462	132	19	the	the	DET
ejpam-462	132	20	original	original	ADJ
ejpam-462	132	21	(	(	PUNCT
ejpam-462	132	22	in	in	ADP
ejpam-462	132	23	-	-	PUNCT
ejpam-462	132	24	sample	sample	NOUN
ejpam-462	132	25	)	)	PUNCT
ejpam-462	132	26	sample	sample	NOUN
ejpam-462	132	27	size	size	NOUN
ejpam-462	132	28	plus	plus	CCONJ
ejpam-462	132	29	enough	enough	ADJ
ejpam-462	132	30	disturbances	disturbance	NOUN
ejpam-462	132	31	for	for	ADP
ejpam-462	132	32	all	all	DET
ejpam-462	132	33	forecast	forecast	NOUN
ejpam-462	132	34	observations	observation	NOUN
ejpam-462	132	35	.	.	PUNCT
ejpam-462	133	1	2	2	X
ejpam-462	133	2	.	.	X
ejpam-462	133	3	conditioning	conditioning	NOUN
ejpam-462	133	4	on	on	ADP
ejpam-462	133	5	the	the	DET
ejpam-462	133	6	pre	pre	ADJ
ejpam-462	133	7	-	-	ADJ
ejpam-462	133	8	sample	sample	ADJ
ejpam-462	133	9	observations	observation	NOUN
ejpam-462	133	10	,	,	PUNCT
ejpam-462	133	11	recursively	recursively	ADV
ejpam-462	133	12	simulate	simulate	VERB
ejpam-462	133	13	the	the	DET
ejpam-462	133	14	data	datum	NOUN
ejpam-462	133	15	yb	yb	PROPN
ejpam-462	133	16	using	use	VERB
ejpam-462	133	17	the	the	DET
ejpam-462	133	18	β̂fgls	β̂fgls	SYM
ejpam-462	133	19	model	model	NOUN
ejpam-462	133	20	coefficients	coefficient	NOUN
ejpam-462	133	21	matrix	matrix	NOUN
ejpam-462	133	22	and	and	CCONJ
ejpam-462	133	23	the	the	DET
ejpam-462	133	24	error	error	NOUN
ejpam-462	133	25	terms	term	NOUN
ejpam-462	133	26	from	from	ADP
ejpam-462	133	27	ǫ̂fgls	ǫ̂fgls	NOUN
ejpam-462	133	28	,	,	PUNCT
ejpam-462	133	29	b	b	NOUN
ejpam-462	133	30	,	,	PUNCT
ejpam-462	133	31	as	as	ADP
ejpam-462	133	32	in	in	ADP
ejpam-462	133	33	(	(	PUNCT
ejpam-462	133	34	4	4	NUM
ejpam-462	133	35	)	)	PUNCT
ejpam-462	133	36	.	.	PUNCT
ejpam-462	134	1	3	3	X
ejpam-462	134	2	.	.	X
ejpam-462	134	3	with	with	ADP
ejpam-462	134	4	the	the	DET
ejpam-462	134	5	simulated	simulate	VERB
ejpam-462	134	6	dependent	dependent	ADJ
ejpam-462	134	7	and	and	CCONJ
ejpam-462	134	8	independent	independent	ADJ
ejpam-462	134	9	matrices	matrix	NOUN
ejpam-462	134	10	,	,	PUNCT
ejpam-462	134	11	yb	yb	PROPN
ejpam-462	134	12	and	and	CCONJ
ejpam-462	134	13	xb	xb	PROPN
ejpam-462	134	14	,	,	PUNCT
ejpam-462	134	15	re	re	VERB
ejpam-462	134	16	-	-	VERB
ejpam-462	134	17	estimate	estimate	VERB
ejpam-462	134	18	the	the	DET
ejpam-462	134	19	fgls	fgls	NOUN
ejpam-462	134	20	parameters	parameter	NOUN
ejpam-462	134	21	for	for	ADP
ejpam-462	134	22	both	both	CCONJ
ejpam-462	134	23	the	the	DET
ejpam-462	134	24	subset	subset	NOUN
ejpam-462	134	25	model	model	NOUN
ejpam-462	134	26	β̂sub	β̂sub	PROPN
ejpam-462	134	27	,	,	PUNCT
ejpam-462	134	28	b	b	NOUN
ejpam-462	134	29	,	,	PUNCT
ejpam-462	134	30	and	and	CCONJ
ejpam-462	134	31	the	the	DET
ejpam-462	134	32	saturated	saturated	ADJ
ejpam-462	134	33	model	model	NOUN
ejpam-462	134	34	β̂sat	β̂sat	PROPN
ejpam-462	134	35	,	,	PUNCT
ejpam-462	134	36	b.	b.	PROPN
ejpam-462	134	37	4	4	NUM
ejpam-462	134	38	.	.	PUNCT
ejpam-462	135	1	these	these	DET
ejpam-462	135	2	models	model	NOUN
ejpam-462	135	3	are	be	AUX
ejpam-462	135	4	then	then	ADV
ejpam-462	135	5	used	use	VERB
ejpam-462	135	6	to	to	PART
ejpam-462	135	7	compute	compute	VERB
ejpam-462	135	8	point	point	NOUN
ejpam-462	135	9	estimates	estimate	NOUN
ejpam-462	135	10	and	and	CCONJ
ejpam-462	135	11	forecast	forecast	NOUN
ejpam-462	135	12	errors	error	NOUN
ejpam-462	135	13	for	for	ADP
ejpam-462	135	14	the	the	DET
ejpam-462	135	15	outof	outof	PROPN
ejpam-462	135	16	-	-	PUNCT
ejpam-462	135	17	sample	sample	NOUN
ejpam-462	135	18	simulated	simulate	VERB
ejpam-462	135	19	datapoints	datapoint	NOUN
ejpam-462	135	20	:	:	PUNCT
ejpam-462	135	21	fsub	fsub	PROPN
ejpam-462	135	22	=	=	SYM
ejpam-462	135	23	yb	yb	PROPN
ejpam-462	135	24	−	−	PROPN
ejpam-462	136	1	β̂sub	β̂sub	PROPN
ejpam-462	136	2	,	,	PUNCT
ejpam-462	136	3	bxb	bxb	NOUN
ejpam-462	136	4	and	and	CCONJ
ejpam-462	136	5	fsat	fsat	VERB
ejpam-462	136	6	=	=	PUNCT
ejpam-462	136	7	yb	yb	PROPN
ejpam-462	136	8	−	−	PROPN
ejpam-462	136	9	β̂sat	β̂sat	PROPN
ejpam-462	136	10	,	,	PUNCT
ejpam-462	136	11	bxb	bxb	PROPN
ejpam-462	136	12	.	.	PUNCT
ejpam-462	137	1	for	for	ADP
ejpam-462	137	2	this	this	DET
ejpam-462	137	3	work	work	NOUN
ejpam-462	137	4	,	,	PUNCT
ejpam-462	137	5	we	we	PRON
ejpam-462	137	6	allowed	allow	VERB
ejpam-462	137	7	the	the	DET
ejpam-462	137	8	procedure	procedure	NOUN
ejpam-462	137	9	to	to	PART
ejpam-462	137	10	look	look	VERB
ejpam-462	137	11	ahead	ahead	ADV
ejpam-462	137	12	100	100	NUM
ejpam-462	137	13	periods	period	NOUN
ejpam-462	137	14	.	.	PUNCT
ejpam-462	138	1	a.	a.	NOUN
ejpam-462	138	2	howe	howe	PROPN
ejpam-462	138	3	and	and	CCONJ
ejpam-462	138	4	h.	h.	PROPN
ejpam-462	138	5	bozdogan	bozdogan	PROPN
ejpam-462	138	6	/	/	SYM
ejpam-462	138	7	eur	eur	PROPN
ejpam-462	138	8	.	.	PUNCT
ejpam-462	139	1	j.	j.	PROPN
ejpam-462	139	2	pure	pure	PROPN
ejpam-462	139	3	appl	appl	PROPN
ejpam-462	139	4	.	.	PROPN
ejpam-462	139	5	math	math	PROPN
ejpam-462	139	6	,	,	PUNCT
ejpam-462	139	7	3	3	NUM
ejpam-462	139	8	(	(	PUNCT
ejpam-462	139	9	2010	2010	NUM
ejpam-462	139	10	)	)	PUNCT
ejpam-462	139	11	,	,	PUNCT
ejpam-462	139	12	382	382	NUM
ejpam-462	139	13	-	-	SYM
ejpam-462	139	14	405	405	NUM
ejpam-462	139	15	388	388	NUM
ejpam-462	139	16	for	for	ADP
ejpam-462	139	17	our	our	PRON
ejpam-462	139	18	results	result	NOUN
ejpam-462	139	19	reported	report	VERB
ejpam-462	139	20	here	here	ADV
ejpam-462	139	21	,	,	PUNCT
ejpam-462	139	22	we	we	PRON
ejpam-462	139	23	used	use	VERB
ejpam-462	139	24	b	b	PROPN
ejpam-462	139	25	=	=	SYM
ejpam-462	139	26	2000	2000	NUM
ejpam-462	139	27	iterations	iteration	NOUN
ejpam-462	139	28	.	.	PUNCT
ejpam-462	140	1	utilizing	utilize	VERB
ejpam-462	140	2	all	all	DET
ejpam-462	140	3	bootstrapped	bootstrappe	VERB
ejpam-462	140	4	simulations	simulation	NOUN
ejpam-462	140	5	and	and	CCONJ
ejpam-462	140	6	for	for	ADP
ejpam-462	140	7	each	each	DET
ejpam-462	140	8	time	time	NOUN
ejpam-462	140	9	step	step	NOUN
ejpam-462	140	10	,	,	PUNCT
ejpam-462	140	11	two	two	NUM
ejpam-462	140	12	mean	mean	VERB
ejpam-462	140	13	squared	square	VERB
ejpam-462	140	14	errors	error	NOUN
ejpam-462	140	15	(	(	PUNCT
ejpam-462	140	16	mse	mse	NOUN
ejpam-462	140	17	)	)	PUNCT
ejpam-462	140	18	are	be	AUX
ejpam-462	140	19	computed	compute	VERB
ejpam-462	140	20	and	and	CCONJ
ejpam-462	140	21	stored	store	VERB
ejpam-462	140	22	one	one	NUM
ejpam-462	140	23	for	for	ADP
ejpam-462	140	24	the	the	DET
ejpam-462	140	25	subset	subset	NOUN
ejpam-462	140	26	var	var	PROPN
ejpam-462	140	27	model	model	NOUN
ejpam-462	140	28	,	,	PUNCT
ejpam-462	140	29	and	and	CCONJ
ejpam-462	140	30	the	the	DET
ejpam-462	140	31	other	other	ADJ
ejpam-462	140	32	for	for	ADP
ejpam-462	140	33	the	the	DET
ejpam-462	140	34	saturated	saturate	VERB
ejpam-462	140	35	model	model	NOUN
ejpam-462	140	36	.	.	PUNCT
ejpam-462	141	1	msesub	msesub	PROPN
ejpam-462	141	2	,	,	PUNCT
ejpam-462	141	3	i	i	PRON
ejpam-462	141	4	=	=	NOUN
ejpam-462	141	5	1	1	NUM
ejpam-462	141	6	b	b	PROPN
ejpam-462	141	7	b∑	b∑	PROPN
ejpam-462	141	8	b=1	b=1	PROPN
ejpam-462	141	9	yb	yb	PROPN
ejpam-462	141	10	,	,	PUNCT
ejpam-462	141	11	t+i	t+i	PROPN
ejpam-462	141	12	−	−	PROPN
ejpam-462	141	13	β̂sub	β̂sub	ADP
ejpam-462	141	14	,	,	PUNCT
ejpam-462	141	15	bx	bx	PROPN
ejpam-462	141	16	b	b	PROPN
ejpam-462	141	17	!	!	PUNCT
ejpam-462	141	18	,	,	PUNCT
ejpam-462	141	19	msesat	msesat	PROPN
ejpam-462	141	20	,	,	PUNCT
ejpam-462	141	21	i	i	PRON
ejpam-462	141	22	=	=	NOUN
ejpam-462	141	23	1	1	NUM
ejpam-462	141	24	b	b	PROPN
ejpam-462	141	25	b∑	b∑	PROPN
ejpam-462	141	26	b=1	b=1	PROPN
ejpam-462	141	27	yb	yb	PROPN
ejpam-462	141	28	,	,	PUNCT
ejpam-462	141	29	t+i	t+i	PROPN
ejpam-462	141	30	−	−	PROPN
ejpam-462	141	31	β̂sat	β̂sat	PROPN
ejpam-462	141	32	,	,	PUNCT
ejpam-462	141	33	bx	bx	PROPN
ejpam-462	141	34	b	b	PROPN
ejpam-462	141	35	!	!	PUNCT
ejpam-462	142	1	(	(	PUNCT
ejpam-462	142	2	9	9	NUM
ejpam-462	142	3	)	)	PUNCT
ejpam-462	142	4	with	with	ADP
ejpam-462	142	5	this	this	DET
ejpam-462	142	6	procedure	procedure	NOUN
ejpam-462	142	7	we	we	PRON
ejpam-462	142	8	obtain	obtain	VERB
ejpam-462	142	9	a	a	DET
ejpam-462	142	10	point	point	NOUN
ejpam-462	142	11	estimate	estimate	NOUN
ejpam-462	142	12	and	and	CCONJ
ejpam-462	142	13	a	a	DET
ejpam-462	142	14	variance	variance	NOUN
ejpam-462	142	15	estimate	estimate	NOUN
ejpam-462	142	16	for	for	ADP
ejpam-462	142	17	each	each	DET
ejpam-462	142	18	out	out	ADP
ejpam-462	142	19	-	-	PUNCT
ejpam-462	142	20	of	of	ADP
ejpam-462	142	21	-	-	PUNCT
ejpam-462	142	22	sample	sample	NOUN
ejpam-462	142	23	forecast	forecast	NOUN
ejpam-462	142	24	.	.	PUNCT
ejpam-462	143	1	this	this	PRON
ejpam-462	143	2	allows	allow	VERB
ejpam-462	143	3	us	we	PRON
ejpam-462	143	4	to	to	PART
ejpam-462	143	5	compare	compare	VERB
ejpam-462	143	6	the	the	DET
ejpam-462	143	7	precision	precision	NOUN
ejpam-462	143	8	with	with	ADP
ejpam-462	143	9	which	which	PRON
ejpam-462	143	10	models	model	NOUN
ejpam-462	143	11	make	make	VERB
ejpam-462	143	12	forecasts	forecast	NOUN
ejpam-462	143	13	;	;	PUNCT
ejpam-462	143	14	we	we	PRON
ejpam-462	143	15	can	can	AUX
ejpam-462	143	16	build	build	VERB
ejpam-462	143	17	error	error	NOUN
ejpam-462	143	18	bands	band	NOUN
ejpam-462	143	19	,	,	PUNCT
ejpam-462	143	20	such	such	ADJ
ejpam-462	143	21	as	as	ADP
ejpam-462	143	22	ŷt+i	ŷt+i	PROPN
ejpam-462	143	23	±	±	NOUN
ejpam-462	143	24	2σ̂t	2σ̂t	NUM
ejpam-462	143	25	,	,	PUNCT
ejpam-462	143	26	around	around	ADP
ejpam-462	143	27	the	the	DET
ejpam-462	143	28	point	point	NOUN
ejpam-462	143	29	estimates	estimate	NOUN
ejpam-462	143	30	.	.	PUNCT
ejpam-462	144	1	an	an	DET
ejpam-462	144	2	obvious	obvious	ADJ
ejpam-462	144	3	question	question	NOUN
ejpam-462	144	4	is	be	AUX
ejpam-462	144	5	why	why	SCONJ
ejpam-462	144	6	we	we	PRON
ejpam-462	144	7	should	should	AUX
ejpam-462	144	8	go	go	VERB
ejpam-462	144	9	through	through	ADP
ejpam-462	144	10	all	all	DET
ejpam-462	144	11	this	this	DET
ejpam-462	144	12	trouble	trouble	NOUN
ejpam-462	144	13	to	to	PART
ejpam-462	144	14	bootstrap	bootstrap	VERB
ejpam-462	144	15	from	from	ADP
ejpam-462	144	16	the	the	DET
ejpam-462	144	17	estimated	estimate	VERB
ejpam-462	144	18	residuals	residual	NOUN
ejpam-462	144	19	after	after	ADP
ejpam-462	144	20	fitting	fit	VERB
ejpam-462	144	21	the	the	DET
ejpam-462	144	22	var	var	NOUN
ejpam-462	144	23	model	model	NOUN
ejpam-462	144	24	.	.	PUNCT
ejpam-462	145	1	after	after	ADV
ejpam-462	145	2	all	all	ADV
ejpam-462	145	3	,	,	PUNCT
ejpam-462	145	4	as	as	ADV
ejpam-462	145	5	long	long	ADV
ejpam-462	145	6	as	as	SCONJ
ejpam-462	145	7	the	the	DET
ejpam-462	145	8	ols	ol	NOUN
ejpam-462	145	9	assumptions	assumption	NOUN
ejpam-462	145	10	are	be	AUX
ejpam-462	145	11	justified	justified	ADJ
ejpam-462	145	12	,	,	PUNCT
ejpam-462	145	13	it	it	PRON
ejpam-462	145	14	would	would	AUX
ejpam-462	145	15	be	be	AUX
ejpam-462	145	16	much	much	ADV
ejpam-462	145	17	simpler	simple	ADJ
ejpam-462	145	18	to	to	PART
ejpam-462	145	19	simulate	simulate	VERB
ejpam-462	145	20	error	error	NOUN
ejpam-462	145	21	terms	term	NOUN
ejpam-462	145	22	from	from	ADP
ejpam-462	145	23	a	a	DET
ejpam-462	145	24	multivariate	multivariate	NOUN
ejpam-462	145	25	gaussian	gaussian	ADJ
ejpam-462	145	26	distribution	distribution	NOUN
ejpam-462	145	27	with	with	ADP
ejpam-462	145	28	an	an	DET
ejpam-462	145	29	appropriate	appropriate	ADJ
ejpam-462	145	30	scatter	scatter	NOUN
ejpam-462	145	31	matrix	matrix	NOUN
ejpam-462	145	32	.	.	PUNCT
ejpam-462	146	1	however	however	ADV
ejpam-462	146	2	,	,	PUNCT
ejpam-462	146	3	when	when	SCONJ
ejpam-462	146	4	the	the	DET
ejpam-462	146	5	data	datum	NOUN
ejpam-462	146	6	exhibit	exhibit	VERB
ejpam-462	146	7	non	non	ADJ
ejpam-462	146	8	-	-	ADJ
ejpam-462	146	9	gaussian	gaussian	ADJ
ejpam-462	146	10	behavior	behavior	NOUN
ejpam-462	146	11	,	,	PUNCT
ejpam-462	146	12	from	from	ADP
ejpam-462	146	13	what	what	DET
ejpam-462	146	14	distribution	distribution	NOUN
ejpam-462	146	15	would	would	AUX
ejpam-462	146	16	we	we	PRON
ejpam-462	146	17	simulate	simulate	VERB
ejpam-462	146	18	?	?	PUNCT
ejpam-462	147	1	the	the	DET
ejpam-462	147	2	use	use	NOUN
ejpam-462	147	3	of	of	ADP
ejpam-462	147	4	this	this	DET
ejpam-462	147	5	method	method	NOUN
ejpam-462	147	6	is	be	AUX
ejpam-462	147	7	justified	justify	VERB
ejpam-462	147	8	on	on	ADP
ejpam-462	147	9	the	the	DET
ejpam-462	147	10	basis	basis	NOUN
ejpam-462	147	11	that	that	SCONJ
ejpam-462	147	12	it	it	PRON
ejpam-462	147	13	is	be	AUX
ejpam-462	147	14	more	more	ADV
ejpam-462	147	15	robust	robust	ADJ
ejpam-462	147	16	.	.	PUNCT
ejpam-462	148	1	3	3	X
ejpam-462	148	2	.	.	X
ejpam-462	148	3	genetic	genetic	ADJ
ejpam-462	148	4	algorithm	algorithm	NOUN
ejpam-462	148	5	(	(	PUNCT
ejpam-462	148	6	ga	ga	PROPN
ejpam-462	148	7	)	)	PUNCT
ejpam-462	148	8	there	there	PRON
ejpam-462	148	9	are	be	VERB
ejpam-462	148	10	many	many	ADJ
ejpam-462	148	11	search	search	NOUN
ejpam-462	148	12	algorithms	algorithm	NOUN
ejpam-462	148	13	that	that	PRON
ejpam-462	148	14	a	a	DET
ejpam-462	148	15	researcher	researcher	NOUN
ejpam-462	148	16	could	could	AUX
ejpam-462	148	17	apply	apply	VERB
ejpam-462	148	18	to	to	ADP
ejpam-462	148	19	a	a	DET
ejpam-462	148	20	subset	subset	ADJ
ejpam-462	148	21	model	model	NOUN
ejpam-462	148	22	selection	selection	NOUN
ejpam-462	148	23	problem	problem	NOUN
ejpam-462	148	24	such	such	ADJ
ejpam-462	148	25	as	as	ADP
ejpam-462	148	26	this	this	PRON
ejpam-462	148	27	.	.	PUNCT
ejpam-462	149	1	we	we	PRON
ejpam-462	149	2	could	could	AUX
ejpam-462	149	3	have	have	AUX
ejpam-462	149	4	chosen	choose	VERB
ejpam-462	149	5	to	to	PART
ejpam-462	149	6	use	use	VERB
ejpam-462	149	7	a	a	DET
ejpam-462	149	8	gradient	gradient	NOUN
ejpam-462	149	9	-	-	PUNCT
ejpam-462	149	10	based	base	VERB
ejpam-462	149	11	algorithm	algorithm	NOUN
ejpam-462	149	12	,	,	PUNCT
ejpam-462	149	13	such	such	ADJ
ejpam-462	149	14	as	as	ADP
ejpam-462	149	15	the	the	DET
ejpam-462	149	16	greedy	greedy	ADJ
ejpam-462	149	17	algorithm	algorithm	NOUN
ejpam-462	149	18	or	or	CCONJ
ejpam-462	149	19	a	a	DET
ejpam-462	149	20	modified	modified	ADJ
ejpam-462	149	21	newton	newton	PROPN
ejpam-462	149	22	method	method	NOUN
ejpam-462	149	23	.	.	PUNCT
ejpam-462	150	1	one	one	NUM
ejpam-462	150	2	shortcoming	shortcoming	NOUN
ejpam-462	150	3	of	of	ADP
ejpam-462	150	4	this	this	DET
ejpam-462	150	5	approach	approach	NOUN
ejpam-462	150	6	is	be	AUX
ejpam-462	150	7	that	that	SCONJ
ejpam-462	150	8	maximization	maximization	NOUN
ejpam-462	150	9	of	of	ADP
ejpam-462	150	10	the	the	DET
ejpam-462	150	11	likelihood	likelihood	NOUN
ejpam-462	150	12	does	do	AUX
ejpam-462	150	13	not	not	PART
ejpam-462	150	14	consider	consider	VERB
ejpam-462	150	15	model	model	NOUN
ejpam-462	150	16	complexity	complexity	NOUN
ejpam-462	150	17	,	,	PUNCT
ejpam-462	150	18	and	and	CCONJ
ejpam-462	150	19	will	will	AUX
ejpam-462	150	20	lead	lead	VERB
ejpam-462	150	21	to	to	ADP
ejpam-462	150	22	suboptimal	suboptimal	ADJ
ejpam-462	150	23	forecasts	forecast	NOUN
ejpam-462	150	24	when	when	SCONJ
ejpam-462	150	25	the	the	DET
ejpam-462	150	26	functional	functional	ADJ
ejpam-462	150	27	form	form	NOUN
ejpam-462	150	28	is	be	AUX
ejpam-462	150	29	misspecified	misspecifie	VERB
ejpam-462	150	30	.	.	PUNCT
ejpam-462	151	1	additionally	additionally	ADV
ejpam-462	151	2	,	,	PUNCT
ejpam-462	151	3	the	the	DET
ejpam-462	151	4	likelihood	likelihood	NOUN
ejpam-462	151	5	landscape	landscape	NOUN
ejpam-462	151	6	is	be	AUX
ejpam-462	151	7	very	very	ADV
ejpam-462	151	8	rugged	rugged	ADJ
ejpam-462	151	9	in	in	ADP
ejpam-462	151	10	the	the	DET
ejpam-462	151	11	high	high	ADJ
ejpam-462	151	12	dimensions	dimension	NOUN
ejpam-462	151	13	that	that	PRON
ejpam-462	151	14	characterize	characterize	VERB
ejpam-462	151	15	vector	vector	NOUN
ejpam-462	151	16	autoregressions	autoregression	NOUN
ejpam-462	151	17	.	.	PUNCT
ejpam-462	152	1	hill	hill	NOUN
ejpam-462	152	2	-	-	PUNCT
ejpam-462	152	3	climbing	climb	VERB
ejpam-462	152	4	algorithms	algorithm	NOUN
ejpam-462	152	5	have	have	VERB
ejpam-462	152	6	a	a	DET
ejpam-462	152	7	high	high	ADJ
ejpam-462	152	8	likelihood	likelihood	NOUN
ejpam-462	152	9	of	of	ADP
ejpam-462	152	10	getting	getting	AUX
ejpam-462	152	11	stuck	stick	VERB
ejpam-462	152	12	in	in	ADP
ejpam-462	152	13	local	local	ADJ
ejpam-462	152	14	optima	optima	NOUN
ejpam-462	152	15	.	.	PUNCT
ejpam-462	153	1	a	a	DET
ejpam-462	153	2	second	second	ADJ
ejpam-462	153	3	approach	approach	NOUN
ejpam-462	153	4	would	would	AUX
ejpam-462	153	5	be	be	AUX
ejpam-462	153	6	to	to	PART
ejpam-462	153	7	use	use	VERB
ejpam-462	153	8	simulated	simulated	ADJ
ejpam-462	153	9	annealing	annealing	NOUN
ejpam-462	153	10	.	.	PUNCT
ejpam-462	154	1	simulated	simulate	VERB
ejpam-462	154	2	annealing	anneal	VERB
ejpam-462	154	3	shares	share	NOUN
ejpam-462	154	4	the	the	DET
ejpam-462	154	5	complexity	complexity	NOUN
ejpam-462	154	6	short	short	ADJ
ejpam-462	154	7	-	-	PUNCT
ejpam-462	154	8	sightedness	sightedness	NOUN
ejpam-462	154	9	of	of	ADP
ejpam-462	154	10	other	other	ADJ
ejpam-462	154	11	methods	method	NOUN
ejpam-462	154	12	;	;	PUNCT
ejpam-462	154	13	in	in	ADP
ejpam-462	154	14	its	its	PRON
ejpam-462	154	15	defense	defense	NOUN
ejpam-462	154	16	,	,	PUNCT
ejpam-462	154	17	it	it	PRON
ejpam-462	154	18	is	be	AUX
ejpam-462	154	19	less	less	ADV
ejpam-462	154	20	likely	likely	ADJ
ejpam-462	154	21	to	to	PART
ejpam-462	154	22	get	get	AUX
ejpam-462	154	23	stuck	stick	VERB
ejpam-462	154	24	far	far	ADV
ejpam-462	154	25	away	away	ADV
ejpam-462	154	26	from	from	ADP
ejpam-462	154	27	the	the	DET
ejpam-462	154	28	global	global	ADJ
ejpam-462	154	29	optimum	optimum	NOUN
ejpam-462	154	30	.	.	PUNCT
ejpam-462	155	1	however	however	ADV
ejpam-462	155	2	,	,	PUNCT
ejpam-462	155	3	it	it	PRON
ejpam-462	155	4	requires	require	VERB
ejpam-462	155	5	several	several	ADJ
ejpam-462	155	6	subjective	subjective	ADJ
ejpam-462	155	7	decisions	decision	NOUN
ejpam-462	155	8	.	.	PUNCT
ejpam-462	156	1	if	if	SCONJ
ejpam-462	156	2	made	make	VERB
ejpam-462	156	3	poorly	poorly	ADV
ejpam-462	156	4	,	,	PUNCT
ejpam-462	156	5	these	these	DET
ejpam-462	156	6	decisions	decision	NOUN
ejpam-462	156	7	can	can	AUX
ejpam-462	156	8	doom	doom	VERB
ejpam-462	156	9	the	the	DET
ejpam-462	156	10	algorithm	algorithm	NOUN
ejpam-462	156	11	to	to	ADP
ejpam-462	156	12	failure	failure	NOUN
ejpam-462	156	13	.	.	PUNCT
ejpam-462	157	1	for	for	ADP
ejpam-462	157	2	example	example	NOUN
ejpam-462	157	3	,	,	PUNCT
ejpam-462	157	4	how	how	SCONJ
ejpam-462	157	5	are	be	AUX
ejpam-462	157	6	we	we	PRON
ejpam-462	157	7	to	to	PART
ejpam-462	157	8	decide	decide	VERB
ejpam-462	157	9	the	the	DET
ejpam-462	157	10	range	range	NOUN
ejpam-462	157	11	for	for	ADP
ejpam-462	157	12	the	the	DET
ejpam-462	157	13	temperature	temperature	NOUN
ejpam-462	157	14	parameter	parameter	NOUN
ejpam-462	157	15	,	,	PUNCT
ejpam-462	157	16	or	or	CCONJ
ejpam-462	157	17	the	the	DET
ejpam-462	157	18	cooling	cool	VERB
ejpam-462	157	19	schedule	schedule	NOUN
ejpam-462	157	20	?	?	PUNCT
ejpam-462	158	1	evolutionary	evolutionary	ADJ
ejpam-462	158	2	algorithms	algorithm	NOUN
ejpam-462	158	3	such	such	ADJ
ejpam-462	158	4	as	as	ADP
ejpam-462	158	5	the	the	DET
ejpam-462	158	6	ga	ga	PROPN
ejpam-462	158	7	,	,	PUNCT
ejpam-462	158	8	popularized	popularize	VERB
ejpam-462	158	9	by	by	ADP
ejpam-462	158	10	[	[	X
ejpam-462	158	11	10	10	NUM
ejpam-462	158	12	,	,	PUNCT
ejpam-462	158	13	11	11	NUM
ejpam-462	158	14	]	]	PUNCT
ejpam-462	158	15	,	,	PUNCT
ejpam-462	158	16	have	have	AUX
ejpam-462	158	17	become	become	VERB
ejpam-462	158	18	useful	useful	ADJ
ejpam-462	158	19	tools	tool	NOUN
ejpam-462	158	20	for	for	ADP
ejpam-462	158	21	complex	complex	ADJ
ejpam-462	158	22	statistical	statistical	ADJ
ejpam-462	158	23	modeling	modeling	NOUN
ejpam-462	158	24	,	,	PUNCT
ejpam-462	158	25	identifying	identify	VERB
ejpam-462	158	26	near	near	ADV
ejpam-462	158	27	-	-	PUNCT
ejpam-462	158	28	optimal	optimal	ADJ
ejpam-462	158	29	solutions	solution	NOUN
ejpam-462	158	30	while	while	SCONJ
ejpam-462	158	31	providing	provide	VERB
ejpam-462	158	32	computational	computational	ADJ
ejpam-462	158	33	efficiency	efficiency	NOUN
ejpam-462	158	34	.	.	PUNCT
ejpam-462	159	1	published	publish	VERB
ejpam-462	159	2	research	research	NOUN
ejpam-462	159	3	that	that	PRON
ejpam-462	159	4	has	have	AUX
ejpam-462	159	5	used	use	VERB
ejpam-462	159	6	the	the	DET
ejpam-462	159	7	ga	ga	PROPN
ejpam-462	159	8	for	for	ADP
ejpam-462	159	9	financial	financial	ADJ
ejpam-462	159	10	/	/	SYM
ejpam-462	159	11	econometric	econometric	ADJ
ejpam-462	159	12	modeling	modeling	NOUN
ejpam-462	159	13	include	include	VERB
ejpam-462	159	14	[	[	X
ejpam-462	159	15	17	17	NUM
ejpam-462	159	16	,	,	PUNCT
ejpam-462	159	17	20	20	NUM
ejpam-462	159	18	,	,	PUNCT
ejpam-462	159	19	26	26	NUM
ejpam-462	159	20	]	]	PUNCT
ejpam-462	159	21	.	.	PUNCT
ejpam-462	160	1	the	the	DET
ejpam-462	160	2	ga	ga	PROPN
ejpam-462	160	3	is	be	AUX
ejpam-462	160	4	a	a	DET
ejpam-462	160	5	search	search	NOUN
ejpam-462	160	6	algorithm	algorithm	NOUN
ejpam-462	160	7	that	that	PRON
ejpam-462	160	8	borrows	borrow	VERB
ejpam-462	160	9	concepts	concept	NOUN
ejpam-462	160	10	from	from	ADP
ejpam-462	160	11	biological	biological	ADJ
ejpam-462	160	12	evolution	evolution	NOUN
ejpam-462	160	13	.	.	PUNCT
ejpam-462	161	1	biological	biological	ADJ
ejpam-462	161	2	chromosomes	chromosome	NOUN
ejpam-462	161	3	,	,	PUNCT
ejpam-462	161	4	which	which	PRON
ejpam-462	161	5	determine	determine	VERB
ejpam-462	161	6	so	so	ADV
ejpam-462	161	7	much	much	ADJ
ejpam-462	161	8	about	about	ADP
ejpam-462	161	9	organisms	organism	NOUN
ejpam-462	161	10	,	,	PUNCT
ejpam-462	161	11	are	be	AUX
ejpam-462	161	12	represented	represent	VERB
ejpam-462	161	13	as	as	ADP
ejpam-462	161	14	binary	binary	ADJ
ejpam-462	161	15	words	word	NOUN
ejpam-462	161	16	–	–	PUNCT
ejpam-462	161	17	these	these	PRON
ejpam-462	161	18	determine	determine	VERB
ejpam-462	161	19	the	the	DET
ejpam-462	161	20	composition	composition	NOUN
ejpam-462	161	21	of	of	ADP
ejpam-462	161	22	possible	possible	ADJ
ejpam-462	161	23	solutions	solution	NOUN
ejpam-462	161	24	to	to	ADP
ejpam-462	161	25	an	an	DET
ejpam-462	161	26	optimization	optimization	NOUN
ejpam-462	161	27	problem	problem	NOUN
ejpam-462	161	28	.	.	PUNCT
ejpam-462	162	1	for	for	ADP
ejpam-462	162	2	multivariate	multivariate	NOUN
ejpam-462	162	3	regression	regression	NOUN
ejpam-462	162	4	subsetting	subsette	VERB
ejpam-462	162	5	,	,	PUNCT
ejpam-462	162	6	each	each	DET
ejpam-462	162	7	chromosome	chromosome	NOUN
ejpam-462	162	8	is	be	AUX
ejpam-462	162	9	a	a	DET
ejpam-462	162	10	q	q	ADJ
ejpam-462	162	11	-	-	PUNCT
ejpam-462	162	12	length	length	NOUN
ejpam-462	162	13	vector	vector	NOUN
ejpam-462	162	14	such	such	ADJ
ejpam-462	162	15	that	that	SCONJ
ejpam-462	162	16	each	each	DET
ejpam-462	162	17	locus	locus	NOUN
ejpam-462	162	18	represents	represent	VERB
ejpam-462	162	19	the	the	DET
ejpam-462	162	20	presence	presence	NOUN
ejpam-462	162	21	(	(	PUNCT
ejpam-462	162	22	1	1	NUM
ejpam-462	162	23	)	)	PUNCT
ejpam-462	162	24	or	or	CCONJ
ejpam-462	162	25	absence	absence	NOUN
ejpam-462	162	26	(	(	PUNCT
ejpam-462	162	27	0	0	NUM
ejpam-462	162	28	)	)	PUNCT
ejpam-462	162	29	of	of	ADP
ejpam-462	162	30	a	a	DET
ejpam-462	162	31	specific	specific	ADJ
ejpam-462	162	32	predictor	predictor	NOUN
ejpam-462	162	33	.	.	PUNCT
ejpam-462	163	1	an	an	DET
ejpam-462	163	2	example	example	NOUN
ejpam-462	163	3	chromosome	chromosome	NOUN
ejpam-462	163	4	may	may	AUX
ejpam-462	163	5	be	be	AUX
ejpam-462	163	6	[	[	X
ejpam-462	163	7	10011001	10011001	NUM
ejpam-462	163	8	]	]	PUNCT
ejpam-462	163	9	;	;	PUNCT
ejpam-462	163	10	in	in	ADP
ejpam-462	163	11	this	this	DET
ejpam-462	163	12	case	case	NOUN
ejpam-462	163	13	,	,	PUNCT
ejpam-462	163	14	predictors	predictor	NOUN
ejpam-462	163	15	1,4,5,8	1,4,5,8	PRON
ejpam-462	163	16	will	will	AUX
ejpam-462	163	17	be	be	AUX
ejpam-462	163	18	used	use	VERB
ejpam-462	163	19	for	for	ADP
ejpam-462	163	20	ols	ol	NOUN
ejpam-462	163	21	while	while	SCONJ
ejpam-462	163	22	2,3,6,7	2,3,6,7	NUM
ejpam-462	163	23	will	will	AUX
ejpam-462	163	24	not	not	PART
ejpam-462	163	25	.	.	PUNCT
ejpam-462	164	1	one	one	NUM
ejpam-462	164	2	argument	argument	NOUN
ejpam-462	164	3	leveled	level	VERB
ejpam-462	164	4	against	against	ADP
ejpam-462	164	5	the	the	DET
ejpam-462	164	6	ga	ga	PROPN
ejpam-462	164	7	is	be	AUX
ejpam-462	164	8	that	that	SCONJ
ejpam-462	164	9	there	there	PRON
ejpam-462	164	10	is	be	VERB
ejpam-462	164	11	no	no	DET
ejpam-462	164	12	artificial	artificial	ADJ
ejpam-462	164	13	constraint	constraint	NOUN
ejpam-462	164	14	to	to	PART
ejpam-462	164	15	prevent	prevent	VERB
ejpam-462	164	16	duplication	duplication	NOUN
ejpam-462	164	17	of	of	ADP
ejpam-462	164	18	solutions	solution	NOUN
ejpam-462	164	19	within	within	ADP
ejpam-462	164	20	or	or	CCONJ
ejpam-462	164	21	between	between	ADP
ejpam-462	164	22	iterations	iteration	NOUN
ejpam-462	164	23	.	.	PUNCT
ejpam-462	165	1	on	on	ADP
ejpam-462	165	2	the	the	DET
ejpam-462	165	3	surface	surface	NOUN
ejpam-462	165	4	,	,	PUNCT
ejpam-462	165	5	this	this	PRON
ejpam-462	165	6	seems	seem	VERB
ejpam-462	165	7	wasteful	wasteful	ADJ
ejpam-462	165	8	,	,	PUNCT
ejpam-462	165	9	but	but	CCONJ
ejpam-462	165	10	a	a	DET
ejpam-462	165	11	true	true	ADJ
ejpam-462	165	12	understanding	understanding	NOUN
ejpam-462	165	13	of	of	ADP
ejpam-462	165	14	the	the	DET
ejpam-462	165	15	ga	ga	PROPN
ejpam-462	165	16	reveals	reveal	VERB
ejpam-462	165	17	this	this	PRON
ejpam-462	165	18	as	as	ADP
ejpam-462	165	19	a	a	DET
ejpam-462	165	20	strength	strength	NOUN
ejpam-462	165	21	.	.	PUNCT
ejpam-462	166	1	this	this	PRON
ejpam-462	166	2	is	be	AUX
ejpam-462	166	3	due	due	ADJ
ejpam-462	166	4	to	to	ADP
ejpam-462	166	5	the	the	DET
ejpam-462	166	6	way	way	NOUN
ejpam-462	166	7	a.	a.	NOUN
ejpam-462	166	8	howe	howe	PROPN
ejpam-462	166	9	and	and	CCONJ
ejpam-462	166	10	h.	h.	PROPN
ejpam-462	166	11	bozdogan	bozdogan	PROPN
ejpam-462	166	12	/	/	SYM
ejpam-462	166	13	eur	eur	PROPN
ejpam-462	166	14	.	.	PUNCT
ejpam-462	167	1	j.	j.	PROPN
ejpam-462	167	2	pure	pure	PROPN
ejpam-462	167	3	appl	appl	PROPN
ejpam-462	167	4	.	.	PROPN
ejpam-462	167	5	math	math	PROPN
ejpam-462	167	6	,	,	PUNCT
ejpam-462	167	7	3	3	NUM
ejpam-462	167	8	(	(	PUNCT
ejpam-462	167	9	2010	2010	NUM
ejpam-462	167	10	)	)	PUNCT
ejpam-462	167	11	,	,	PUNCT
ejpam-462	167	12	382	382	NUM
ejpam-462	167	13	-	-	SYM
ejpam-462	167	14	405	405	NUM
ejpam-462	167	15	389	389	NUM
ejpam-462	167	16	in	in	ADP
ejpam-462	167	17	which	which	PRON
ejpam-462	167	18	solutions	solution	NOUN
ejpam-462	167	19	are	be	AUX
ejpam-462	167	20	considered	consider	VERB
ejpam-462	167	21	as	as	ADP
ejpam-462	167	22	an	an	DET
ejpam-462	167	23	ensemble	ensemble	ADJ
ejpam-462	167	24	,	,	PUNCT
ejpam-462	167	25	and	and	CCONJ
ejpam-462	167	26	not	not	PART
ejpam-462	167	27	individually	individually	ADV
ejpam-462	167	28	specifically	specifically	ADV
ejpam-462	167	29	because	because	SCONJ
ejpam-462	167	30	of	of	ADP
ejpam-462	167	31	the	the	DET
ejpam-462	167	32	crossover	crossover	NOUN
ejpam-462	167	33	operator	operator	NOUN
ejpam-462	167	34	.	.	PUNCT
ejpam-462	168	1	the	the	DET
ejpam-462	168	2	general	general	ADJ
ejpam-462	168	3	procedure	procedure	NOUN
ejpam-462	168	4	in	in	ADP
ejpam-462	168	5	the	the	DET
ejpam-462	168	6	ga	ga	PROPN
ejpam-462	168	7	is	be	AUX
ejpam-462	168	8	simple	simple	ADJ
ejpam-462	168	9	and	and	CCONJ
ejpam-462	168	10	straightforward	straightforward	ADJ
ejpam-462	168	11	,	,	PUNCT
ejpam-462	168	12	and	and	CCONJ
ejpam-462	168	13	is	be	AUX
ejpam-462	168	14	shown	show	VERB
ejpam-462	168	15	here	here	ADV
ejpam-462	168	16	.	.	PUNCT
ejpam-462	169	1	1	1	X
ejpam-462	169	2	.	.	X
ejpam-462	169	3	generate	generate	VERB
ejpam-462	169	4	initial	initial	ADJ
ejpam-462	169	5	population	population	NOUN
ejpam-462	169	6	of	of	ADP
ejpam-462	169	7	chromosomes	chromosome	NOUN
ejpam-462	169	8	2	2	NUM
ejpam-462	169	9	.	.	PUNCT
ejpam-462	169	10	score	score	VERB
ejpam-462	169	11	all	all	DET
ejpam-462	169	12	members	member	NOUN
ejpam-462	169	13	of	of	ADP
ejpam-462	169	14	current	current	ADJ
ejpam-462	169	15	population	population	NOUN
ejpam-462	169	16	3	3	X
ejpam-462	169	17	.	.	PUNCT
ejpam-462	169	18	determine	determine	VERB
ejpam-462	169	19	how	how	SCONJ
ejpam-462	169	20	current	current	ADJ
ejpam-462	169	21	population	population	NOUN
ejpam-462	169	22	is	be	AUX
ejpam-462	169	23	mated	mate	VERB
ejpam-462	169	24	and	and	CCONJ
ejpam-462	169	25	represented	represent	VERB
ejpam-462	169	26	in	in	ADP
ejpam-462	169	27	next	next	ADJ
ejpam-462	169	28	generation	generation	NOUN
ejpam-462	169	29	4	4	NUM
ejpam-462	169	30	.	.	PUNCT
ejpam-462	169	31	perform	perform	VERB
ejpam-462	169	32	chromosomal	chromosomal	ADJ
ejpam-462	169	33	crossover	crossover	NOUN
ejpam-462	169	34	and	and	CCONJ
ejpam-462	169	35	genetic	genetic	ADJ
ejpam-462	169	36	mutation	mutation	NOUN
ejpam-462	169	37	5	5	NUM
ejpam-462	169	38	.	.	PUNCT
ejpam-462	169	39	pass	pass	VERB
ejpam-462	169	40	on	on	ADP
ejpam-462	169	41	offspring	offspring	NOUN
ejpam-462	169	42	to	to	ADP
ejpam-462	169	43	new	new	ADJ
ejpam-462	169	44	generation	generation	NOUN
ejpam-462	169	45	6	6	NUM
ejpam-462	169	46	.	.	X
ejpam-462	169	47	loop	loop	VERB
ejpam-462	169	48	back	back	ADV
ejpam-462	169	49	to	to	ADP
ejpam-462	169	50	2	2	NUM
ejpam-462	169	51	until	until	SCONJ
ejpam-462	169	52	termination	termination	NOUN
ejpam-462	169	53	criteria	criterion	NOUN
ejpam-462	169	54	mettable	mettable	VERB
ejpam-462	169	55	2	2	NUM
ejpam-462	169	56	:	:	PUNCT
ejpam-462	169	57	geneti	geneti	ADJ
ejpam-462	169	58	algorithm	algorithm	NOUN
ejpam-462	169	59	parameters	parameter	NOUN
ejpam-462	169	60	used	use	VERB
ejpam-462	169	61	in	in	ADP
ejpam-462	169	62	appli	appli	PROPN
ejpam-462	169	63	ation	ation	PROPN
ejpam-462	169	64	example	example	PROPN
ejpam-462	169	65	.	.	PUNCT
ejpam-462	170	1	parameter	parameter	NOUN
ejpam-462	170	2	setting	set	VERB
ejpam-462	170	3	number	number	NOUN
ejpam-462	170	4	of	of	ADP
ejpam-462	170	5	generations	generation	NOUN
ejpam-462	170	6	100	100	NUM
ejpam-462	170	7	population	population	NOUN
ejpam-462	170	8	size	size	NOUN
ejpam-462	170	9	100	100	NUM
ejpam-462	170	10	generation	generation	NOUN
ejpam-462	170	11	seeding	seed	VERB
ejpam-462	170	12	relative	relative	ADJ
ejpam-462	170	13	ranking	ranking	NOUN
ejpam-462	170	14	crossover	crossover	NOUN
ejpam-462	170	15	probability	probability	NOUN
ejpam-462	170	16	0.75	0.75	NUM
ejpam-462	170	17	mutation	mutation	NOUN
ejpam-462	170	18	probability	probability	NOUN
ejpam-462	170	19	0.25	0.25	NUM
ejpam-462	170	20	objective	objective	ADJ
ejpam-462	170	21	function	function	NOUN
ejpam-462	170	22	icom	icom	PROPN
ejpam-462	171	1	pm	pm	PROPN
ejpam-462	171	2	isp_peu(f̂	isp_peu(f̂	PROPN
ejpam-462	171	3	−1	−1	NOUN
ejpam-462	171	4	)	)	PUNCT
ejpam-462	171	5	as	as	SCONJ
ejpam-462	171	6	seen	see	VERB
ejpam-462	171	7	in	in	ADP
ejpam-462	171	8	table	table	NOUN
ejpam-462	171	9	2	2	NUM
ejpam-462	171	10	,	,	PUNCT
ejpam-462	171	11	there	there	PRON
ejpam-462	171	12	are	be	VERB
ejpam-462	171	13	eight	eight	NUM
ejpam-462	171	14	major	major	ADJ
ejpam-462	171	15	parameters	parameter	NOUN
ejpam-462	171	16	used	use	VERB
ejpam-462	171	17	to	to	PART
ejpam-462	171	18	define	define	VERB
ejpam-462	171	19	the	the	DET
ejpam-462	171	20	operation	operation	NOUN
ejpam-462	171	21	of	of	ADP
ejpam-462	171	22	the	the	DET
ejpam-462	171	23	genetic	genetic	ADJ
ejpam-462	171	24	algorithm	algorithm	NOUN
ejpam-462	171	25	.	.	PUNCT
ejpam-462	172	1	since	since	SCONJ
ejpam-462	172	2	the	the	DET
ejpam-462	172	3	ga	ga	PROPN
ejpam-462	172	4	has	have	AUX
ejpam-462	172	5	become	become	VERB
ejpam-462	172	6	a	a	DET
ejpam-462	172	7	fairly	fairly	ADV
ejpam-462	172	8	well	well	ADV
ejpam-462	172	9	-	-	PUNCT
ejpam-462	172	10	known	know	VERB
ejpam-462	172	11	search	search	NOUN
ejpam-462	172	12	algorithm	algorithm	NOUN
ejpam-462	172	13	,	,	PUNCT
ejpam-462	172	14	we	we	PRON
ejpam-462	172	15	direct	direct	VERB
ejpam-462	172	16	interested	interested	ADJ
ejpam-462	172	17	readers	reader	NOUN
ejpam-462	172	18	to	to	ADP
ejpam-462	172	19	many	many	ADJ
ejpam-462	172	20	excellen	excellen	ADJ
ejpam-462	172	21	sources	source	NOUN
ejpam-462	172	22	for	for	ADP
ejpam-462	172	23	further	further	ADJ
ejpam-462	172	24	details	detail	NOUN
ejpam-462	172	25	.	.	PUNCT
ejpam-462	173	1	4	4	X
ejpam-462	173	2	.	.	X
ejpam-462	173	3	information	information	NOUN
ejpam-462	173	4	criteria	criterion	NOUN
ejpam-462	173	5	and	and	CCONJ
ejpam-462	173	6	complexity	complexity	NOUN
ejpam-462	173	7	introduced	introduce	VERB
ejpam-462	173	8	by	by	ADP
ejpam-462	173	9	[	[	X
ejpam-462	173	10	5	5	NUM
ejpam-462	173	11	]	]	PUNCT
ejpam-462	173	12	,	,	PUNCT
ejpam-462	173	13	icom	icom	PROPN
ejpam-462	173	14	p	p	PROPN
ejpam-462	173	15	is	be	AUX
ejpam-462	173	16	a	a	DET
ejpam-462	173	17	logical	logical	ADJ
ejpam-462	173	18	extension	extension	NOUN
ejpam-462	173	19	of	of	ADP
ejpam-462	173	20	akaike	akaike	ADJ
ejpam-462	173	21	’s	’s	ADV
ejpam-462	173	22	aic	aic	PROPN
ejpam-462	174	1	[	[	X
ejpam-462	174	2	1	1	NUM
ejpam-462	174	3	]	]	PUNCT
ejpam-462	174	4	.	.	PUNCT
ejpam-462	175	1	aic	aic	PROPN
ejpam-462	175	2	scores	score	VERB
ejpam-462	175	3	a	a	DET
ejpam-462	175	4	model	model	NOUN
ejpam-462	175	5	by	by	ADP
ejpam-462	175	6	penalizing	penalize	VERB
ejpam-462	175	7	a	a	DET
ejpam-462	175	8	bad	bad	ADJ
ejpam-462	175	9	fit	fit	NOUN
ejpam-462	175	10	with	with	ADP
ejpam-462	175	11	twice	twice	DET
ejpam-462	175	12	the	the	DET
ejpam-462	175	13	negative	negative	ADJ
ejpam-462	175	14	log	log	NOUN
ejpam-462	175	15	-	-	PUNCT
ejpam-462	175	16	likelihood	likelihood	NOUN
ejpam-462	175	17	,	,	PUNCT
ejpam-462	175	18	and	and	CCONJ
ejpam-462	175	19	model	model	NOUN
ejpam-462	175	20	complexity	complexity	NOUN
ejpam-462	175	21	with	with	ADP
ejpam-462	175	22	twice	twice	DET
ejpam-462	175	23	the	the	DET
ejpam-462	175	24	number	number	NOUN
ejpam-462	175	25	of	of	ADP
ejpam-462	175	26	parameters	parameter	NOUN
ejpam-462	175	27	estimated	estimate	VERB
ejpam-462	175	28	.	.	PUNCT
ejpam-462	176	1	for	for	ADP
ejpam-462	176	2	multivariate	multivariate	NOUN
ejpam-462	176	3	gaussian	gaussian	ADJ
ejpam-462	176	4	errors	error	NOUN
ejpam-462	176	5	,	,	PUNCT
ejpam-462	176	6	aic	aic	PROPN
ejpam-462	176	7	=	=	PROPN
ejpam-462	176	8	np	np	INTJ
ejpam-462	176	9	log	log	NOUN
ejpam-462	176	10	(	(	PUNCT
ejpam-462	176	11	2π)+	2π)+	NOUN
ejpam-462	176	12	n	n	NOUN
ejpam-462	176	13	log	log	VERB
ejpam-462	176	14	|σ̂|+	|σ̂|+	PROPN
ejpam-462	176	15	np+	np+	PROPN
ejpam-462	176	16	2	2	NUM
ejpam-462	176	17	m	m	NOUN
ejpam-462	176	18	,	,	PUNCT
ejpam-462	176	19	where	where	SCONJ
ejpam-462	176	20	(	(	PUNCT
ejpam-462	176	21	10	10	NUM
ejpam-462	176	22	)	)	PUNCT
ejpam-462	176	23	m	m	PROPN
ejpam-462	176	24	=	=	PUNCT
ejpam-462	176	25	�	�	PROPN
ejpam-462	176	26	p	p	NOUN
ejpam-462	176	27	(	(	PUNCT
ejpam-462	176	28	k+	k+	PROPN
ejpam-462	176	29	1)+	1)+	NUM
ejpam-462	176	30	p	p	PROPN
ejpam-462	176	31	�	�	PROPN
ejpam-462	176	32	p+	p+	PART
ejpam-462	176	33	1	1	NUM
ejpam-462	176	34	�	�	PROPN
ejpam-462	176	35	2	2	NUM
ejpam-462	176	36	�	�	PROPN
ejpam-462	176	37	.	.	PUNCT
ejpam-462	177	1	for	for	ADP
ejpam-462	177	2	m	m	PRON
ejpam-462	177	3	,	,	PUNCT
ejpam-462	177	4	the	the	DET
ejpam-462	177	5	first	first	ADJ
ejpam-462	177	6	term	term	NOUN
ejpam-462	177	7	is	be	AUX
ejpam-462	177	8	the	the	DET
ejpam-462	177	9	number	number	NOUN
ejpam-462	177	10	of	of	ADP
ejpam-462	177	11	unrestricted	unrestricted	ADJ
ejpam-462	177	12	var	var	NOUN
ejpam-462	177	13	components	component	NOUN
ejpam-462	177	14	in	in	ADP
ejpam-462	177	15	the	the	DET
ejpam-462	177	16	model	model	NOUN
ejpam-462	177	17	;	;	PUNCT
ejpam-462	177	18	the	the	DET
ejpam-462	177	19	second	second	NOUN
ejpam-462	177	20	is	be	AUX
ejpam-462	177	21	the	the	DET
ejpam-462	177	22	number	number	NOUN
ejpam-462	177	23	of	of	ADP
ejpam-462	177	24	variances	variance	NOUN
ejpam-462	177	25	and	and	CCONJ
ejpam-462	177	26	covariances	covariance	NOUN
ejpam-462	177	27	.	.	PUNCT
ejpam-462	178	1	schwartz	schwartz	PROPN
ejpam-462	178	2	’s	’s	PART
ejpam-462	178	3	bayesian	bayesian	NOUN
ejpam-462	178	4	criteria	criterion	NOUN
ejpam-462	178	5	(	(	PUNCT
ejpam-462	178	6	sbc	sbc	NOUN
ejpam-462	178	7	or	or	CCONJ
ejpam-462	178	8	bic	bic	NOUN
ejpam-462	178	9	)	)	PUNCT
ejpam-462	178	10	enforces	enforce	VERB
ejpam-462	178	11	a	a	DET
ejpam-462	178	12	similar	similar	ADJ
ejpam-462	178	13	penalty	penalty	NOUN
ejpam-462	178	14	,	,	PUNCT
ejpam-462	178	15	scaling	scale	VERB
ejpam-462	178	16	the	the	DET
ejpam-462	178	17	number	number	NOUN
ejpam-462	178	18	of	of	ADP
ejpam-462	178	19	parameters	parameter	NOUN
ejpam-462	178	20	with	with	ADP
ejpam-462	178	21	log	log	NOUN
ejpam-462	178	22	n.	n.	NOUN
ejpam-462	178	23	penalizing	penalize	VERB
ejpam-462	178	24	model	model	NOUN
ejpam-462	178	25	complexity	complexity	NOUN
ejpam-462	178	26	with	with	ADP
ejpam-462	178	27	no	no	DET
ejpam-462	178	28	more	more	ADJ
ejpam-462	178	29	information	information	NOUN
ejpam-462	178	30	than	than	SCONJ
ejpam-462	178	31	the	the	DET
ejpam-462	178	32	number	number	NOUN
ejpam-462	178	33	of	of	ADP
ejpam-462	178	34	parameters	parameter	NOUN
ejpam-462	178	35	can	can	AUX
ejpam-462	178	36	be	be	AUX
ejpam-462	178	37	compared	compare	VERB
ejpam-462	178	38	to	to	ADP
ejpam-462	178	39	the	the	DET
ejpam-462	178	40	proverbial	proverbial	ADJ
ejpam-462	178	41	blind	blind	ADJ
ejpam-462	178	42	man	man	NOUN
ejpam-462	178	43	trying	try	VERB
ejpam-462	178	44	to	to	PART
ejpam-462	178	45	identify	identify	VERB
ejpam-462	178	46	an	an	DET
ejpam-462	178	47	elephant	elephant	NOUN
ejpam-462	178	48	by	by	ADP
ejpam-462	178	49	only	only	ADV
ejpam-462	178	50	feeling	feel	VERB
ejpam-462	178	51	it	it	PRON
ejpam-462	178	52	’s	’	VERB
ejpam-462	178	53	legs	leg	NOUN
ejpam-462	178	54	.	.	PUNCT
ejpam-462	179	1	this	this	PRON
ejpam-462	179	2	is	be	AUX
ejpam-462	179	3	just	just	ADV
ejpam-462	179	4	not	not	PART
ejpam-462	179	5	enough	enough	ADJ
ejpam-462	179	6	information	information	NOUN
ejpam-462	179	7	to	to	PART
ejpam-462	179	8	measure	measure	VERB
ejpam-462	179	9	the	the	DET
ejpam-462	179	10	information	information	NOUN
ejpam-462	179	11	in	in	ADP
ejpam-462	179	12	a	a	DET
ejpam-462	179	13	model	model	NOUN
ejpam-462	179	14	.	.	PUNCT
ejpam-462	180	1	for	for	ADP
ejpam-462	180	2	the	the	DET
ejpam-462	180	3	same	same	ADJ
ejpam-462	180	4	dataset	dataset	NOUN
ejpam-462	180	5	,	,	PUNCT
ejpam-462	180	6	neither	neither	CCONJ
ejpam-462	180	7	aic	aic	PROPN
ejpam-462	180	8	nor	nor	CCONJ
ejpam-462	180	9	sbc	sbc	NOUN
ejpam-462	180	10	will	will	AUX
ejpam-462	180	11	be	be	AUX
ejpam-462	180	12	able	able	ADJ
ejpam-462	180	13	to	to	PART
ejpam-462	180	14	distinguish	distinguish	VERB
ejpam-462	180	15	between	between	ADP
ejpam-462	180	16	two	two	NUM
ejpam-462	180	17	models	model	NOUN
ejpam-462	180	18	with	with	ADP
ejpam-462	180	19	a	a	DET
ejpam-462	180	20	similar	similar	ADJ
ejpam-462	180	21	fit	fit	NOUN
ejpam-462	180	22	and	and	CCONJ
ejpam-462	180	23	size	size	NOUN
ejpam-462	180	24	,	,	PUNCT
ejpam-462	180	25	but	but	CCONJ
ejpam-462	180	26	different	different	ADJ
ejpam-462	180	27	structures	structure	NOUN
ejpam-462	180	28	.	.	PUNCT
ejpam-462	181	1	thus	thus	ADV
ejpam-462	181	2	,	,	PUNCT
ejpam-462	181	3	we	we	PRON
ejpam-462	181	4	use	use	VERB
ejpam-462	181	5	a	a	DET
ejpam-462	181	6	form	form	NOUN
ejpam-462	181	7	of	of	ADP
ejpam-462	181	8	icom	icom	PROPN
ejpam-462	181	9	p	p	PROPN
ejpam-462	181	10	which	which	PRON
ejpam-462	181	11	penalizes	penalize	VERB
ejpam-462	181	12	model	model	NOUN
ejpam-462	181	13	complexity	complexity	NOUN
ejpam-462	181	14	with	with	ADP
ejpam-462	181	15	a	a	DET
ejpam-462	181	16	more	more	ADV
ejpam-462	181	17	judicious	judicious	ADJ
ejpam-462	181	18	penalty	penalty	NOUN
ejpam-462	181	19	term	term	NOUN
ejpam-462	181	20	.	.	PUNCT
ejpam-462	182	1	a.	a.	NOUN
ejpam-462	182	2	howe	howe	PROPN
ejpam-462	182	3	and	and	CCONJ
ejpam-462	182	4	h.	h.	PROPN
ejpam-462	182	5	bozdogan	bozdogan	PROPN
ejpam-462	182	6	/	/	SYM
ejpam-462	182	7	eur	eur	PROPN
ejpam-462	182	8	.	.	PUNCT
ejpam-462	183	1	j.	j.	PROPN
ejpam-462	183	2	pure	pure	PROPN
ejpam-462	183	3	appl	appl	PROPN
ejpam-462	183	4	.	.	PROPN
ejpam-462	183	5	math	math	PROPN
ejpam-462	183	6	,	,	PUNCT
ejpam-462	183	7	3	3	NUM
ejpam-462	183	8	(	(	PUNCT
ejpam-462	183	9	2010	2010	NUM
ejpam-462	183	10	)	)	PUNCT
ejpam-462	183	11	,	,	PUNCT
ejpam-462	183	12	382	382	NUM
ejpam-462	183	13	-	-	SYM
ejpam-462	183	14	405	405	NUM
ejpam-462	183	15	390	390	NUM
ejpam-462	183	16	icom	icom	PROPN
ejpam-462	183	17	p(f̂−1	p(f̂−1	PROPN
ejpam-462	183	18	)	)	PUNCT
ejpam-462	183	19	utilizes	utilize	VERB
ejpam-462	183	20	the	the	DET
ejpam-462	183	21	information	information	NOUN
ejpam-462	183	22	in	in	ADP
ejpam-462	183	23	the	the	DET
ejpam-462	183	24	first	first	ADJ
ejpam-462	183	25	order	order	NOUN
ejpam-462	183	26	maximal	maximal	ADJ
ejpam-462	183	27	entropic	entropic	ADJ
ejpam-462	183	28	complexity	complexity	NOUN
ejpam-462	183	29	of	of	ADP
ejpam-462	183	30	the	the	DET
ejpam-462	183	31	estimated	estimate	VERB
ejpam-462	183	32	inverse	inverse	NOUN
ejpam-462	183	33	fisher	fisher	PROPN
ejpam-462	183	34	information	information	NOUN
ejpam-462	183	35	matrix	matrix	NOUN
ejpam-462	183	36	(	(	PUNCT
ejpam-462	183	37	ifim	ifim	NOUN
ejpam-462	183	38	)	)	PUNCT
ejpam-462	183	39	.	.	PUNCT
ejpam-462	184	1	because	because	SCONJ
ejpam-462	184	2	of	of	ADP
ejpam-462	184	3	this	this	DET
ejpam-462	184	4	more	more	ADV
ejpam-462	184	5	intelligent	intelligent	ADJ
ejpam-462	184	6	penalty	penalty	NOUN
ejpam-462	184	7	,	,	PUNCT
ejpam-462	184	8	the	the	DET
ejpam-462	184	9	number	number	NOUN
ejpam-462	184	10	of	of	ADP
ejpam-462	184	11	variables	variable	NOUN
ejpam-462	184	12	,	,	PUNCT
ejpam-462	184	13	their	their	PRON
ejpam-462	184	14	different	different	ADJ
ejpam-462	184	15	structures	structure	NOUN
ejpam-462	184	16	,	,	PUNCT
ejpam-462	184	17	and	and	CCONJ
ejpam-462	184	18	their	their	PRON
ejpam-462	184	19	interrelationships	interrelationship	NOUN
ejpam-462	184	20	are	be	AUX
ejpam-462	184	21	all	all	PRON
ejpam-462	184	22	simultaneously	simultaneously	ADV
ejpam-462	184	23	taken	take	VERB
ejpam-462	184	24	into	into	ADP
ejpam-462	184	25	consideration	consideration	NOUN
ejpam-462	184	26	.	.	PUNCT
ejpam-462	185	1	in	in	ADP
ejpam-462	185	2	a	a	DET
ejpam-462	185	3	world	world	NOUN
ejpam-462	185	4	title	title	NOUN
ejpam-462	185	5	award	award	NOUN
ejpam-462	185	6	winning	win	VERB
ejpam-462	185	7	paper	paper	NOUN
ejpam-462	185	8	,	,	PUNCT
ejpam-462	185	9	[	[	X
ejpam-462	185	10	4	4	X
ejpam-462	185	11	]	]	PUNCT
ejpam-462	185	12	demonstrated	demonstrate	VERB
ejpam-462	185	13	the	the	DET
ejpam-462	185	14	value	value	NOUN
ejpam-462	185	15	of	of	ADP
ejpam-462	185	16	icom	icom	PROPN
ejpam-462	185	17	p	p	PROPN
ejpam-462	185	18	and	and	CCONJ
ejpam-462	185	19	information	information	NOUN
ejpam-462	185	20	theoretic	theoretic	NOUN
ejpam-462	185	21	techniques	technique	NOUN
ejpam-462	185	22	to	to	PART
ejpam-462	185	23	select	select	VERB
ejpam-462	185	24	autoregressive	autoregressive	ADJ
ejpam-462	185	25	distributed	distribute	VERB
ejpam-462	185	26	lag	lag	NOUN
ejpam-462	185	27	models	model	NOUN
ejpam-462	185	28	for	for	ADP
ejpam-462	185	29	forecasting	forecast	VERB
ejpam-462	185	30	food	food	NOUN
ejpam-462	185	31	consumption	consumption	NOUN
ejpam-462	185	32	in	in	ADP
ejpam-462	185	33	the	the	DET
ejpam-462	185	34	netherlands	netherlands	PROPN
ejpam-462	185	35	.	.	PUNCT
ejpam-462	186	1	the	the	DET
ejpam-462	186	2	simplest	simple	ADJ
ejpam-462	186	3	form	form	NOUN
ejpam-462	186	4	of	of	ADP
ejpam-462	186	5	icom	icom	PROPN
ejpam-462	186	6	p	p	PROPN
ejpam-462	186	7	that	that	PRON
ejpam-462	186	8	uses	use	VERB
ejpam-462	186	9	this	this	DET
ejpam-462	186	10	penalty	penalty	NOUN
ejpam-462	186	11	function	function	NOUN
ejpam-462	186	12	is	be	AUX
ejpam-462	186	13	shown	show	VERB
ejpam-462	186	14	in	in	ADP
ejpam-462	186	15	(	(	PUNCT
ejpam-462	186	16	11	11	NUM
ejpam-462	186	17	)	)	PUNCT
ejpam-462	186	18	.	.	PUNCT
ejpam-462	187	1	icom	icom	PROPN
ejpam-462	187	2	p(f̂−1	p(f̂−1	PROPN
ejpam-462	187	3	)	)	PUNCT
ejpam-462	187	4	=	=	NOUN
ejpam-462	187	5	np	np	PRON
ejpam-462	187	6	log	log	NOUN
ejpam-462	187	7	(	(	PUNCT
ejpam-462	187	8	2π)+	2π)+	NOUN
ejpam-462	187	9	n	n	NOUN
ejpam-462	187	10	log	log	VERB
ejpam-462	187	11	|σ̂|+	|σ̂|+	PROPN
ejpam-462	187	12	np+	np+	PROPN
ejpam-462	187	13	2c1(f̂	2c1(f̂	NUM
ejpam-462	187	14	−1	−1	NOUN
ejpam-462	187	15	)	)	PUNCT
ejpam-462	187	16	(	(	PUNCT
ejpam-462	187	17	11	11	X
ejpam-462	187	18	)	)	PUNCT
ejpam-462	187	19	modeling	modeling	NOUN
ejpam-462	187	20	procedures	procedure	NOUN
ejpam-462	187	21	like	like	ADP
ejpam-462	187	22	this	this	PRON
ejpam-462	187	23	have	have	VERB
ejpam-462	187	24	high	high	ADJ
ejpam-462	187	25	potential	potential	NOUN
ejpam-462	187	26	for	for	ADP
ejpam-462	187	27	overparameterization	overparameterization	NOUN
ejpam-462	187	28	and	and	CCONJ
ejpam-462	187	29	bias	bias	NOUN
ejpam-462	187	30	;	;	PUNCT
ejpam-462	187	31	a	a	DET
ejpam-462	187	32	useful	useful	ADJ
ejpam-462	187	33	form	form	NOUN
ejpam-462	187	34	of	of	ADP
ejpam-462	187	35	icom	icom	PROPN
ejpam-462	187	36	p	p	PROPN
ejpam-462	187	37	which	which	PRON
ejpam-462	187	38	uses	use	VERB
ejpam-462	187	39	a	a	DET
ejpam-462	187	40	stricter	strict	ADJ
ejpam-462	187	41	penalty	penalty	NOUN
ejpam-462	187	42	,	,	PUNCT
ejpam-462	187	43	icom	icom	PROPN
ejpam-462	187	44	pm	pm	PROPN
ejpam-462	187	45	isp_peu(f̂	isp_peu(f̂	PROPN
ejpam-462	187	46	−1	−1	NOUN
ejpam-462	187	47	)	)	PUNCT
ejpam-462	188	1	=	=	NOUN
ejpam-462	188	2	np	np	INTJ
ejpam-462	188	3	log	log	NOUN
ejpam-462	188	4	(	(	PUNCT
ejpam-462	188	5	2π)+	2π)+	NOUN
ejpam-462	188	6	n	n	NOUN
ejpam-462	188	7	log	log	VERB
ejpam-462	188	8	|σ̂|+	|σ̂|+	PROPN
ejpam-462	188	9	np+m+	np+m+	PROPN
ejpam-462	188	10	2b+	2b+	NUM
ejpam-462	188	11	2c1(f̂	2c1(f̂	NUM
ejpam-462	188	12	−1	−1	NOUN
ejpam-462	188	13	)	)	PUNCT
ejpam-462	188	14	,	,	PUNCT
ejpam-462	188	15	(	(	PUNCT
ejpam-462	188	16	12	12	NUM
ejpam-462	188	17	)	)	PUNCT
ejpam-462	188	18	was	be	AUX
ejpam-462	188	19	developed	develop	VERB
ejpam-462	188	20	by	by	ADP
ejpam-462	188	21	[	[	X
ejpam-462	188	22	6	6	NUM
ejpam-462	188	23	]	]	PUNCT
ejpam-462	188	24	as	as	ADP
ejpam-462	188	25	a	a	DET
ejpam-462	188	26	bayesian	bayesian	NOUN
ejpam-462	188	27	criterion	criterion	NOUN
ejpam-462	188	28	for	for	ADP
ejpam-462	188	29	maximizing	maximize	VERB
ejpam-462	188	30	a	a	DET
ejpam-462	188	31	posterior	posterior	ADJ
ejpam-462	188	32	expected	expect	VERB
ejpam-462	188	33	utility	utility	NOUN
ejpam-462	188	34	.	.	PUNCT
ejpam-462	189	1	the	the	DET
ejpam-462	189	2	misp_peu	misp_peu	PROPN
ejpam-462	189	3	indicates	indicate	VERB
ejpam-462	189	4	that	that	SCONJ
ejpam-462	189	5	this	this	DET
ejpam-462	189	6	criterion	criterion	NOUN
ejpam-462	189	7	is	be	AUX
ejpam-462	189	8	misspecification	misspecification	NOUN
ejpam-462	189	9	-	-	PUNCT
ejpam-462	189	10	resistant	resistant	ADJ
ejpam-462	189	11	,	,	PUNCT
ejpam-462	189	12	and	and	CCONJ
ejpam-462	189	13	its	its	PRON
ejpam-462	189	14	relationship	relationship	NOUN
ejpam-462	189	15	to	to	ADP
ejpam-462	189	16	the	the	DET
ejpam-462	189	17	posterior	posterior	ADJ
ejpam-462	189	18	expected	expect	VERB
ejpam-462	189	19	utility	utility	NOUN
ejpam-462	189	20	(	(	PUNCT
ejpam-462	189	21	more	more	ADJ
ejpam-462	189	22	on	on	ADP
ejpam-462	189	23	the	the	DET
ejpam-462	189	24	misspecification	misspecification	NOUN
ejpam-462	189	25	robustness	robustness	NOUN
ejpam-462	189	26	soon	soon	ADV
ejpam-462	189	27	)	)	PUNCT
ejpam-462	189	28	.	.	PUNCT
ejpam-462	190	1	for	for	ADP
ejpam-462	190	2	the	the	DET
ejpam-462	190	3	feasible	feasible	ADJ
ejpam-462	190	4	generalized	generalized	ADJ
ejpam-462	190	5	least	least	ADJ
ejpam-462	190	6	squares	square	NOUN
ejpam-462	190	7	estimates	estimate	NOUN
ejpam-462	190	8	,	,	PUNCT
ejpam-462	190	9	f̂−1	f̂−1	PROPN
ejpam-462	190	10	is	be	AUX
ejpam-462	190	11	shown	show	VERB
ejpam-462	190	12	in	in	ADP
ejpam-462	190	13	(	(	PUNCT
ejpam-462	190	14	13	13	NUM
ejpam-462	190	15	)	)	PUNCT
ejpam-462	190	16	.	.	PUNCT
ejpam-462	191	1	f̂−1	f̂−1	PROPN
ejpam-462	191	2	(	(	PUNCT
ejpam-462	191	3	θ	θ	NOUN
ejpam-462	191	4	)	)	PUNCT
ejpam-462	191	5	=	=	SYM
ejpam-462	191	6	�	�	PROPN
ejpam-462	191	7	(	(	PUNCT
ejpam-462	191	8	x	x	NOUN
ejpam-462	191	9	′supω̂	′supω̂	NOUN
ejpam-462	191	10	−1xsup	−1xsup	NOUN
ejpam-462	191	11	)	)	PUNCT
ejpam-462	191	12	−1	−1	NOUN
ejpam-462	191	13	0	0	NUM
ejpam-462	191	14	0′	0′	NUM
ejpam-462	191	15	2	2	NUM
ejpam-462	191	16	n	n	PROPN
ejpam-462	191	17	d+p	d+p	PROPN
ejpam-462	191	18	(	(	PUNCT
ejpam-462	191	19	σ̂⊗	σ̂⊗	PROPN
ejpam-462	191	20	σ̂)d	σ̂)d	VERB
ejpam-462	191	21	+	+	PROPN
ejpam-462	191	22	′	′	NUM
ejpam-462	191	23	p	p	ADJ
ejpam-462	191	24	�	�	PROPN
ejpam-462	191	25	(	(	PUNCT
ejpam-462	191	26	13	13	NUM
ejpam-462	191	27	)	)	PUNCT
ejpam-462	191	28	the	the	DET
ejpam-462	191	29	matrix	matrix	NOUN
ejpam-462	191	30	dp	dp	NOUN
ejpam-462	191	31	is	be	AUX
ejpam-462	191	32	a	a	DET
ejpam-462	191	33	unique	unique	ADJ
ejpam-462	191	34	�	�	NOUN
ejpam-462	191	35	p2	p2	PROPN
ejpam-462	191	36	×	×	PROPN
ejpam-462	191	37	p	p	PROPN
ejpam-462	191	38	�	�	PROPN
ejpam-462	191	39	p+	p+	PART
ejpam-462	191	40	1	1	NUM
ejpam-462	191	41	�	�	PROPN
ejpam-462	191	42	/2	/2	PUNCT
ejpam-462	191	43	�	�	PROPN
ejpam-462	191	44	duplication	duplication	NOUN
ejpam-462	191	45	matrix	matrix	NOUN
ejpam-462	191	46	which	which	PRON
ejpam-462	191	47	transforms	transform	VERB
ejpam-462	191	48	a	a	DET
ejpam-462	191	49	square	square	ADJ
ejpam-462	191	50	matrix	matrix	NOUN
ejpam-462	191	51	;	;	PUNCT
ejpam-462	191	52	d+p	d+p	PROPN
ejpam-462	191	53	is	be	AUX
ejpam-462	191	54	its	its	PRON
ejpam-462	191	55	moore	moore	PROPN
ejpam-462	191	56	-	-	PUNCT
ejpam-462	191	57	penrose	penrose	PROPN
ejpam-462	191	58	inverse	inverse	NOUN
ejpam-462	191	59	:	:	PUNCT
ejpam-462	191	60	d+p	d+p	PROPN
ejpam-462	191	61	=	=	SYM
ejpam-462	191	62	(	(	PUNCT
ejpam-462	191	63	d	d	NOUN
ejpam-462	191	64	′	′	NUM
ejpam-462	191	65	pdp	pdp	PROPN
ejpam-462	191	66	)	)	PUNCT
ejpam-462	191	67	−1d′p	−1d′p	PROPN
ejpam-462	191	68	.	.	PUNCT
ejpam-462	192	1	see	see	VERB
ejpam-462	192	2	[	[	X
ejpam-462	192	3	15	15	NUM
ejpam-462	192	4	]	]	PUNCT
ejpam-462	192	5	for	for	ADP
ejpam-462	192	6	more	more	ADJ
ejpam-462	192	7	about	about	ADP
ejpam-462	192	8	the	the	DET
ejpam-462	192	9	duplication	duplication	NOUN
ejpam-462	192	10	matrix	matrix	NOUN
ejpam-462	192	11	and	and	CCONJ
ejpam-462	192	12	the	the	DET
ejpam-462	192	13	matrix	matrix	NOUN
ejpam-462	192	14	calculus	calculus	NOUN
ejpam-462	192	15	required	require	VERB
ejpam-462	192	16	for	for	ADP
ejpam-462	192	17	the	the	DET
ejpam-462	192	18	derivations	derivation	NOUN
ejpam-462	192	19	.	.	PUNCT
ejpam-462	193	1	for	for	ADP
ejpam-462	193	2	a	a	DET
ejpam-462	193	3	given	give	VERB
ejpam-462	193	4	square	square	ADJ
ejpam-462	193	5	matrix	matrix	NOUN
ejpam-462	193	6	m	m	NOUN
ejpam-462	193	7	,	,	PUNCT
ejpam-462	193	8	the	the	DET
ejpam-462	193	9	complexity	complexity	NOUN
ejpam-462	193	10	is	be	AUX
ejpam-462	193	11	defined	define	VERB
ejpam-462	193	12	as	as	ADP
ejpam-462	193	13	c1	c1	PROPN
ejpam-462	193	14	(	(	PUNCT
ejpam-462	193	15	m	m	PROPN
ejpam-462	193	16	)	)	PUNCT
ejpam-462	193	17	=	=	SYM
ejpam-462	193	18	s	s	PART
ejpam-462	193	19	2	2	NUM
ejpam-462	193	20	log	log	NOUN
ejpam-462	193	21	�	�	PROPN
ejpam-462	193	22	t	t	PROPN
ejpam-462	193	23	r	r	NOUN
ejpam-462	193	24	(	(	PUNCT
ejpam-462	193	25	m	m	NOUN
ejpam-462	193	26	)	)	PUNCT
ejpam-462	193	27	s	s	PART
ejpam-462	193	28	�	�	PROPN
ejpam-462	193	29	−	−	NUM
ejpam-462	193	30	1	1	NUM
ejpam-462	193	31	2	2	NUM
ejpam-462	193	32	log	log	NOUN
ejpam-462	193	33	|m	|m	NOUN
ejpam-462	193	34	|	|	ADV
ejpam-462	193	35	,	,	PUNCT
ejpam-462	193	36	(	(	PUNCT
ejpam-462	193	37	14	14	NUM
ejpam-462	193	38	)	)	PUNCT
ejpam-462	193	39	where	where	SCONJ
ejpam-462	193	40	s	s	NOUN
ejpam-462	193	41	=	=	SYM
ejpam-462	193	42	rank(m	rank(m	NOUN
ejpam-462	193	43	)	)	PUNCT
ejpam-462	193	44	.	.	PUNCT
ejpam-462	194	1	after	after	ADP
ejpam-462	194	2	some	some	DET
ejpam-462	194	3	work	work	NOUN
ejpam-462	194	4	,	,	PUNCT
ejpam-462	194	5	we	we	PRON
ejpam-462	194	6	have	have	VERB
ejpam-462	194	7	the	the	DET
ejpam-462	194	8	complexity	complexity	NOUN
ejpam-462	194	9	of	of	ADP
ejpam-462	194	10	the	the	DET
ejpam-462	194	11	inverse	inverse	NOUN
ejpam-462	194	12	fisher	fisher	PROPN
ejpam-462	194	13	information	information	NOUN
ejpam-462	194	14	matrix	matrix	NOUN
ejpam-462	194	15	in	in	ADP
ejpam-462	194	16	(	(	PUNCT
ejpam-462	194	17	15	15	NUM
ejpam-462	194	18	)	)	PUNCT
ejpam-462	194	19	.	.	PUNCT
ejpam-462	195	1	c1(f̂	c1(f̂	PROPN
ejpam-462	195	2	−1	−1	NOUN
ejpam-462	195	3	)	)	PUNCT
ejpam-462	195	4	=	=	PRON
ejpam-462	195	5	{	{	PUNCT
ejpam-462	195	6	m	m	PROPN
ejpam-462	195	7	2	2	NUM
ejpam-462	195	8	log	log	NOUN
ejpam-462	195	9			NOUN
ejpam-462	195	10			PRON
ejpam-462	195	11	t	t	NOUN
ejpam-462	195	12	r	r	X
ejpam-462	195	13	[	[	PUNCT
ejpam-462	195	14	�	�	PROPN
ejpam-462	195	15	x	x	SYM
ejpam-462	195	16	′supω̂	′supω̂	NOUN
ejpam-462	195	17	−1xsup	−1xsup	NOUN
ejpam-462	195	18	�	�	NOUN
ejpam-462	195	19	−1	−1	NOUN
ejpam-462	195	20	]	]	PUNCT
ejpam-462	196	1	+	+	CCONJ
ejpam-462	196	2	1	1	NUM
ejpam-462	196	3	2n	2n	NUM
ejpam-462	196	4	g	g	PROPN
ejpam-462	196	5	m	m	PROPN
ejpam-462	196	6			PROPN
ejpam-462	196	7			PROPN
ejpam-462	196	8	.	.	PUNCT
ejpam-462	196	9	.	.	PUNCT
ejpam-462	197	1	.	.	PUNCT
ejpam-462	198	1	−	−	NOUN
ejpam-462	198	2	1	1	NUM
ejpam-462	198	3	2	2	NUM
ejpam-462	198	4	log	log	NOUN
ejpam-462	198	5	|	|	ADV
ejpam-462	198	6	�	�	PROPN
ejpam-462	198	7	x	x	PUNCT
ejpam-462	198	8	′supω̂	′supω̂	NOUN
ejpam-462	198	9	−1xsup	−1xsup	NOUN
ejpam-462	198	10	�	�	NOUN
ejpam-462	198	11	−1	−1	NOUN
ejpam-462	198	12	|	|	ADV
ejpam-462	198	13	−	−	PROPN
ejpam-462	198	14	p	p	NOUN
ejpam-462	198	15	2	2	NUM
ejpam-462	198	16	log	log	NOUN
ejpam-462	198	17	(	(	PUNCT
ejpam-462	198	18	2	2	NUM
ejpam-462	198	19	)	)	PUNCT
ejpam-462	198	20	+	+	CCONJ
ejpam-462	198	21	p	p	PROPN
ejpam-462	198	22	�	�	PROPN
ejpam-462	198	23	p+	p+	PART
ejpam-462	198	24	1	1	NUM
ejpam-462	198	25	�	�	PROPN
ejpam-462	198	26	log	log	VERB
ejpam-462	198	27	n	n	PRON
ejpam-462	198	28	4	4	NUM
ejpam-462	198	29	.	.	PUNCT
ejpam-462	198	30	.	.	PUNCT
ejpam-462	198	31	.	.	PUNCT
ejpam-462	199	1	−	−	PROPN
ejpam-462	199	2	�	�	PROPN
ejpam-462	199	3	p+	p+	PART
ejpam-462	199	4	1	1	NUM
ejpam-462	199	5	�	�	PROPN
ejpam-462	199	6	2	2	NUM
ejpam-462	199	7	log	log	NOUN
ejpam-462	199	8	|σ̂∗fgls|	|σ̂∗fgls|	PROPN
ejpam-462	199	9	}	}	PUNCT
ejpam-462	199	10	.	.	PUNCT
ejpam-462	200	1	(	(	PUNCT
ejpam-462	200	2	15	15	X
ejpam-462	200	3	)	)	PUNCT
ejpam-462	200	4	a.	a.	NOUN
ejpam-462	200	5	howe	howe	NOUN
ejpam-462	200	6	and	and	CCONJ
ejpam-462	200	7	h.	h.	PROPN
ejpam-462	200	8	bozdogan	bozdogan	PROPN
ejpam-462	200	9	/	/	SYM
ejpam-462	200	10	eur	eur	PROPN
ejpam-462	200	11	.	.	PUNCT
ejpam-462	201	1	j.	j.	PROPN
ejpam-462	201	2	pure	pure	PROPN
ejpam-462	201	3	appl	appl	PROPN
ejpam-462	201	4	.	.	PROPN
ejpam-462	201	5	math	math	PROPN
ejpam-462	201	6	,	,	PUNCT
ejpam-462	201	7	3	3	NUM
ejpam-462	201	8	(	(	PUNCT
ejpam-462	201	9	2010	2010	NUM
ejpam-462	201	10	)	)	PUNCT
ejpam-462	201	11	,	,	PUNCT
ejpam-462	201	12	382	382	NUM
ejpam-462	201	13	-	-	SYM
ejpam-462	201	14	405	405	NUM
ejpam-462	201	15	391	391	NUM
ejpam-462	201	16	we	we	PRON
ejpam-462	201	17	define	define	VERB
ejpam-462	201	18	g	g	PRON
ejpam-462	201	19	to	to	PART
ejpam-462	201	20	be	be	AUX
ejpam-462	201	21	g	g	PROPN
ejpam-462	201	22	=	=	SYM
ejpam-462	201	23	t	t	PROPN
ejpam-462	201	24	r(σ̂∗2fgls	r(σ̂∗2fgls	PROPN
ejpam-462	201	25	)	)	PUNCT
ejpam-462	202	1	+	+	NUM
ejpam-462	202	2	t	t	NOUN
ejpam-462	202	3	r(σ̂∗2fgls	r(σ̂∗2fgl	NOUN
ejpam-462	202	4	)	)	PUNCT
ejpam-462	202	5	+	+	CCONJ
ejpam-462	202	6	2	2	NUM
ejpam-462	202	7	p∑	p∑	NOUN
ejpam-462	203	1	j=1	j=1	PROPN
ejpam-462	203	2	�	�	PROPN
ejpam-462	204	1	σ̂2	σ̂2	PROPN
ejpam-462	205	1	j	j	PROPN
ejpam-462	206	1	j	j	PROPN
ejpam-462	206	2	�	�	PROPN
ejpam-462	206	3	2	2	NUM
ejpam-462	206	4	.	.	PUNCT
ejpam-462	207	1	in	in	ADP
ejpam-462	207	2	most	most	ADJ
ejpam-462	207	3	statistical	statistical	ADJ
ejpam-462	207	4	modeling	modeling	NOUN
ejpam-462	207	5	problems	problem	NOUN
ejpam-462	207	6	,	,	PUNCT
ejpam-462	207	7	we	we	PRON
ejpam-462	207	8	ca	can	AUX
ejpam-462	207	9	n’t	not	PART
ejpam-462	207	10	assume	assume	VERB
ejpam-462	207	11	that	that	SCONJ
ejpam-462	207	12	the	the	DET
ejpam-462	207	13	true	true	ADJ
ejpam-462	207	14	model	model	NOUN
ejpam-462	207	15	is	be	AUX
ejpam-462	207	16	one	one	NUM
ejpam-462	207	17	of	of	ADP
ejpam-462	207	18	those	those	PRON
ejpam-462	207	19	being	be	AUX
ejpam-462	207	20	evaluated	evaluate	VERB
ejpam-462	207	21	.	.	PUNCT
ejpam-462	208	1	this	this	PRON
ejpam-462	208	2	can	can	AUX
ejpam-462	208	3	bias	bias	VERB
ejpam-462	208	4	parameter	parameter	NOUN
ejpam-462	208	5	estimates	estimate	NOUN
ejpam-462	208	6	and	and	CCONJ
ejpam-462	208	7	overor	overor	NOUN
ejpam-462	208	8	underestimate	underestimate	VERB
ejpam-462	208	9	their	their	PRON
ejpam-462	208	10	variances	variance	NOUN
ejpam-462	208	11	.	.	PUNCT
ejpam-462	209	1	in	in	ADP
ejpam-462	209	2	the	the	DET
ejpam-462	209	3	context	context	NOUN
ejpam-462	209	4	of	of	ADP
ejpam-462	209	5	regression	regression	NOUN
ejpam-462	209	6	,	,	PUNCT
ejpam-462	209	7	one	one	NUM
ejpam-462	209	8	of	of	ADP
ejpam-462	209	9	the	the	DET
ejpam-462	209	10	most	most	ADV
ejpam-462	209	11	abused	abuse	VERB
ejpam-462	209	12	assumptions	assumption	NOUN
ejpam-462	209	13	is	be	AUX
ejpam-462	209	14	that	that	PRON
ejpam-462	209	15	of	of	ADP
ejpam-462	209	16	normality	normality	NOUN
ejpam-462	209	17	.	.	PUNCT
ejpam-462	210	1	non	non	ADJ
ejpam-462	210	2	-	-	ADJ
ejpam-462	210	3	normal	normal	ADJ
ejpam-462	210	4	characteristics	characteristic	NOUN
ejpam-462	210	5	of	of	ADP
ejpam-462	210	6	data	datum	NOUN
ejpam-462	210	7	,	,	PUNCT
ejpam-462	210	8	such	such	ADJ
ejpam-462	210	9	as	as	ADP
ejpam-462	210	10	kurtosis	kurtosis	NOUN
ejpam-462	210	11	and	and	CCONJ
ejpam-462	210	12	skewness	skewness	NOUN
ejpam-462	210	13	,	,	PUNCT
ejpam-462	210	14	bias	bias	VERB
ejpam-462	210	15	the	the	DET
ejpam-462	210	16	coefficient	coefficient	NOUN
ejpam-462	210	17	estimates	estimate	VERB
ejpam-462	210	18	.	.	PUNCT
ejpam-462	211	1	to	to	PART
ejpam-462	211	2	combat	combat	VERB
ejpam-462	211	3	this	this	PRON
ejpam-462	211	4	,	,	PUNCT
ejpam-462	211	5	a	a	DET
ejpam-462	211	6	bias	bias	NOUN
ejpam-462	211	7	estimate	estimate	NOUN
ejpam-462	211	8	can	can	AUX
ejpam-462	211	9	be	be	AUX
ejpam-462	211	10	computed	compute	VERB
ejpam-462	211	11	as	as	ADP
ejpam-462	211	12	b̂	b̂	NOUN
ejpam-462	211	13	=	=	PROPN
ejpam-462	211	14	t	t	PROPN
ejpam-462	211	15	r(f̂−1r̂	r(f̂−1r̂	PROPN
ejpam-462	211	16	)	)	PUNCT
ejpam-462	211	17	.	.	PUNCT
ejpam-462	212	1	when	when	SCONJ
ejpam-462	212	2	a	a	DET
ejpam-462	212	3	model	model	NOUN
ejpam-462	212	4	is	be	AUX
ejpam-462	212	5	correctly	correctly	ADV
ejpam-462	212	6	specified	specify	VERB
ejpam-462	212	7	,	,	PUNCT
ejpam-462	212	8	it	it	PRON
ejpam-462	212	9	is	be	AUX
ejpam-462	212	10	well	well	ADV
ejpam-462	212	11	known	know	VERB
ejpam-462	212	12	that	that	SCONJ
ejpam-462	212	13	the	the	DET
ejpam-462	212	14	covariance	covariance	NOUN
ejpam-462	212	15	of	of	ADP
ejpam-462	212	16	the	the	DET
ejpam-462	212	17	parameters	parameter	NOUN
ejpam-462	212	18	is	be	AUX
ejpam-462	212	19	f̂−1	f̂−1	PROPN
ejpam-462	212	20	.	.	PUNCT
ejpam-462	213	1	however	however	ADV
ejpam-462	213	2	,	,	PUNCT
ejpam-462	213	3	in	in	ADP
ejpam-462	213	4	the	the	DET
ejpam-462	213	5	presence	presence	NOUN
ejpam-462	213	6	of	of	ADP
ejpam-462	213	7	misspecification	misspecification	NOUN
ejpam-462	213	8	,	,	PUNCT
ejpam-462	213	9	the	the	DET
ejpam-462	213	10	appropriate	appropriate	ADJ
ejpam-462	213	11	covariance	covariance	NOUN
ejpam-462	213	12	matrix	matrix	NOUN
ejpam-462	213	13	can	can	AUX
ejpam-462	213	14	be	be	AUX
ejpam-462	213	15	shown	show	VERB
ejpam-462	213	16	to	to	PART
ejpam-462	213	17	be	be	AUX
ejpam-462	213	18	ôcov	ôcov	VERB
ejpam-462	213	19	(	(	PUNCT
ejpam-462	213	20	θ	θ	NOUN
ejpam-462	213	21	)	)	PUNCT
ejpam-462	213	22	=	=	SYM
ejpam-462	213	23	f̂−1r̂f̂−1	f̂−1r̂f̂−1	NOUN
ejpam-462	213	24	.	.	PUNCT
ejpam-462	214	1	whereas	whereas	SCONJ
ejpam-462	214	2	f̂	f̂	PROPN
ejpam-462	214	3	is	be	AUX
ejpam-462	214	4	the	the	DET
ejpam-462	214	5	inner	inner	ADJ
ejpam-462	214	6	-	-	PUNCT
ejpam-462	214	7	product	product	NOUN
ejpam-462	214	8	(	(	PUNCT
ejpam-462	214	9	or	or	CCONJ
ejpam-462	214	10	hessian	hessian	ADJ
ejpam-462	214	11	)	)	PUNCT
ejpam-462	214	12	form	form	NOUN
ejpam-462	214	13	of	of	ADP
ejpam-462	214	14	the	the	DET
ejpam-462	214	15	fim	fim	NOUN
ejpam-462	214	16	,	,	PUNCT
ejpam-462	214	17	r̂	r̂	NOUN
ejpam-462	214	18	is	be	AUX
ejpam-462	214	19	the	the	DET
ejpam-462	214	20	outer	outer	ADJ
ejpam-462	214	21	-	-	PUNCT
ejpam-462	214	22	product	product	NOUN
ejpam-462	214	23	form	form	NOUN
ejpam-462	214	24	,	,	PUNCT
ejpam-462	214	25	both	both	PRON
ejpam-462	214	26	shown	show	VERB
ejpam-462	214	27	in	in	ADP
ejpam-462	214	28	(	(	PUNCT
ejpam-462	214	29	16	16	NUM
ejpam-462	214	30	)	)	PUNCT
ejpam-462	214	31	and	and	CCONJ
ejpam-462	214	32	(	(	PUNCT
ejpam-462	214	33	17	17	NUM
ejpam-462	214	34	)	)	PUNCT
ejpam-462	214	35	.	.	PUNCT
ejpam-462	215	1	f	f	X
ejpam-462	216	1	=	=	PRON
ejpam-462	216	2	−e	−e	NOUN
ejpam-462	216	3	�	�	PROPN
ejpam-462	216	4	∂	∂	NUM
ejpam-462	216	5	2	2	NUM
ejpam-462	216	6	log	log	NOUN
ejpam-462	216	7	l	l	NOUN
ejpam-462	216	8	(	(	PUNCT
ejpam-462	216	9	θ	θ	NOUN
ejpam-462	216	10	)	)	PUNCT
ejpam-462	216	11	∂	∂	NOUN
ejpam-462	216	12	θ∂	θ∂	NOUN
ejpam-462	216	13	θ	θ	NOUN
ejpam-462	216	14	′	′	NUM
ejpam-462	216	15	�	�	PROPN
ejpam-462	216	16	(	(	PUNCT
ejpam-462	216	17	16	16	NUM
ejpam-462	216	18	)	)	PUNCT
ejpam-462	216	19	r	r	NOUN
ejpam-462	216	20	=	=	SYM
ejpam-462	216	21	e	e	X
ejpam-462	216	22	�	�	PROPN
ejpam-462	216	23	∂	∂	NUM
ejpam-462	216	24	log	log	NOUN
ejpam-462	216	25	l	l	PROPN
ejpam-462	216	26	(	(	PUNCT
ejpam-462	216	27	θ	θ	NOUN
ejpam-462	216	28	)	)	PUNCT
ejpam-462	216	29	∂	∂	NUM
ejpam-462	216	30	θ	θ	NOUN
ejpam-462	216	31	·	·	PUNCT
ejpam-462	216	32	∂	∂	NUM
ejpam-462	216	33	log	log	NOUN
ejpam-462	216	34	l	l	PROPN
ejpam-462	216	35	(	(	PUNCT
ejpam-462	216	36	θ	θ	NOUN
ejpam-462	216	37	)	)	PUNCT
ejpam-462	216	38	∂	∂	NUM
ejpam-462	216	39	θ	θ	NOUN
ejpam-462	216	40	′	′	NUM
ejpam-462	216	41	�	�	PROPN
ejpam-462	216	42	(	(	PUNCT
ejpam-462	216	43	17	17	NUM
ejpam-462	216	44	)	)	PUNCT
ejpam-462	216	45	of	of	ADP
ejpam-462	216	46	course	course	NOUN
ejpam-462	216	47	,	,	PUNCT
ejpam-462	216	48	we	we	PRON
ejpam-462	216	49	must	must	AUX
ejpam-462	216	50	use	use	VERB
ejpam-462	216	51	the	the	DET
ejpam-462	216	52	observed	observe	VERB
ejpam-462	216	53	values	value	NOUN
ejpam-462	216	54	for	for	ADP
ejpam-462	216	55	these	these	DET
ejpam-462	216	56	matrices	matrix	NOUN
ejpam-462	216	57	:	:	PUNCT
ejpam-462	216	58	f̂	f̂	NUM
ejpam-462	216	59	and	and	CCONJ
ejpam-462	216	60	r̂	r̂	NOUN
ejpam-462	216	61	.	.	PUNCT
ejpam-462	217	1	unfortunately	unfortunately	ADV
ejpam-462	217	2	,	,	PUNCT
ejpam-462	217	3	for	for	ADP
ejpam-462	217	4	the	the	DET
ejpam-462	217	5	problem	problem	NOUN
ejpam-462	217	6	of	of	ADP
ejpam-462	217	7	feasible	feasible	ADJ
ejpam-462	217	8	generalized	generalized	ADJ
ejpam-462	217	9	least	least	ADJ
ejpam-462	217	10	squares	square	NOUN
ejpam-462	217	11	,	,	PUNCT
ejpam-462	217	12	computation	computation	NOUN
ejpam-462	217	13	of	of	ADP
ejpam-462	217	14	r̂	r̂	NOUN
ejpam-462	217	15	is	be	AUX
ejpam-462	217	16	a	a	DET
ejpam-462	217	17	currently	currently	ADV
ejpam-462	217	18	intractable	intractable	ADJ
ejpam-462	217	19	problem	problem	NOUN
ejpam-462	217	20	,	,	PUNCT
ejpam-462	217	21	so	so	ADV
ejpam-462	217	22	b̂	b̂	NOUN
ejpam-462	217	23	is	be	AUX
ejpam-462	217	24	not	not	PART
ejpam-462	217	25	directly	directly	ADV
ejpam-462	217	26	computable	computable	ADJ
ejpam-462	217	27	.	.	PUNCT
ejpam-462	218	1	however	however	ADV
ejpam-462	218	2	,	,	PUNCT
ejpam-462	218	3	it	it	PRON
ejpam-462	218	4	can	can	AUX
ejpam-462	218	5	be	be	AUX
ejpam-462	218	6	shown	show	VERB
ejpam-462	218	7	that	that	SCONJ
ejpam-462	218	8	b̂	b̂	NOUN
ejpam-462	218	9	≃	≃	ADJ
ejpam-462	218	10	nm/	nm/	ADJ
ejpam-462	218	11	(	(	PUNCT
ejpam-462	218	12	n−m−	n−m−	NOUN
ejpam-462	218	13	2	2	NUM
ejpam-462	218	14	)	)	PUNCT
ejpam-462	218	15	.	.	PUNCT
ejpam-462	219	1	thus	thus	ADV
ejpam-462	219	2	,	,	PUNCT
ejpam-462	219	3	icom	icom	PROPN
ejpam-462	219	4	pm	pm	PROPN
ejpam-462	219	5	isp_peu(f̂	isp_peu(f̂	PROPN
ejpam-462	219	6	−1	−1	NOUN
ejpam-462	219	7	)	)	PUNCT
ejpam-462	219	8	can	can	AUX
ejpam-462	219	9	still	still	ADV
ejpam-462	219	10	drive	drive	VERB
ejpam-462	219	11	effective	effective	ADJ
ejpam-462	219	12	model	model	NOUN
ejpam-462	219	13	selection	selection	NOUN
ejpam-462	219	14	,	,	PUNCT
ejpam-462	219	15	considering	consider	VERB
ejpam-462	219	16	the	the	DET
ejpam-462	219	17	nonnormal	nonnormal	ADJ
ejpam-462	219	18	characteristics	characteristic	NOUN
ejpam-462	219	19	of	of	ADP
ejpam-462	219	20	the	the	DET
ejpam-462	219	21	data	datum	NOUN
ejpam-462	219	22	,	,	PUNCT
ejpam-462	219	23	despite	despite	SCONJ
ejpam-462	219	24	any	any	DET
ejpam-462	219	25	incorrect	incorrect	ADJ
ejpam-462	219	26	assumptions	assumption	NOUN
ejpam-462	219	27	,	,	PUNCT
ejpam-462	219	28	is	be	AUX
ejpam-462	219	29	given	give	VERB
ejpam-462	219	30	by	by	ADP
ejpam-462	219	31	icom	icom	PROPN
ejpam-462	219	32	pm	pm	PROPN
ejpam-462	219	33	isp_peu(f̂	isp_peu(f̂	PROPN
ejpam-462	219	34	−1	−1	NOUN
ejpam-462	219	35	)	)	PUNCT
ejpam-462	220	1	=	=	NOUN
ejpam-462	221	1	np	np	INTJ
ejpam-462	221	2	log	log	NOUN
ejpam-462	221	3	(	(	PUNCT
ejpam-462	221	4	2π)+	2π)+	NOUN
ejpam-462	221	5	n	n	PRON
ejpam-462	221	6	log	log	VERB
ejpam-462	221	7	|σ̂fgls|+	|σ̂fgls|+	NOUN
ejpam-462	222	1	np	np	INTJ
ejpam-462	223	1	+	+	CCONJ
ejpam-462	223	2	m+	m+	NUM
ejpam-462	223	3	2	2	NUM
ejpam-462	223	4	�	�	PROPN
ejpam-462	223	5	nm	nm	ADJ
ejpam-462	223	6	n−m−	n−m−	NUM
ejpam-462	223	7	2	2	NUM
ejpam-462	223	8	�	�	NOUN
ejpam-462	223	9	+	+	CCONJ
ejpam-462	223	10	2c1(f̂	2c1(f̂	NUM
ejpam-462	223	11	−1	−1	NOUN
ejpam-462	223	12	)	)	PUNCT
ejpam-462	223	13	.	.	PUNCT
ejpam-462	224	1	(	(	PUNCT
ejpam-462	224	2	18	18	NUM
ejpam-462	224	3	)	)	PUNCT
ejpam-462	224	4	slightly	slightly	ADV
ejpam-462	224	5	simpler	simple	ADJ
ejpam-462	224	6	would	would	AUX
ejpam-462	224	7	be	be	AUX
ejpam-462	224	8	icom	icom	PROPN
ejpam-462	224	9	pm	pm	VERB
ejpam-462	224	10	isp	isp	ADV
ejpam-462	224	11	,	,	PUNCT
ejpam-462	224	12	which	which	PRON
ejpam-462	224	13	does	do	AUX
ejpam-462	224	14	not	not	PART
ejpam-462	224	15	have	have	VERB
ejpam-462	224	16	the	the	DET
ejpam-462	224	17	m	m	NOUN
ejpam-462	224	18	term	term	NOUN
ejpam-462	224	19	,	,	PUNCT
ejpam-462	224	20	or	or	CCONJ
ejpam-462	224	21	icom	icom	PROPN
ejpam-462	224	22	ppeu	ppeu	PROPN
ejpam-462	224	23	,	,	PUNCT
ejpam-462	224	24	missing	miss	VERB
ejpam-462	224	25	the	the	DET
ejpam-462	224	26	2b̂.	2b̂.	NUM
ejpam-462	224	27	finally	finally	ADV
ejpam-462	224	28	,	,	PUNCT
ejpam-462	224	29	we	we	PRON
ejpam-462	224	30	would	would	AUX
ejpam-462	224	31	mention	mention	VERB
ejpam-462	224	32	that	that	SCONJ
ejpam-462	224	33	cross	cross	ADJ
ejpam-462	224	34	-	-	ADJ
ejpam-462	224	35	validation	validation	ADJ
ejpam-462	224	36	based	base	VERB
ejpam-462	224	37	criteria	criterion	NOUN
ejpam-462	224	38	are	be	AUX
ejpam-462	224	39	often	often	ADV
ejpam-462	224	40	used	use	VERB
ejpam-462	224	41	for	for	ADP
ejpam-462	224	42	model	model	NOUN
ejpam-462	224	43	selection	selection	NOUN
ejpam-462	224	44	problems	problem	NOUN
ejpam-462	224	45	.	.	PUNCT
ejpam-462	225	1	given	give	VERB
ejpam-462	225	2	the	the	DET
ejpam-462	225	3	high	high	ADJ
ejpam-462	225	4	complexity	complexity	NOUN
ejpam-462	225	5	of	of	ADP
ejpam-462	225	6	our	our	PRON
ejpam-462	225	7	application	application	NOUN
ejpam-462	225	8	,	,	PUNCT
ejpam-462	225	9	cross	cross	NOUN
ejpam-462	225	10	-	-	NOUN
ejpam-462	225	11	validation	validation	NOUN
ejpam-462	225	12	is	be	AUX
ejpam-462	225	13	just	just	ADV
ejpam-462	225	14	not	not	PART
ejpam-462	225	15	computationally	computationally	ADV
ejpam-462	225	16	feasible	feasible	ADJ
ejpam-462	225	17	.	.	PUNCT
ejpam-462	226	1	this	this	DET
ejpam-462	226	2	complexity	complexity	NOUN
ejpam-462	226	3	raises	raise	VERB
ejpam-462	226	4	concerns	concern	NOUN
ejpam-462	226	5	regarding	regard	VERB
ejpam-462	226	6	the	the	DET
ejpam-462	226	7	feasibility	feasibility	NOUN
ejpam-462	226	8	of	of	ADP
ejpam-462	226	9	subset	subset	NOUN
ejpam-462	226	10	selection	selection	NOUN
ejpam-462	226	11	,	,	PUNCT
ejpam-462	226	12	given	give	VERB
ejpam-462	226	13	existing	exist	VERB
ejpam-462	226	14	computational	computational	ADJ
ejpam-462	226	15	power	power	NOUN
ejpam-462	226	16	.	.	PUNCT
ejpam-462	227	1	one	one	NUM
ejpam-462	227	2	response	response	NOUN
ejpam-462	227	3	would	would	AUX
ejpam-462	227	4	be	be	AUX
ejpam-462	227	5	to	to	PART
ejpam-462	227	6	restrict	restrict	VERB
ejpam-462	227	7	attention	attention	NOUN
ejpam-462	227	8	to	to	ADP
ejpam-462	227	9	very	very	ADV
ejpam-462	227	10	small	small	ADJ
ejpam-462	227	11	models	model	NOUN
ejpam-462	227	12	.	.	PUNCT
ejpam-462	228	1	our	our	PRON
ejpam-462	228	2	results	result	NOUN
ejpam-462	228	3	,	,	PUNCT
ejpam-462	228	4	however	however	ADV
ejpam-462	228	5	,	,	PUNCT
ejpam-462	228	6	demonstrate	demonstrate	VERB
ejpam-462	228	7	that	that	SCONJ
ejpam-462	228	8	arbitrary	arbitrary	ADJ
ejpam-462	228	9	restrictions	restriction	NOUN
ejpam-462	228	10	such	such	ADJ
ejpam-462	228	11	as	as	ADP
ejpam-462	228	12	this	this	PRON
ejpam-462	228	13	are	be	AUX
ejpam-462	228	14	unnecessary	unnecessary	ADJ
ejpam-462	228	15	.	.	PUNCT
ejpam-462	229	1	5	5	X
ejpam-462	229	2	.	.	X
ejpam-462	229	3	numerical	numerical	PROPN
ejpam-462	229	4	results	result	NOUN
ejpam-462	229	5	the	the	DET
ejpam-462	229	6	value	value	NOUN
ejpam-462	229	7	of	of	ADP
ejpam-462	229	8	our	our	PRON
ejpam-462	229	9	techniques	technique	NOUN
ejpam-462	229	10	are	be	AUX
ejpam-462	229	11	demonstrated	demonstrate	VERB
ejpam-462	229	12	here	here	ADV
ejpam-462	229	13	using	use	VERB
ejpam-462	229	14	both	both	DET
ejpam-462	229	15	simulated	simulated	ADJ
ejpam-462	229	16	data	datum	NOUN
ejpam-462	229	17	and	and	CCONJ
ejpam-462	229	18	the	the	DET
ejpam-462	229	19	real	real	ADJ
ejpam-462	229	20	-	-	PUNCT
ejpam-462	229	21	world	world	NOUN
ejpam-462	229	22	example	example	NOUN
ejpam-462	229	23	using	use	VERB
ejpam-462	229	24	stock	stock	NOUN
ejpam-462	229	25	market	market	NOUN
ejpam-462	229	26	indices	index	NOUN
ejpam-462	229	27	,	,	PUNCT
ejpam-462	229	28	respectively	respectively	ADV
ejpam-462	229	29	.	.	PUNCT
ejpam-462	230	1	in	in	ADP
ejpam-462	230	2	both	both	DET
ejpam-462	230	3	cases	case	NOUN
ejpam-462	230	4	,	,	PUNCT
ejpam-462	230	5	we	we	PRON
ejpam-462	230	6	see	see	VERB
ejpam-462	230	7	models	model	NOUN
ejpam-462	230	8	emerging	emerge	VERB
ejpam-462	230	9	that	that	PRON
ejpam-462	230	10	fit	fit	VERB
ejpam-462	230	11	the	the	DET
ejpam-462	230	12	data	datum	NOUN
ejpam-462	230	13	well	well	ADV
ejpam-462	230	14	,	,	PUNCT
ejpam-462	230	15	are	be	AUX
ejpam-462	230	16	efficient	efficient	ADJ
ejpam-462	230	17	with	with	ADP
ejpam-462	230	18	their	their	PRON
ejpam-462	230	19	forecasts	forecast	NOUN
ejpam-462	230	20	,	,	PUNCT
ejpam-462	230	21	and	and	CCONJ
ejpam-462	230	22	use	use	VERB
ejpam-462	230	23	substantially	substantially	ADV
ejpam-462	230	24	reduced	reduce	VERB
ejpam-462	230	25	parameter	parameter	NOUN
ejpam-462	230	26	spaces	space	NOUN
ejpam-462	230	27	.	.	PUNCT
ejpam-462	231	1	a.	a.	NOUN
ejpam-462	231	2	howe	howe	PROPN
ejpam-462	231	3	and	and	CCONJ
ejpam-462	231	4	h.	h.	PROPN
ejpam-462	231	5	bozdogan	bozdogan	PROPN
ejpam-462	231	6	/	/	SYM
ejpam-462	231	7	eur	eur	PROPN
ejpam-462	231	8	.	.	PUNCT
ejpam-462	232	1	j.	j.	PROPN
ejpam-462	232	2	pure	pure	PROPN
ejpam-462	232	3	appl	appl	PROPN
ejpam-462	232	4	.	.	PROPN
ejpam-462	232	5	math	math	PROPN
ejpam-462	232	6	,	,	PUNCT
ejpam-462	232	7	3	3	NUM
ejpam-462	232	8	(	(	PUNCT
ejpam-462	232	9	2010	2010	NUM
ejpam-462	232	10	)	)	PUNCT
ejpam-462	232	11	,	,	PUNCT
ejpam-462	232	12	382	382	NUM
ejpam-462	232	13	-	-	SYM
ejpam-462	232	14	405	405	NUM
ejpam-462	232	15	392	392	NUM
ejpam-462	232	16	5.1	5.1	NUM
ejpam-462	232	17	.	.	PUNCT
ejpam-462	233	1	simulation	simulation	NOUN
ejpam-462	233	2	we	we	PRON
ejpam-462	233	3	begin	begin	VERB
ejpam-462	233	4	by	by	ADP
ejpam-462	233	5	generating	generate	VERB
ejpam-462	233	6	data	datum	NOUN
ejpam-462	233	7	from	from	ADP
ejpam-462	233	8	a	a	DET
ejpam-462	233	9	bivariate	bivariate	NOUN
ejpam-462	233	10	(	(	PUNCT
ejpam-462	233	11	p	p	NOUN
ejpam-462	233	12	=	=	NOUN
ejpam-462	233	13	2	2	NUM
ejpam-462	233	14	)	)	PUNCT
ejpam-462	233	15	autoregressive	autoregressive	ADJ
ejpam-462	233	16	data	datum	NOUN
ejpam-462	233	17	generating	generating	NOUN
ejpam-462	233	18	process	process	NOUN
ejpam-462	233	19	shown	show	VERB
ejpam-462	233	20	in	in	ADP
ejpam-462	233	21	(	(	PUNCT
ejpam-462	233	22	19	19	NUM
ejpam-462	233	23	)	)	PUNCT
ejpam-462	233	24	.	.	PUNCT
ejpam-462	234	1	�	�	PROPN
ejpam-462	234	2	y	y	NOUN
ejpam-462	234	3	′t	′t	NOUN
ejpam-462	234	4	x	x	PUNCT
ejpam-462	234	5	′t	′t	PROPN
ejpam-462	234	6	�	�	PROPN
ejpam-462	234	7	=	=	SYM
ejpam-462	234	8	φ1	φ1	PROPN
ejpam-462	234	9	�	�	PROPN
ejpam-462	234	10	y	y	PROPN
ejpam-462	234	11	′t−1	′t−1	NOUN
ejpam-462	234	12	x	x	SYM
ejpam-462	234	13	′t−1	′t−1	NOUN
ejpam-462	234	14	�	�	PROPN
ejpam-462	234	15	+	+	PROPN
ejpam-462	234	16	φ2	φ2	PROPN
ejpam-462	234	17	�	�	PROPN
ejpam-462	234	18	y	y	PROPN
ejpam-462	234	19	′t−2	′t−2	PROPN
ejpam-462	234	20	x	x	SYM
ejpam-462	234	21	′t−2	′t−2	ADJ
ejpam-462	234	22	�	�	PROPN
ejpam-462	234	23	+	+	CCONJ
ejpam-462	234	24	ǫt	ǫt	PROPN
ejpam-462	234	25	(	(	PUNCT
ejpam-462	234	26	19	19	NUM
ejpam-462	234	27	)	)	PUNCT
ejpam-462	234	28	we	we	PRON
ejpam-462	234	29	build	build	VERB
ejpam-462	234	30	the	the	DET
ejpam-462	234	31	coefficient	coefficient	NOUN
ejpam-462	234	32	matrices	matrix	NOUN
ejpam-462	234	33	as	as	ADP
ejpam-462	234	34	φ1	φ1	PROPN
ejpam-462	234	35	=	=	SYM
ejpam-462	234	36	�	�	PROPN
ejpam-462	234	37	−0.2800	−0.2800	NUM
ejpam-462	234	38	0.0215	0.0215	NUM
ejpam-462	234	39	−0.5496	−0.5496	NUM
ejpam-462	234	40	0.2854	0.2854	NUM
ejpam-462	234	41	�	�	PROPN
ejpam-462	234	42	,	,	PUNCT
ejpam-462	234	43	and	and	CCONJ
ejpam-462	234	44	φ2	φ2	PROPN
ejpam-462	234	45	=	=	SYM
ejpam-462	234	46	�	�	PROPN
ejpam-462	234	47	−0.2785	−0.2785	X
ejpam-462	234	48	−0.4081	−0.4081	PROPN
ejpam-462	235	1	−0.0144	−0.0144	PROPN
ejpam-462	235	2	0.1809	0.1809	NUM
ejpam-462	235	3	�	�	PROPN
ejpam-462	235	4	,	,	PUNCT
ejpam-462	235	5	and	and	CCONJ
ejpam-462	235	6	the	the	DET
ejpam-462	235	7	error	error	NOUN
ejpam-462	235	8	terms	term	NOUN
ejpam-462	235	9	are	be	AUX
ejpam-462	235	10	generated	generate	VERB
ejpam-462	235	11	from	from	ADP
ejpam-462	235	12	a	a	DET
ejpam-462	235	13	multivariate	multivariate	NOUN
ejpam-462	235	14	gaussian	gaussian	ADJ
ejpam-462	235	15	white	white	PROPN
ejpam-462	235	16	noise	noise	NOUN
ejpam-462	235	17	process	process	NOUN
ejpam-462	235	18	ǫt	ǫt	NOUN
ejpam-462	235	19	∼	∼	NOUN
ejpam-462	235	20	n2	n2	ADJ
ejpam-462	235	21	�	�	PROPN
ejpam-462	235	22	µ,σ	µ,σ	ADP
ejpam-462	235	23	�	�	PROPN
ejpam-462	235	24	with	with	ADP
ejpam-462	235	25	parameters	parameter	NOUN
ejpam-462	235	26	µ	µ	X
ejpam-462	235	27	=	=	SYM
ejpam-462	235	28	�	�	PROPN
ejpam-462	235	29	0.00	0.00	NUM
ejpam-462	235	30	0.00	0.00	NUM
ejpam-462	235	31	�	�	PROPN
ejpam-462	235	32	and	and	CCONJ
ejpam-462	235	33	σ	σ	PROPN
ejpam-462	235	34	=	=	SYM
ejpam-462	235	35	�	�	PROPN
ejpam-462	235	36	0.09	0.09	NUM
ejpam-462	235	37	0.05	0.05	NUM
ejpam-462	235	38	0.05	0.05	NUM
ejpam-462	235	39	0.04	0.04	NUM
ejpam-462	235	40	�	�	PROPN
ejpam-462	235	41	.	.	PUNCT
ejpam-462	236	1	note	note	VERB
ejpam-462	236	2	the	the	DET
ejpam-462	236	3	presence	presence	NOUN
ejpam-462	236	4	of	of	ADP
ejpam-462	236	5	correlation	correlation	NOUN
ejpam-462	236	6	between	between	ADP
ejpam-462	236	7	the	the	DET
ejpam-462	236	8	error	error	NOUN
ejpam-462	236	9	terms	term	NOUN
ejpam-462	236	10	we	we	PRON
ejpam-462	236	11	do	do	VERB
ejpam-462	236	12	this	this	PRON
ejpam-462	236	13	so	so	SCONJ
ejpam-462	236	14	as	as	SCONJ
ejpam-462	236	15	to	to	PART
ejpam-462	236	16	introduce	introduce	VERB
ejpam-462	236	17	some	some	DET
ejpam-462	236	18	extra	extra	ADJ
ejpam-462	236	19	difficulty	difficulty	NOUN
ejpam-462	236	20	into	into	ADP
ejpam-462	236	21	the	the	DET
ejpam-462	236	22	modeling	modeling	NOUN
ejpam-462	236	23	process	process	NOUN
ejpam-462	236	24	.	.	PUNCT
ejpam-462	237	1	each	each	DET
ejpam-462	237	2	simulation	simulation	NOUN
ejpam-462	237	3	is	be	AUX
ejpam-462	237	4	allowed	allow	VERB
ejpam-462	237	5	to	to	PART
ejpam-462	237	6	run	run	VERB
ejpam-462	237	7	for	for	ADP
ejpam-462	237	8	a	a	DET
ejpam-462	237	9	burn	burn	NOUN
ejpam-462	237	10	-	-	PUNCT
ejpam-462	237	11	in	in	ADP
ejpam-462	237	12	period	period	NOUN
ejpam-462	237	13	of	of	ADP
ejpam-462	237	14	1000	1000	NUM
ejpam-462	237	15	cycles	cycle	NOUN
ejpam-462	237	16	,	,	PUNCT
ejpam-462	237	17	which	which	PRON
ejpam-462	237	18	are	be	AUX
ejpam-462	237	19	subsequently	subsequently	ADV
ejpam-462	237	20	thrown	throw	VERB
ejpam-462	237	21	away	away	ADV
ejpam-462	237	22	before	before	ADP
ejpam-462	237	23	n	n	NOUN
ejpam-462	237	24	=	=	SYM
ejpam-462	237	25	200	200	NUM
ejpam-462	237	26	observations	observation	NOUN
ejpam-462	237	27	are	be	AUX
ejpam-462	237	28	saved	save	VERB
ejpam-462	237	29	.	.	PUNCT
ejpam-462	238	1	all	all	DET
ejpam-462	238	2	modeling	modeling	NOUN
ejpam-462	238	3	performed	perform	VERB
ejpam-462	238	4	with	with	ADP
ejpam-462	238	5	this	this	DET
ejpam-462	238	6	data	datum	NOUN
ejpam-462	238	7	was	be	AUX
ejpam-462	238	8	based	base	VERB
ejpam-462	238	9	on	on	ADP
ejpam-462	238	10	(	(	PUNCT
ejpam-462	238	11	1	1	NUM
ejpam-462	238	12	)	)	PUNCT
ejpam-462	238	13	with	with	ADP
ejpam-462	238	14	q	q	NOUN
ejpam-462	238	15	=	=	SYM
ejpam-462	238	16	4	4	NUM
ejpam-462	238	17	lags	lag	NOUN
ejpam-462	238	18	of	of	ADP
ejpam-462	238	19	both	both	DET
ejpam-462	238	20	variables	variable	NOUN
ejpam-462	238	21	;	;	PUNCT
ejpam-462	238	22	thus	thus	ADV
ejpam-462	238	23	there	there	PRON
ejpam-462	238	24	are	be	VERB
ejpam-462	238	25	218−1=	218−1=	NUM
ejpam-462	238	26	262,143	262,143	NUM
ejpam-462	238	27	potential	potential	ADJ
ejpam-462	238	28	nontrivial	nontrivial	NOUN
ejpam-462	238	29	subset	subset	NOUN
ejpam-462	238	30	models	model	NOUN
ejpam-462	238	31	.	.	PUNCT
ejpam-462	239	1	an	an	DET
ejpam-462	239	2	example	example	NOUN
ejpam-462	239	3	of	of	ADP
ejpam-462	239	4	one	one	NUM
ejpam-462	239	5	such	such	ADJ
ejpam-462	239	6	set	set	NOUN
ejpam-462	239	7	of	of	ADP
ejpam-462	239	8	simulated	simulate	VERB
ejpam-462	239	9	data	datum	NOUN
ejpam-462	239	10	can	can	AUX
ejpam-462	239	11	be	be	AUX
ejpam-462	239	12	seen	see	VERB
ejpam-462	239	13	in	in	ADP
ejpam-462	239	14	figure	figure	NOUN
ejpam-462	239	15	1	1	NUM
ejpam-462	239	16	.	.	PUNCT
ejpam-462	240	1	the	the	DET
ejpam-462	240	2	simulation	simulation	NOUN
ejpam-462	240	3	is	be	AUX
ejpam-462	240	4	clearly	clearly	ADV
ejpam-462	240	5	generating	generate	VERB
ejpam-462	240	6	stationary	stationary	ADJ
ejpam-462	240	7	data	datum	NOUN
ejpam-462	240	8	.	.	PUNCT
ejpam-462	241	1	to	to	PART
ejpam-462	241	2	demonstrate	demonstrate	VERB
ejpam-462	241	3	that	that	SCONJ
ejpam-462	241	4	this	this	PRON
ejpam-462	241	5	is	be	AUX
ejpam-462	241	6	not	not	PART
ejpam-462	241	7	necessarily	necessarily	ADV
ejpam-462	241	8	an	an	DET
ejpam-462	241	9	easy	easy	ADJ
ejpam-462	241	10	simulation	simulation	NOUN
ejpam-462	241	11	,	,	PUNCT
ejpam-462	241	12	we	we	PRON
ejpam-462	241	13	attempted	attempt	VERB
ejpam-462	241	14	to	to	ADP
ejpam-462	241	15	50	50	NUM
ejpam-462	241	16	100	100	NUM
ejpam-462	241	17	150	150	NUM
ejpam-462	241	18	200	200	NUM
ejpam-462	241	19	−0.5	−0.5	NUM
ejpam-462	241	20	0	0	NUM
ejpam-462	241	21	0.5	0.5	NUM
ejpam-462	241	22	1	1	NUM
ejpam-462	241	23	y	y	PROPN
ejpam-462	241	24	1	1	NUM
ejpam-462	241	25	50	50	NUM
ejpam-462	241	26	100	100	NUM
ejpam-462	241	27	150	150	NUM
ejpam-462	241	28	200	200	NUM
ejpam-462	241	29	−0.6	−0.6	PROPN
ejpam-462	241	30	−0.4	−0.4	PUNCT
ejpam-462	242	1	−0.2	−0.2	NOUN
ejpam-462	242	2	0	0	NUM
ejpam-462	242	3	0.2	0.2	NUM
ejpam-462	242	4	0.4	0.4	NUM
ejpam-462	242	5	0.6	0.6	NUM
ejpam-462	242	6	y	y	SYM
ejpam-462	242	7	2	2	NUM
ejpam-462	242	8	figure	figure	NOUN
ejpam-462	242	9	1	1	NUM
ejpam-462	242	10	:	:	PUNCT
ejpam-462	242	11	example	example	NOUN
ejpam-462	242	12	of	of	ADP
ejpam-462	242	13	simulated	simulated	ADJ
ejpam-462	242	14	var	var	NOUN
ejpam-462	242	15	data	data	PROPN
ejpam-462	242	16	.	.	PUNCT
ejpam-462	243	1	fit	fit	VERB
ejpam-462	243	2	a	a	DET
ejpam-462	243	3	subset	subset	ADJ
ejpam-462	243	4	model	model	NOUN
ejpam-462	243	5	of	of	ADP
ejpam-462	243	6	the	the	DET
ejpam-462	243	7	correct	correct	ADJ
ejpam-462	243	8	structure	structure	NOUN
ejpam-462	243	9	to	to	ADP
ejpam-462	243	10	one	one	NUM
ejpam-462	243	11	set	set	NOUN
ejpam-462	243	12	of	of	ADP
ejpam-462	243	13	observations	observation	NOUN
ejpam-462	243	14	.	.	PUNCT
ejpam-462	244	1	hence	hence	ADV
ejpam-462	244	2	we	we	PRON
ejpam-462	244	3	assume	assume	VERB
ejpam-462	244	4	some	some	DET
ejpam-462	244	5	a	a	DET
ejpam-462	244	6	priori	priori	ADJ
ejpam-462	244	7	knowledge	knowledge	NOUN
ejpam-462	244	8	of	of	ADP
ejpam-462	244	9	the	the	DET
ejpam-462	244	10	structure	structure	NOUN
ejpam-462	244	11	.	.	PUNCT
ejpam-462	245	1	the	the	DET
ejpam-462	245	2	ga	ga	PROPN
ejpam-462	245	3	string	string	NOUN
ejpam-462	245	4	for	for	ADP
ejpam-462	245	5	this	this	DET
ejpam-462	245	6	solution	solution	NOUN
ejpam-462	245	7	is	be	AUX
ejpam-462	245	8	[	[	X
ejpam-462	245	9	011110000011110000	011110000011110000	NUM
ejpam-462	245	10	]	]	PUNCT
ejpam-462	245	11	.	.	PUNCT
ejpam-462	246	1	this	this	PRON
ejpam-462	246	2	indicates	indicate	VERB
ejpam-462	246	3	that	that	SCONJ
ejpam-462	246	4	:	:	PUNCT
ejpam-462	246	5	all	all	DET
ejpam-462	246	6	3rd	3rd	ADJ
ejpam-462	246	7	and	and	CCONJ
ejpam-462	246	8	4th	4th	ADJ
ejpam-462	246	9	lags	lag	NOUN
ejpam-462	246	10	are	be	AUX
ejpam-462	246	11	restricted	restrict	VERB
ejpam-462	246	12	to	to	ADP
ejpam-462	246	13	0	0	NUM
ejpam-462	246	14	for	for	ADP
ejpam-462	246	15	each	each	DET
ejpam-462	246	16	variable	variable	NOUN
ejpam-462	246	17	,	,	PUNCT
ejpam-462	246	18	the	the	DET
ejpam-462	246	19	1st	1st	ADJ
ejpam-462	246	20	and	and	CCONJ
ejpam-462	246	21	2nd	2nd	ADJ
ejpam-462	246	22	lags	lag	NOUN
ejpam-462	246	23	are	be	AUX
ejpam-462	246	24	not	not	PART
ejpam-462	246	25	,	,	PUNCT
ejpam-462	246	26	and	and	CCONJ
ejpam-462	246	27	there	there	PRON
ejpam-462	246	28	is	be	VERB
ejpam-462	246	29	no	no	DET
ejpam-462	246	30	intercept	intercept	NOUN
ejpam-462	246	31	.	.	PUNCT
ejpam-462	247	1	we	we	PRON
ejpam-462	247	2	would	would	AUX
ejpam-462	247	3	like	like	VERB
ejpam-462	247	4	,	,	PUNCT
ejpam-462	247	5	of	of	ADP
ejpam-462	247	6	course	course	NOUN
ejpam-462	247	7	,	,	PUNCT
ejpam-462	247	8	to	to	PART
ejpam-462	247	9	see	see	VERB
ejpam-462	247	10	estimated	estimate	VERB
ejpam-462	247	11	parameter	parameter	PROPN
ejpam-462	247	12	a.	a.	NOUN
ejpam-462	247	13	howe	howe	PROPN
ejpam-462	247	14	and	and	CCONJ
ejpam-462	247	15	h.	h.	PROPN
ejpam-462	247	16	bozdogan	bozdogan	PROPN
ejpam-462	247	17	/	/	SYM
ejpam-462	247	18	eur	eur	PROPN
ejpam-462	247	19	.	.	PUNCT
ejpam-462	248	1	j.	j.	PROPN
ejpam-462	248	2	pure	pure	PROPN
ejpam-462	248	3	appl	appl	PROPN
ejpam-462	248	4	.	.	PROPN
ejpam-462	248	5	math	math	PROPN
ejpam-462	248	6	,	,	PUNCT
ejpam-462	248	7	3	3	NUM
ejpam-462	248	8	(	(	PUNCT
ejpam-462	248	9	2010	2010	NUM
ejpam-462	248	10	)	)	PUNCT
ejpam-462	248	11	,	,	PUNCT
ejpam-462	248	12	382	382	NUM
ejpam-462	248	13	-	-	SYM
ejpam-462	248	14	405	405	NUM
ejpam-462	248	15	393	393	NUM
ejpam-462	248	16	estimates	estimate	NOUN
ejpam-462	248	17	reasonably	reasonably	ADV
ejpam-462	248	18	close	close	ADJ
ejpam-462	248	19	to	to	ADP
ejpam-462	248	20	those	those	PRON
ejpam-462	248	21	shown	show	VERB
ejpam-462	248	22	above	above	ADP
ejpam-462	248	23	.	.	PUNCT
ejpam-462	249	1	the	the	DET
ejpam-462	249	2	fit	fit	NOUN
ejpam-462	249	3	was	be	AUX
ejpam-462	249	4	first	first	ADV
ejpam-462	249	5	performed	perform	VERB
ejpam-462	249	6	with	with	ADP
ejpam-462	249	7	n	n	NOUN
ejpam-462	249	8	=	=	SYM
ejpam-462	249	9	200	200	NUM
ejpam-462	249	10	observations	observation	NOUN
ejpam-462	249	11	,	,	PUNCT
ejpam-462	249	12	then	then	ADV
ejpam-462	249	13	with	with	ADP
ejpam-462	249	14	n	n	NOUN
ejpam-462	249	15	=	=	SYM
ejpam-462	249	16	1000	1000	NUM
ejpam-462	249	17	observations	observation	NOUN
ejpam-462	249	18	.	.	PUNCT
ejpam-462	250	1	as	as	SCONJ
ejpam-462	250	2	can	can	AUX
ejpam-462	250	3	be	be	AUX
ejpam-462	250	4	seen	see	VERB
ejpam-462	250	5	in	in	ADP
ejpam-462	250	6	table	table	NOUN
ejpam-462	250	7	3	3	NUM
ejpam-462	250	8	,	,	PUNCT
ejpam-462	250	9	many	many	ADJ
ejpam-462	250	10	of	of	ADP
ejpam-462	250	11	the	the	DET
ejpam-462	250	12	pa	pa	PROPN
ejpam-462	250	13	-	-	PUNCT
ejpam-462	250	14	table	table	NOUN
ejpam-462	250	15	3	3	NUM
ejpam-462	250	16	:	:	PUNCT
ejpam-462	250	17	estimated	estimate	VERB
ejpam-462	250	18	φ	φ	PROPN
ejpam-462	250	19	matri	matri	PROPN
ejpam-462	250	20	es	es	PROPN
ejpam-462	250	21	and	and	CCONJ
ejpam-462	250	22	relative	relative	ADJ
ejpam-462	250	23	errors	error	NOUN
ejpam-462	250	24	for	for	ADP
ejpam-462	250	25	di	di	NOUN
ejpam-462	250	26	�	�	PROPN
ejpam-462	250	27	erent	erent	NOUN
ejpam-462	250	28	n.	n.	NOUN
ejpam-462	250	29	n	n	CCONJ
ejpam-462	250	30	φ̂1	φ̂1	NOUN
ejpam-462	250	31	,	,	PUNCT
ejpam-462	250	32	|φ̂1−φ1|	|φ̂1−φ1|	PROPN
ejpam-462	250	33	φ1	φ1	NOUN
ejpam-462	250	34	%	%	NOUN
ejpam-462	250	35	φ̂2	φ̂2	PROPN
ejpam-462	250	36	,	,	PUNCT
ejpam-462	250	37	|φ̂2−φ2|	|φ̂2−φ2|	PROPN
ejpam-462	250	38	φ2	φ2	PROPN
ejpam-462	250	39	%	%	NOUN
ejpam-462	250	40	200	200	NUM
ejpam-462	250	41	�	�	NOUN
ejpam-462	250	42	−0.33	−0.33	PROPN
ejpam-462	250	43	0.13	0.13	NUM
ejpam-462	250	44	−0.62	−0.62	PROPN
ejpam-462	250	45	0.36	0.36	NUM
ejpam-462	250	46	�	�	PROPN
ejpam-462	250	47	,	,	PUNCT
ejpam-462	250	48	�	�	PROPN
ejpam-462	250	49	18.86	18.86	NUM
ejpam-462	250	50	493.02	493.02	NUM
ejpam-462	250	51	12.81	12.81	NUM
ejpam-462	250	52	25.33	25.33	NUM
ejpam-462	250	53	�	�	PROPN
ejpam-462	250	54	�	�	PROPN
ejpam-462	250	55	−0.15	−0.15	PROPN
ejpam-462	250	56	−0.50	−0.50	PROPN
ejpam-462	250	57	0.01	0.01	NUM
ejpam-462	250	58	0.22	0.22	NUM
ejpam-462	250	59	�	�	PROPN
ejpam-462	250	60	,	,	PUNCT
ejpam-462	250	61	�	�	PROPN
ejpam-462	250	62	46.14	46.14	NUM
ejpam-462	250	63	22.03	22.03	NUM
ejpam-462	250	64	147.92	147.92	NUM
ejpam-462	250	65	22.33	22.33	NUM
ejpam-462	250	66	�	�	PROPN
ejpam-462	250	67	1000	1000	NUM
ejpam-462	250	68	�	�	PROPN
ejpam-462	250	69	−0.32	−0.32	X
ejpam-462	250	70	0.084	0.084	NUM
ejpam-462	250	71	−0.58	−0.58	NUM
ejpam-462	250	72	0.33	0.33	NUM
ejpam-462	250	73	�	�	PROPN
ejpam-462	250	74	,	,	PUNCT
ejpam-462	250	75	�	�	PROPN
ejpam-462	250	76	13.04	13.04	NUM
ejpam-462	250	77	291.16	291.16	NUM
ejpam-462	250	78	5.26	5.26	NUM
ejpam-462	250	79	16.78	16.78	NUM
ejpam-462	250	80	�	�	PROPN
ejpam-462	250	81	�	�	PROPN
ejpam-462	251	1	−0.21	−0.21	PROPN
ejpam-462	251	2	−0.43	−0.43	NOUN
ejpam-462	251	3	0.05	0.05	NUM
ejpam-462	251	4	0.14	0.14	NUM
ejpam-462	251	5	�	�	PROPN
ejpam-462	251	6	,	,	PUNCT
ejpam-462	251	7	�	�	PROPN
ejpam-462	251	8	25.03	25.03	NUM
ejpam-462	251	9	4.43	4.43	NUM
ejpam-462	251	10	443.06	443.06	NUM
ejpam-462	251	11	21.17	21.17	NUM
ejpam-462	251	12	�	�	PROPN
ejpam-462	251	13	rameter	rameter	NOUN
ejpam-462	251	14	estimates	estimate	NOUN
ejpam-462	251	15	are	be	AUX
ejpam-462	251	16	quite	quite	ADV
ejpam-462	251	17	biased	biased	ADJ
ejpam-462	251	18	,	,	PUNCT
ejpam-462	251	19	even	even	ADV
ejpam-462	251	20	when	when	SCONJ
ejpam-462	251	21	many	many	ADJ
ejpam-462	251	22	observations	observation	NOUN
ejpam-462	251	23	were	be	AUX
ejpam-462	251	24	available	available	ADJ
ejpam-462	251	25	.	.	PUNCT
ejpam-462	252	1	next	next	ADV
ejpam-462	252	2	to	to	ADP
ejpam-462	252	3	each	each	DET
ejpam-462	252	4	estimated	estimate	VERB
ejpam-462	252	5	coefficient	coefficient	NOUN
ejpam-462	252	6	matrix	matrix	NOUN
ejpam-462	252	7	is	be	AUX
ejpam-462	252	8	a	a	DET
ejpam-462	252	9	matrix	matrix	NOUN
ejpam-462	252	10	showing	show	VERB
ejpam-462	252	11	the	the	DET
ejpam-462	252	12	percentage	percentage	NOUN
ejpam-462	252	13	deviation	deviation	NOUN
ejpam-462	252	14	from	from	ADP
ejpam-462	252	15	the	the	DET
ejpam-462	252	16	true	true	ADJ
ejpam-462	252	17	coefficient	coefficient	NOUN
ejpam-462	252	18	.	.	PUNCT
ejpam-462	253	1	with	with	ADP
ejpam-462	253	2	the	the	DET
ejpam-462	253	3	exception	exception	NOUN
ejpam-462	253	4	of	of	ADP
ejpam-462	253	5	the	the	DET
ejpam-462	253	6	bold	bold	ADJ
ejpam-462	253	7	element	element	NOUN
ejpam-462	253	8	,	,	PUNCT
ejpam-462	253	9	the	the	DET
ejpam-462	253	10	accuracy	accuracy	NOUN
ejpam-462	253	11	of	of	ADP
ejpam-462	253	12	the	the	DET
ejpam-462	253	13	estimates	estimate	NOUN
ejpam-462	253	14	improved	improve	VERB
ejpam-462	253	15	substantially	substantially	ADV
ejpam-462	253	16	when	when	SCONJ
ejpam-462	253	17	n	n	PROPN
ejpam-462	253	18	=	=	SYM
ejpam-462	253	19	1000	1000	NUM
ejpam-462	253	20	observations	observation	NOUN
ejpam-462	253	21	are	be	AUX
ejpam-462	253	22	used	use	VERB
ejpam-462	253	23	.	.	PUNCT
ejpam-462	254	1	this	this	PRON
ejpam-462	254	2	is	be	AUX
ejpam-462	254	3	clearly	clearly	ADV
ejpam-462	254	4	a	a	DET
ejpam-462	254	5	difficult	difficult	ADJ
ejpam-462	254	6	environment	environment	NOUN
ejpam-462	254	7	in	in	ADP
ejpam-462	254	8	which	which	PRON
ejpam-462	254	9	to	to	PART
ejpam-462	254	10	pick	pick	VERB
ejpam-462	254	11	a	a	DET
ejpam-462	254	12	good	good	ADJ
ejpam-462	254	13	model	model	NOUN
ejpam-462	254	14	.	.	PUNCT
ejpam-462	255	1	our	our	PRON
ejpam-462	255	2	first	first	ADJ
ejpam-462	255	3	set	set	NOUN
ejpam-462	255	4	of	of	ADP
ejpam-462	255	5	simulation	simulation	NOUN
ejpam-462	255	6	experiments	experiment	NOUN
ejpam-462	255	7	with	with	ADP
ejpam-462	255	8	this	this	DET
ejpam-462	255	9	data	data	NOUN
ejpam-462	255	10	generating	generating	NOUN
ejpam-462	255	11	process	process	NOUN
ejpam-462	255	12	involved	involve	VERB
ejpam-462	255	13	fitting	fit	VERB
ejpam-462	255	14	all	all	DET
ejpam-462	255	15	possible	possible	ADJ
ejpam-462	255	16	symmetric	symmetric	ADJ
ejpam-462	255	17	subset	subset	NOUN
ejpam-462	255	18	models	model	NOUN
ejpam-462	255	19	.	.	PUNCT
ejpam-462	256	1	we	we	PRON
ejpam-462	256	2	assume	assume	VERB
ejpam-462	256	3	that	that	SCONJ
ejpam-462	256	4	a	a	DET
ejpam-462	256	5	lag	lag	NOUN
ejpam-462	256	6	is	be	AUX
ejpam-462	256	7	included	include	VERB
ejpam-462	256	8	/	/	PUNCT
ejpam-462	256	9	excluded	exclude	VERB
ejpam-462	256	10	for	for	ADP
ejpam-462	256	11	both	both	DET
ejpam-462	256	12	responses	response	NOUN
ejpam-462	256	13	.	.	PUNCT
ejpam-462	257	1	with	with	ADP
ejpam-462	257	2	q	q	NOUN
ejpam-462	257	3	=	=	SYM
ejpam-462	257	4	18	18	NUM
ejpam-462	257	5	,	,	PUNCT
ejpam-462	257	6	this	this	PRON
ejpam-462	257	7	substantially	substantially	ADV
ejpam-462	257	8	reduces	reduce	VERB
ejpam-462	257	9	the	the	DET
ejpam-462	257	10	computational	computational	ADJ
ejpam-462	257	11	burden	burden	NOUN
ejpam-462	257	12	from	from	ADP
ejpam-462	257	13	262,143	262,143	NUM
ejpam-462	257	14	to	to	ADP
ejpam-462	257	15	511	511	NUM
ejpam-462	257	16	possible	possible	ADJ
ejpam-462	257	17	models	model	NOUN
ejpam-462	257	18	.	.	PUNCT
ejpam-462	258	1	in	in	ADP
ejpam-462	258	2	each	each	DET
ejpam-462	258	3	simulation	simulation	NOUN
ejpam-462	258	4	,	,	PUNCT
ejpam-462	258	5	five	five	NUM
ejpam-462	258	6	information	information	NOUN
ejpam-462	258	7	criteria	criterion	NOUN
ejpam-462	258	8	are	be	AUX
ejpam-462	258	9	computed	compute	VERB
ejpam-462	258	10	based	base	VERB
ejpam-462	258	11	on	on	ADP
ejpam-462	258	12	the	the	DET
ejpam-462	258	13	fgls	fgls	NOUN
ejpam-462	258	14	estimators	estimator	NOUN
ejpam-462	258	15	aic	aic	PROPN
ejpam-462	258	16	,	,	PUNCT
ejpam-462	258	17	sbc	sbc	PROPN
ejpam-462	258	18	,	,	PUNCT
ejpam-462	258	19	icom	icom	PROPN
ejpam-462	258	20	p	p	PROPN
ejpam-462	258	21	,	,	PUNCT
ejpam-462	258	22	icom	icom	PROPN
ejpam-462	258	23	pm	pm	VERB
ejpam-462	258	24	isp	isp	ADV
ejpam-462	258	25	,	,	PUNCT
ejpam-462	258	26	and	and	CCONJ
ejpam-462	258	27	icom	icom	PROPN
ejpam-462	258	28	ppeu	ppeu	PROPN
ejpam-462	258	29	.	.	PUNCT
ejpam-462	259	1	with	with	ADP
ejpam-462	259	2	no	no	DET
ejpam-462	259	3	desire	desire	NOUN
ejpam-462	259	4	to	to	PART
ejpam-462	259	5	“	"	PUNCT
ejpam-462	259	6	multiply	multiply	VERB
ejpam-462	259	7	hypotheses	hypothesis	NOUN
ejpam-462	259	8	more	more	ADJ
ejpam-462	259	9	than	than	ADP
ejpam-462	259	10	necessary”(william	necessary”(william	PROPN
ejpam-462	259	11	of	of	ADP
ejpam-462	259	12	occam	occam	PROPN
ejpam-462	259	13	)	)	PUNCT
ejpam-462	259	14	,	,	PUNCT
ejpam-462	259	15	robust	robust	ADJ
ejpam-462	259	16	covariance	covariance	NOUN
ejpam-462	259	17	estimation	estimation	NOUN
ejpam-462	259	18	was	be	AUX
ejpam-462	259	19	performed	perform	VERB
ejpam-462	259	20	with	with	ADP
ejpam-462	259	21	the	the	DET
ejpam-462	259	22	maximum	maximum	ADJ
ejpam-462	259	23	likelihood	likelihood	NOUN
ejpam-462	259	24	/	/	SYM
ejpam-462	259	25	empirical	empirical	ADJ
ejpam-462	259	26	bayes	bayes	PROPN
ejpam-462	259	27	estimator	estimator	NOUN
ejpam-462	259	28	in	in	ADP
ejpam-462	259	29	this	this	PRON
ejpam-462	259	30	and	and	CCONJ
ejpam-462	259	31	the	the	DET
ejpam-462	259	32	next	next	ADJ
ejpam-462	259	33	experiment	experiment	NOUN
ejpam-462	259	34	.	.	PUNCT
ejpam-462	260	1	table	table	NOUN
ejpam-462	260	2	4	4	NUM
ejpam-462	260	3	shows	show	VERB
ejpam-462	260	4	correct	correct	ADJ
ejpam-462	260	5	model	model	NOUN
ejpam-462	260	6	hit	hit	VERB
ejpam-462	260	7	rates	rate	NOUN
ejpam-462	260	8	and	and	CCONJ
ejpam-462	260	9	the	the	DET
ejpam-462	260	10	average	average	ADJ
ejpam-462	260	11	model	model	NOUN
ejpam-462	260	12	size	size	NOUN
ejpam-462	260	13	for	for	ADP
ejpam-462	260	14	n	n	NOUN
ejpam-462	260	15	=	=	SYM
ejpam-462	260	16	50	50	NUM
ejpam-462	260	17	,	,	PUNCT
ejpam-462	260	18	n=	n=	ADJ
ejpam-462	260	19	200	200	NUM
ejpam-462	260	20	,	,	PUNCT
ejpam-462	260	21	and	and	CCONJ
ejpam-462	260	22	n=	n=	ADJ
ejpam-462	260	23	500	500	NUM
ejpam-462	260	24	.	.	PUNCT
ejpam-462	261	1	clearly	clearly	ADV
ejpam-462	261	2	,	,	PUNCT
ejpam-462	261	3	the	the	DET
ejpam-462	261	4	performance	performance	NOUN
ejpam-462	261	5	of	of	ADP
ejpam-462	261	6	all	all	DET
ejpam-462	261	7	criteria	criterion	NOUN
ejpam-462	261	8	is	be	AUX
ejpam-462	261	9	rather	rather	ADV
ejpam-462	261	10	dismal	dismal	ADJ
ejpam-462	261	11	for	for	ADP
ejpam-462	261	12	the	the	DET
ejpam-462	261	13	smallesttable	smallesttable	NOUN
ejpam-462	261	14	4	4	NUM
ejpam-462	261	15	:	:	PUNCT
ejpam-462	261	16	model	model	NOUN
ejpam-462	261	17	hit	hit	VERB
ejpam-462	261	18	rates	rate	NOUN
ejpam-462	261	19	and	and	CCONJ
ejpam-462	261	20	average	average	ADJ
ejpam-462	261	21	subset	subset	NOUN
ejpam-462	261	22	model	model	NOUN
ejpam-462	261	23	sizes	size	NOUN
ejpam-462	261	24	(	(	PUNCT
ejpam-462	261	25	true	true	ADJ
ejpam-462	261	26	model	model	NOUN
ejpam-462	261	27	size	size	NOUN
ejpam-462	261	28	=	=	SYM
ejpam-462	261	29	4	4	NUM
ejpam-462	261	30	)	)	PUNCT
ejpam-462	261	31	.	.	PUNCT
ejpam-462	262	1	aic	aic	PROPN
ejpam-462	262	2	sbc	sbc	PROPN
ejpam-462	262	3	icomp	icomp	PROPN
ejpam-462	262	4	icom	icom	PROPN
ejpam-462	262	5	pm	pm	VERB
ejpam-462	262	6	isp	isp	ADV
ejpam-462	262	7	icom	icom	PROPN
ejpam-462	262	8	ppeu	ppeu	PROPN
ejpam-462	262	9	n=	n=	ADJ
ejpam-462	262	10	50	50	NUM
ejpam-462	262	11	hit	hit	NOUN
ejpam-462	262	12	rate	rate	NOUN
ejpam-462	262	13	(	(	PUNCT
ejpam-462	262	14	%	%	INTJ
ejpam-462	262	15	)	)	PUNCT
ejpam-462	262	16	18.5	18.5	NUM
ejpam-462	262	17	13.8	13.8	NUM
ejpam-462	262	18	13.1	13.1	NUM
ejpam-462	262	19	2.7	2.7	NUM
ejpam-462	262	20	12.1	12.1	NUM
ejpam-462	262	21	average	average	ADJ
ejpam-462	262	22	size	size	NOUN
ejpam-462	262	23	4.24	4.24	NUM
ejpam-462	262	24	2.96	2.96	NUM
ejpam-462	262	25	3.96	3.96	NUM
ejpam-462	262	26	2.45	2.45	NUM
ejpam-462	262	27	3.27	3.27	NUM
ejpam-462	262	28	n=	n=	ADJ
ejpam-462	262	29	200	200	NUM
ejpam-462	262	30	hit	hit	NOUN
ejpam-462	262	31	rate	rate	NOUN
ejpam-462	262	32	(	(	PUNCT
ejpam-462	262	33	%	%	NOUN
ejpam-462	262	34	)	)	PUNCT
ejpam-462	262	35	49.5	49.5	NUM
ejpam-462	262	36	87.90	87.90	NUM
ejpam-462	262	37	59.80	59.80	NUM
ejpam-462	262	38	84.8	84.8	NUM
ejpam-462	262	39	77.6	77.6	NUM
ejpam-462	262	40	average	average	ADJ
ejpam-462	262	41	size	size	NOUN
ejpam-462	262	42	4.67	4.67	NUM
ejpam-462	262	43	3.95	3.95	NUM
ejpam-462	262	44	4.46	4.46	NUM
ejpam-462	262	45	3.99	3.99	NUM
ejpam-462	262	46	4.13	4.13	NUM
ejpam-462	262	47	n=	n=	ADJ
ejpam-462	262	48	500	500	NUM
ejpam-462	262	49	hit	hit	NOUN
ejpam-462	262	50	rate	rate	NOUN
ejpam-462	262	51	(	(	PUNCT
ejpam-462	262	52	%	%	NOUN
ejpam-462	262	53	)	)	PUNCT
ejpam-462	262	54	49.7	49.7	NUM
ejpam-462	262	55	99.2	99.2	NUM
ejpam-462	262	56	62.0	62.0	NUM
ejpam-462	262	57	94.7	94.7	NUM
ejpam-462	262	58	84.8	84.8	NUM
ejpam-462	262	59	average	average	ADJ
ejpam-462	262	60	size	size	NOUN
ejpam-462	262	61	4.68	4.68	NUM
ejpam-462	262	62	4.01	4.01	NUM
ejpam-462	262	63	4.49	4.49	NUM
ejpam-462	262	64	4.05	4.05	NUM
ejpam-462	262	65	4.17	4.17	NUM
ejpam-462	262	66	sample	sample	NOUN
ejpam-462	262	67	size	size	NOUN
ejpam-462	262	68	evaluated	evaluate	VERB
ejpam-462	262	69	.	.	PUNCT
ejpam-462	263	1	as	as	ADP
ejpam-462	263	2	n	n	PRON
ejpam-462	263	3	increases	increase	NOUN
ejpam-462	263	4	,	,	PUNCT
ejpam-462	263	5	we	we	PRON
ejpam-462	263	6	observe	observe	VERB
ejpam-462	263	7	the	the	DET
ejpam-462	263	8	consistency	consistency	NOUN
ejpam-462	263	9	of	of	ADP
ejpam-462	263	10	aic	aic	PROPN
ejpam-462	263	11	picking	pick	VERB
ejpam-462	263	12	the	the	DET
ejpam-462	263	13	correct	correct	ADJ
ejpam-462	263	14	model	model	NOUN
ejpam-462	263	15	less	less	ADJ
ejpam-462	263	16	than	than	ADP
ejpam-462	263	17	50	50	NUM
ejpam-462	263	18	%	%	NOUN
ejpam-462	263	19	of	of	ADP
ejpam-462	263	20	the	the	DET
ejpam-462	263	21	time	time	NOUN
ejpam-462	263	22	,	,	PUNCT
ejpam-462	263	23	as	as	ADV
ejpam-462	263	24	well	well	ADV
ejpam-462	263	25	as	as	ADP
ejpam-462	263	26	the	the	DET
ejpam-462	263	27	tendency	tendency	NOUN
ejpam-462	263	28	to	to	PART
ejpam-462	263	29	pick	pick	VERB
ejpam-462	263	30	overly	overly	ADV
ejpam-462	263	31	complex	complex	ADJ
ejpam-462	263	32	models	model	NOUN
ejpam-462	263	33	.	.	PUNCT
ejpam-462	264	1	the	the	DET
ejpam-462	264	2	icom	icom	PROPN
ejpam-462	264	3	p	p	PROPN
ejpam-462	264	4	with	with	ADP
ejpam-462	264	5	neither	neither	CCONJ
ejpam-462	264	6	the	the	DET
ejpam-462	264	7	heavier	heavy	ADJ
ejpam-462	264	8	penalty	penalty	NOUN
ejpam-462	264	9	nor	nor	CCONJ
ejpam-462	264	10	the	the	DET
ejpam-462	264	11	misspecification	misspecification	NOUN
ejpam-462	264	12	adjustment	adjustment	NOUN
ejpam-462	264	13	is	be	AUX
ejpam-462	264	14	the	the	DET
ejpam-462	264	15	2nd	2nd	ADJ
ejpam-462	264	16	a.	a.	NOUN
ejpam-462	264	17	howe	howe	NOUN
ejpam-462	264	18	and	and	CCONJ
ejpam-462	264	19	h.	h.	PROPN
ejpam-462	264	20	bozdogan	bozdogan	PROPN
ejpam-462	264	21	/	/	SYM
ejpam-462	264	22	eur	eur	PROPN
ejpam-462	264	23	.	.	PUNCT
ejpam-462	265	1	j.	j.	PROPN
ejpam-462	265	2	pure	pure	PROPN
ejpam-462	265	3	appl	appl	PROPN
ejpam-462	265	4	.	.	PROPN
ejpam-462	265	5	math	math	PROPN
ejpam-462	265	6	,	,	PUNCT
ejpam-462	265	7	3	3	NUM
ejpam-462	265	8	(	(	PUNCT
ejpam-462	265	9	2010	2010	NUM
ejpam-462	265	10	)	)	PUNCT
ejpam-462	265	11	,	,	PUNCT
ejpam-462	265	12	382	382	NUM
ejpam-462	265	13	-	-	SYM
ejpam-462	265	14	405	405	NUM
ejpam-462	265	15	394	394	NUM
ejpam-462	265	16	worst	bad	ADJ
ejpam-462	265	17	performer	performer	NOUN
ejpam-462	265	18	and	and	CCONJ
ejpam-462	265	19	also	also	ADV
ejpam-462	265	20	exhibits	exhibit	VERB
ejpam-462	265	21	a	a	DET
ejpam-462	265	22	tendency	tendency	NOUN
ejpam-462	265	23	to	to	PART
ejpam-462	265	24	overfit	overfit	VERB
ejpam-462	265	25	.	.	PUNCT
ejpam-462	266	1	both	both	PRON
ejpam-462	266	2	sbc	sbc	PROPN
ejpam-462	266	3	and	and	CCONJ
ejpam-462	266	4	icom	icom	PROPN
ejpam-462	266	5	pm	pm	VERB
ejpam-462	266	6	isp	isp	ADV
ejpam-462	266	7	,	,	PUNCT
ejpam-462	266	8	however	however	ADV
ejpam-462	266	9	,	,	PUNCT
ejpam-462	266	10	perform	perform	VERB
ejpam-462	266	11	very	very	ADV
ejpam-462	266	12	well	well	ADV
ejpam-462	266	13	,	,	PUNCT
ejpam-462	266	14	picking	pick	VERB
ejpam-462	266	15	the	the	DET
ejpam-462	266	16	correct	correct	ADJ
ejpam-462	266	17	model	model	NOUN
ejpam-462	266	18	with	with	ADP
ejpam-462	266	19	very	very	ADV
ejpam-462	266	20	high	high	ADJ
ejpam-462	266	21	frequencies	frequency	NOUN
ejpam-462	266	22	,	,	PUNCT
ejpam-462	266	23	and	and	CCONJ
ejpam-462	266	24	exhibiting	exhibit	VERB
ejpam-462	266	25	no	no	DET
ejpam-462	266	26	tendency	tendency	NOUN
ejpam-462	266	27	to	to	PART
ejpam-462	266	28	overfit	overfit	VERB
ejpam-462	266	29	.	.	PUNCT
ejpam-462	267	1	the	the	DET
ejpam-462	267	2	strong	strong	ADJ
ejpam-462	267	3	performance	performance	NOUN
ejpam-462	267	4	of	of	ADP
ejpam-462	267	5	icom	icom	PROPN
ejpam-462	267	6	pm	pm	VERB
ejpam-462	267	7	isp	isp	ADV
ejpam-462	267	8	is	be	AUX
ejpam-462	267	9	of	of	ADP
ejpam-462	267	10	particular	particular	ADJ
ejpam-462	267	11	interest	interest	NOUN
ejpam-462	267	12	.	.	PUNCT
ejpam-462	268	1	recall	recall	VERB
ejpam-462	268	2	that	that	SCONJ
ejpam-462	268	3	the	the	DET
ejpam-462	268	4	error	error	NOUN
ejpam-462	268	5	terms	term	NOUN
ejpam-462	268	6	were	be	AUX
ejpam-462	268	7	generated	generate	VERB
ejpam-462	268	8	as	as	ADP
ejpam-462	268	9	homoskedastic	homoskedastic	ADJ
ejpam-462	268	10	multivariate	multivariate	NOUN
ejpam-462	268	11	gaussian	gaussian	NOUN
ejpam-462	268	12	noise	noise	NOUN
ejpam-462	268	13	with	with	ADP
ejpam-462	268	14	only	only	ADJ
ejpam-462	268	15	slight	slight	ADJ
ejpam-462	268	16	correlation	correlation	NOUN
ejpam-462	268	17	.	.	PUNCT
ejpam-462	269	1	thus	thus	ADV
ejpam-462	269	2	,	,	PUNCT
ejpam-462	269	3	we	we	PRON
ejpam-462	269	4	would	would	AUX
ejpam-462	269	5	expect	expect	VERB
ejpam-462	269	6	the	the	DET
ejpam-462	269	7	model	model	NOUN
ejpam-462	269	8	to	to	PART
ejpam-462	269	9	be	be	AUX
ejpam-462	269	10	correctly	correctly	ADV
ejpam-462	269	11	specified	specify	VERB
ejpam-462	269	12	.	.	PUNCT
ejpam-462	270	1	however	however	ADV
ejpam-462	270	2	,	,	PUNCT
ejpam-462	270	3	what	what	PRON
ejpam-462	270	4	we	we	PRON
ejpam-462	270	5	observe	observe	VERB
ejpam-462	270	6	here	here	ADV
ejpam-462	270	7	suggests	suggest	VERB
ejpam-462	270	8	something	something	PRON
ejpam-462	270	9	very	very	ADV
ejpam-462	270	10	interesting	interesting	ADJ
ejpam-462	270	11	:	:	PUNCT
ejpam-462	270	12	model	model	ADJ
ejpam-462	270	13	misspecification	misspecification	NOUN
ejpam-462	270	14	comes	come	VERB
ejpam-462	270	15	automatically	automatically	ADV
ejpam-462	270	16	with	with	ADP
ejpam-462	270	17	•	•	NOUN
ejpam-462	270	18	even	even	ADV
ejpam-462	270	19	slight	slight	ADJ
ejpam-462	270	20	correlation	correlation	NOUN
ejpam-462	270	21	of	of	ADP
ejpam-462	270	22	errors	error	NOUN
ejpam-462	270	23	•	•	ADP
ejpam-462	270	24	high	high	ADJ
ejpam-462	270	25	dimensionality	dimensionality	NOUN
ejpam-462	270	26	−→	−→	NOUN
ejpam-462	270	27	overparameterization	overparameterization	NOUN
ejpam-462	270	28	•	•	NOUN
ejpam-462	270	29	multicollinearity	multicollinearity	NOUN
ejpam-462	270	30	inherent	inherent	ADJ
ejpam-462	270	31	in	in	ADP
ejpam-462	270	32	time	time	NOUN
ejpam-462	270	33	series	series	PROPN
ejpam-462	270	34	data	data	VERB
ejpam-462	270	35	more	more	ADV
ejpam-462	270	36	on	on	ADP
ejpam-462	270	37	this	this	DET
ejpam-462	270	38	later	later	ADV
ejpam-462	270	39	.	.	PUNCT
ejpam-462	271	1	for	for	ADP
ejpam-462	271	2	our	our	PRON
ejpam-462	271	3	second	second	ADJ
ejpam-462	271	4	experiment	experiment	NOUN
ejpam-462	271	5	with	with	ADP
ejpam-462	271	6	this	this	DET
ejpam-462	271	7	simulation	simulation	NOUN
ejpam-462	271	8	protocol	protocol	NOUN
ejpam-462	271	9	,	,	PUNCT
ejpam-462	271	10	we	we	PRON
ejpam-462	271	11	performed	perform	VERB
ejpam-462	271	12	100	100	NUM
ejpam-462	271	13	monte	monte	PROPN
ejpam-462	271	14	carlo	carlo	NOUN
ejpam-462	271	15	simulations	simulation	NOUN
ejpam-462	271	16	of	of	ADP
ejpam-462	271	17	the	the	DET
ejpam-462	271	18	entire	entire	ADJ
ejpam-462	271	19	modeling	modeling	NOUN
ejpam-462	271	20	process	process	NOUN
ejpam-462	271	21	,	,	PUNCT
ejpam-462	271	22	using	use	VERB
ejpam-462	271	23	the	the	DET
ejpam-462	271	24	simpler	simple	ADJ
ejpam-462	271	25	form	form	NOUN
ejpam-462	271	26	of	of	ADP
ejpam-462	271	27	icom	icom	PROPN
ejpam-462	271	28	p	p	PROPN
ejpam-462	271	29	,	,	PUNCT
ejpam-462	271	30	shown	show	VERB
ejpam-462	271	31	in	in	ADP
ejpam-462	271	32	(	(	PUNCT
ejpam-462	271	33	11	11	NUM
ejpam-462	271	34	)	)	PUNCT
ejpam-462	271	35	.	.	PUNCT
ejpam-462	272	1	the	the	DET
ejpam-462	272	2	best	good	ADJ
ejpam-462	272	3	5	5	NUM
ejpam-462	272	4	subset	subset	NOUN
ejpam-462	272	5	models	model	NOUN
ejpam-462	272	6	selected	select	VERB
ejpam-462	272	7	by	by	ADP
ejpam-462	272	8	the	the	DET
ejpam-462	272	9	genetic	genetic	ADJ
ejpam-462	272	10	algorithm	algorithm	NOUN
ejpam-462	272	11	shared	share	VERB
ejpam-462	272	12	remarkable	remarkable	ADJ
ejpam-462	272	13	similarities	similarity	NOUN
ejpam-462	272	14	in	in	ADP
ejpam-462	272	15	structures	structure	NOUN
ejpam-462	272	16	and	and	CCONJ
ejpam-462	272	17	parsimony	parsimony	NOUN
ejpam-462	272	18	.	.	PUNCT
ejpam-462	273	1	none	none	NOUN
ejpam-462	273	2	selected	select	VERB
ejpam-462	273	3	an	an	DET
ejpam-462	273	4	intercept	intercept	NOUN
ejpam-462	273	5	for	for	ADP
ejpam-462	273	6	the	the	DET
ejpam-462	273	7	model	model	NOUN
ejpam-462	273	8	,	,	PUNCT
ejpam-462	273	9	and	and	CCONJ
ejpam-462	273	10	all	all	PRON
ejpam-462	273	11	restricted	restrict	VERB
ejpam-462	273	12	most	most	ADJ
ejpam-462	273	13	elements	element	NOUN
ejpam-462	273	14	of	of	ADP
ejpam-462	273	15	φ̂3	φ̂3	PROPN
ejpam-462	273	16	and	and	CCONJ
ejpam-462	273	17	φ̂4	φ̂4	PRON
ejpam-462	273	18	to	to	PART
ejpam-462	273	19	be	be	AUX
ejpam-462	273	20	0	0	NUM
ejpam-462	273	21	in	in	ADP
ejpam-462	273	22	the	the	DET
ejpam-462	273	23	interest	interest	NOUN
ejpam-462	273	24	of	of	ADP
ejpam-462	273	25	space	space	NOUN
ejpam-462	273	26	,	,	PUNCT
ejpam-462	273	27	only	only	ADV
ejpam-462	273	28	the	the	DET
ejpam-462	273	29	first	first	ADJ
ejpam-462	273	30	two	two	NUM
ejpam-462	273	31	terms	term	NOUN
ejpam-462	273	32	are	be	AUX
ejpam-462	273	33	shown	show	VERB
ejpam-462	273	34	in	in	ADP
ejpam-462	273	35	table	table	NOUN
ejpam-462	273	36	5	5	NUM
ejpam-462	273	37	.	.	PUNCT
ejpam-462	274	1	out	out	ADP
ejpam-462	274	2	of	of	ADP
ejpam-462	274	3	these	these	DET
ejpam-462	274	4	top	top	ADJ
ejpam-462	274	5	five	five	NUM
ejpam-462	274	6	models	model	NOUN
ejpam-462	274	7	.	.	PUNCT
ejpam-462	275	1	it	it	PRON
ejpam-462	275	2	is	be	AUX
ejpam-462	275	3	interesting	interesting	ADJ
ejpam-462	275	4	to	to	PART
ejpam-462	275	5	note	note	VERB
ejpam-462	275	6	that	that	SCONJ
ejpam-462	275	7	there	there	PRON
ejpam-462	275	8	was	be	VERB
ejpam-462	275	9	substantially	substantially	ADV
ejpam-462	275	10	more	more	ADJ
ejpam-462	275	11	confusion	confusion	NOUN
ejpam-462	275	12	in	in	ADP
ejpam-462	275	13	the	the	DET
ejpam-462	275	14	estimates	estimate	NOUN
ejpam-462	275	15	for	for	ADP
ejpam-462	275	16	the	the	DET
ejpam-462	275	17	φ̂2	φ̂2	PROPN
ejpam-462	275	18	matrices	matrix	NOUN
ejpam-462	275	19	,	,	PUNCT
ejpam-462	275	20	despite	despite	SCONJ
ejpam-462	275	21	the	the	DET
ejpam-462	275	22	fact	fact	NOUN
ejpam-462	275	23	that	that	SCONJ
ejpam-462	275	24	the	the	DET
ejpam-462	275	25	true	true	ADJ
ejpam-462	275	26	variance	variance	NOUN
ejpam-462	275	27	of	of	ADP
ejpam-462	275	28	the	the	DET
ejpam-462	275	29	error	error	NOUN
ejpam-462	275	30	term	term	NOUN
ejpam-462	275	31	on	on	ADP
ejpam-462	275	32	this	this	DET
ejpam-462	275	33	component	component	NOUN
ejpam-462	275	34	was	be	AUX
ejpam-462	275	35	the	the	DET
ejpam-462	275	36	smaller	small	ADJ
ejpam-462	275	37	of	of	ADP
ejpam-462	275	38	the	the	DET
ejpam-462	275	39	two	two	NUM
ejpam-462	275	40	.	.	PUNCT
ejpam-462	276	1	here	here	ADV
ejpam-462	276	2	we’vetable	we’vetable	ADJ
ejpam-462	276	3	5	5	NUM
ejpam-462	276	4	:	:	PUNCT
ejpam-462	276	5	top	top	ADJ
ejpam-462	276	6	five	five	NUM
ejpam-462	276	7	models	model	NOUN
ejpam-462	276	8	as	as	SCONJ
ejpam-462	276	9	sele	sele	PROPN
ejpam-462	276	10	ted	te	VERB
ejpam-462	276	11	by	by	ADP
ejpam-462	276	12	the	the	DET
ejpam-462	276	13	ga	ga	PROPN
ejpam-462	276	14	with	with	ADP
ejpam-462	276	15	icom	icom	PROPN
ejpam-462	276	16	p.	p.	PROPN
ejpam-462	276	17	φ̂1	φ̂1	PROPN
ejpam-462	276	18	φ̂2	φ̂2	PROPN
ejpam-462	276	19	score	score	NOUN
ejpam-462	276	20	%	%	NOUN
ejpam-462	276	21	reduction	reduction	NOUN
ejpam-462	276	22	1	1	NUM
ejpam-462	276	23	�	�	NOUN
ejpam-462	276	24	−0.230	−0.230	VERB
ejpam-462	276	25	·	·	PUNCT
ejpam-462	276	26	−0.466	−0.466	NUM
ejpam-462	276	27	0.245	0.245	NUM
ejpam-462	276	28	�	�	PROPN
ejpam-462	276	29	�	�	PROPN
ejpam-462	277	1	−0.247	−0.247	PROPN
ejpam-462	277	2	−0.525	−0.525	NOUN
ejpam-462	277	3	0.071	0.071	NUM
ejpam-462	277	4	·	·	PUNCT
ejpam-462	277	5	�	�	PROPN
ejpam-462	277	6	−299.83	−299.83	PROPN
ejpam-462	277	7	(	(	PUNCT
ejpam-462	277	8	−272.85	−272.85	PROPN
ejpam-462	277	9	)	)	PUNCT
ejpam-462	277	10	61.1	61.1	NUM
ejpam-462	277	11	(	(	PUNCT
ejpam-462	277	12	9.9	9.9	NUM
ejpam-462	277	13	)	)	SYM
ejpam-462	277	14	2	2	NUM
ejpam-462	277	15	�	�	PROPN
ejpam-462	277	16	−0.120	−0.120	X
ejpam-462	277	17	·	·	PUNCT
ejpam-462	277	18	−0.472	−0.472	NOUN
ejpam-462	277	19	0.327	0.327	NUM
ejpam-462	277	20	�	�	PROPN
ejpam-462	277	21	�	�	PROPN
ejpam-462	277	22	−0.166	−0.166	PROPN
ejpam-462	277	23	−0.486	−0.486	PROPN
ejpam-462	277	24	0.118	0.118	NUM
ejpam-462	277	25	·	·	PUNCT
ejpam-462	277	26	�	�	PROPN
ejpam-462	277	27	−295.08	−295.08	PROPN
ejpam-462	277	28	(	(	PUNCT
ejpam-462	277	29	−272.35	−272.35	NOUN
ejpam-462	277	30	)	)	PUNCT
ejpam-462	277	31	44.5	44.5	NUM
ejpam-462	277	32	(	(	PUNCT
ejpam-462	277	33	8.3	8.3	NUM
ejpam-462	277	34	)	)	SYM
ejpam-462	277	35	3	3	NUM
ejpam-462	277	36	�	�	PROPN
ejpam-462	277	37	−0.281	−0.281	PROPN
ejpam-462	277	38	·	·	PUNCT
ejpam-462	277	39	−0.560	−0.560	PROPN
ejpam-462	277	40	0.327	0.327	NUM
ejpam-462	277	41	�	�	PROPN
ejpam-462	277	42	�	�	PROPN
ejpam-462	277	43	−0.339	−0.339	PROPN
ejpam-462	277	44	−0.369	−0.369	PROPN
ejpam-462	277	45	·	·	PUNCT
ejpam-462	277	46	0.142	0.142	NUM
ejpam-462	277	47	�	�	PROPN
ejpam-462	277	48	−286.94	−286.94	PROPN
ejpam-462	277	49	(	(	PUNCT
ejpam-462	277	50	−257.26	−257.26	ADJ
ejpam-462	277	51	)	)	PUNCT
ejpam-462	277	52	61.1	61.1	NUM
ejpam-462	277	53	(	(	PUNCT
ejpam-462	277	54	11.5	11.5	NUM
ejpam-462	277	55	)	)	PUNCT
ejpam-462	277	56	4	4	NUM
ejpam-462	277	57	�	�	PROPN
ejpam-462	277	58	−0.276	−0.276	PROPN
ejpam-462	277	59	·	·	PUNCT
ejpam-462	277	60	−0.511	−0.511	NOUN
ejpam-462	277	61	0.194	0.194	NUM
ejpam-462	277	62	�	�	PROPN
ejpam-462	277	63	�	�	PROPN
ejpam-462	277	64	−0.230	−0.230	VERB
ejpam-462	277	65	−0.529	−0.529	ADV
ejpam-462	277	66	·	·	PUNCT
ejpam-462	277	67	0.167	0.167	NUM
ejpam-462	277	68	�	�	PROPN
ejpam-462	277	69	−284.28	−284.28	X
ejpam-462	277	70	(	(	PUNCT
ejpam-462	277	71	−256.56	−256.56	PROPN
ejpam-462	277	72	)	)	PUNCT
ejpam-462	277	73	61.1	61.1	NUM
ejpam-462	277	74	(	(	PUNCT
ejpam-462	277	75	10.8	10.8	NUM
ejpam-462	277	76	)	)	PUNCT
ejpam-462	277	77	5	5	NUM
ejpam-462	277	78	�	�	PROPN
ejpam-462	277	79	−0.274	−0.274	NOUN
ejpam-462	277	80	·	·	PUNCT
ejpam-462	277	81	−0.553	−0.553	NOUN
ejpam-462	277	82	0.352	0.352	NUM
ejpam-462	277	83	�	�	PROPN
ejpam-462	277	84	�	�	PROPN
ejpam-462	277	85	−0.223	−0.223	PROPN
ejpam-462	277	86	−0.633	−0.633	NOUN
ejpam-462	277	87	0.090	0.090	NUM
ejpam-462	277	88	·	·	PUNCT
ejpam-462	277	89	�	�	PROPN
ejpam-462	277	90	−266.46	−266.46	NOUN
ejpam-462	277	91	(	(	PUNCT
ejpam-462	277	92	−240.98	−240.98	PROPN
ejpam-462	277	93	)	)	PUNCT
ejpam-462	277	94	61.1	61.1	NUM
ejpam-462	277	95	(	(	PUNCT
ejpam-462	277	96	10.6	10.6	NUM
ejpam-462	277	97	)	)	PUNCT
ejpam-462	277	98	identified	identify	VERB
ejpam-462	277	99	,	,	PUNCT
ejpam-462	277	100	in	in	ADP
ejpam-462	277	101	the	the	DET
ejpam-462	277	102	4th	4th	ADJ
ejpam-462	277	103	column	column	NOUN
ejpam-462	277	104	,	,	PUNCT
ejpam-462	277	105	the	the	DET
ejpam-462	277	106	score	score	NOUN
ejpam-462	277	107	for	for	ADP
ejpam-462	277	108	both	both	PRON
ejpam-462	277	109	the	the	DET
ejpam-462	277	110	subset	subset	NOUN
ejpam-462	277	111	model	model	NOUN
ejpam-462	277	112	and	and	CCONJ
ejpam-462	277	113	the	the	DET
ejpam-462	277	114	corresponding	corresponding	ADJ
ejpam-462	277	115	saturated	saturated	ADJ
ejpam-462	277	116	model	model	NOUN
ejpam-462	277	117	the	the	DET
ejpam-462	277	118	latter	latter	ADJ
ejpam-462	277	119	in	in	ADP
ejpam-462	277	120	parentheses	parenthesis	NOUN
ejpam-462	277	121	.	.	PUNCT
ejpam-462	278	1	the	the	DET
ejpam-462	278	2	final	final	ADJ
ejpam-462	278	3	column	column	NOUN
ejpam-462	278	4	identifies	identify	VERB
ejpam-462	278	5	the	the	DET
ejpam-462	278	6	percentage	percentage	NOUN
ejpam-462	278	7	by	by	ADP
ejpam-462	278	8	which	which	PRON
ejpam-462	278	9	the	the	DET
ejpam-462	278	10	model	model	NOUN
ejpam-462	278	11	complexity	complexity	NOUN
ejpam-462	278	12	was	be	AUX
ejpam-462	278	13	reduced	reduce	VERB
ejpam-462	278	14	both	both	CCONJ
ejpam-462	278	15	in	in	ADP
ejpam-462	278	16	terms	term	NOUN
ejpam-462	278	17	of	of	ADP
ejpam-462	278	18	the	the	DET
ejpam-462	278	19	parameter	parameter	NOUN
ejpam-462	278	20	space	space	NOUN
ejpam-462	278	21	and	and	CCONJ
ejpam-462	278	22	the	the	DET
ejpam-462	278	23	information	information	NOUN
ejpam-462	278	24	complexity	complexity	NOUN
ejpam-462	278	25	,	,	PUNCT
ejpam-462	278	26	respectively	respectively	ADV
ejpam-462	278	27	.	.	PUNCT
ejpam-462	279	1	with	with	ADP
ejpam-462	279	2	a	a	DET
ejpam-462	279	3	relatively	relatively	ADV
ejpam-462	279	4	modest	modest	ADJ
ejpam-462	279	5	reduction	reduction	NOUN
ejpam-462	279	6	in	in	ADP
ejpam-462	279	7	the	the	DET
ejpam-462	279	8	information	information	NOUN
ejpam-462	279	9	a.	a.	NOUN
ejpam-462	279	10	howe	howe	PROPN
ejpam-462	279	11	and	and	CCONJ
ejpam-462	279	12	h.	h.	PROPN
ejpam-462	279	13	bozdogan	bozdogan	PROPN
ejpam-462	279	14	/	/	SYM
ejpam-462	279	15	eur	eur	PROPN
ejpam-462	279	16	.	.	PUNCT
ejpam-462	280	1	j.	j.	PROPN
ejpam-462	280	2	pure	pure	PROPN
ejpam-462	280	3	appl	appl	PROPN
ejpam-462	280	4	.	.	PROPN
ejpam-462	280	5	math	math	PROPN
ejpam-462	280	6	,	,	PUNCT
ejpam-462	280	7	3	3	NUM
ejpam-462	280	8	(	(	PUNCT
ejpam-462	280	9	2010	2010	NUM
ejpam-462	280	10	)	)	PUNCT
ejpam-462	280	11	,	,	PUNCT
ejpam-462	280	12	382	382	NUM
ejpam-462	280	13	-	-	SYM
ejpam-462	280	14	405	405	NUM
ejpam-462	280	15	395	395	NUM
ejpam-462	280	16	criteria	criterion	NOUN
ejpam-462	280	17	score	score	NOUN
ejpam-462	280	18	,	,	PUNCT
ejpam-462	280	19	we	we	PRON
ejpam-462	280	20	obtained	obtain	VERB
ejpam-462	280	21	greatly	greatly	ADV
ejpam-462	280	22	simplified	simplify	VERB
ejpam-462	280	23	models	model	NOUN
ejpam-462	280	24	.	.	PUNCT
ejpam-462	281	1	though	though	SCONJ
ejpam-462	281	2	not	not	PART
ejpam-462	281	3	shown	show	VERB
ejpam-462	281	4	here	here	ADV
ejpam-462	281	5	,	,	PUNCT
ejpam-462	281	6	both	both	CCONJ
ejpam-462	281	7	the	the	DET
ejpam-462	281	8	subsettable	subsettable	ADJ
ejpam-462	281	9	6	6	NUM
ejpam-462	281	10	:	:	PUNCT
ejpam-462	281	11	mean	mean	NOUN
ejpam-462	281	12	squared	square	VERB
ejpam-462	281	13	errors	error	NOUN
ejpam-462	281	14	for	for	ADP
ejpam-462	281	15	simulated	simulated	ADJ
ejpam-462	281	16	data	datum	NOUN
ejpam-462	281	17	.	.	PUNCT
ejpam-462	282	1	x1	x1	PRON
ejpam-462	283	1	x2	x2	PROPN
ejpam-462	283	2	step	step	NOUN
ejpam-462	283	3	msesub	msesub	PROPN
ejpam-462	283	4	,	,	PUNCT
ejpam-462	283	5	i	i	PRON
ejpam-462	283	6	msesat	msesat	VERB
ejpam-462	283	7	,	,	PUNCT
ejpam-462	283	8	i	i	PRON
ejpam-462	283	9	msesub	msesub	VERB
ejpam-462	283	10	,	,	PUNCT
ejpam-462	283	11	i	i	PRON
ejpam-462	283	12	msesat	msesat	VERB
ejpam-462	283	13	,	,	PUNCT
ejpam-462	283	14	i	i	PRON
ejpam-462	283	15	10	10	NUM
ejpam-462	283	16	0.0652	0.0652	NUM
ejpam-462	283	17	*	*	PUNCT
ejpam-462	284	1	0.0675	0.0675	NUM
ejpam-462	284	2	0.0325	0.0325	NUM
ejpam-462	284	3	*	*	PUNCT
ejpam-462	285	1	0.0337	0.0337	NUM
ejpam-462	285	2	20	20	NUM
ejpam-462	285	3	0.0687	0.0687	NUM
ejpam-462	285	4	*	*	NOUN
ejpam-462	285	5	0.0701	0.0701	NUM
ejpam-462	285	6	0.0321	0.0321	NUM
ejpam-462	285	7	*	*	NUM
ejpam-462	285	8	0.0330	0.0330	NUM
ejpam-462	285	9	30	30	NUM
ejpam-462	285	10	0.0664	0.0664	NUM
ejpam-462	285	11	*	*	PUNCT
ejpam-462	285	12	0.0687	0.0687	NUM
ejpam-462	285	13	0.0326	0.0326	NUM
ejpam-462	285	14	*	*	PUNCT
ejpam-462	285	15	0.0339	0.0339	NUM
ejpam-462	285	16	40	40	NUM
ejpam-462	285	17	0.0675	0.0675	NUM
ejpam-462	285	18	*	*	PUNCT
ejpam-462	285	19	0.0699	0.0699	NUM
ejpam-462	285	20	0.0331	0.0331	NUM
ejpam-462	285	21	*	*	PUNCT
ejpam-462	285	22	0.0341	0.0341	NUM
ejpam-462	285	23	50	50	NUM
ejpam-462	285	24	0.0674	0.0674	NUM
ejpam-462	285	25	*	*	PUNCT
ejpam-462	285	26	0.0696	0.0696	NUM
ejpam-462	285	27	0.0334	0.0334	NUM
ejpam-462	285	28	*	*	PUNCT
ejpam-462	285	29	0.0346	0.0346	NUM
ejpam-462	285	30	60	60	NUM
ejpam-462	285	31	0.0656	0.0656	NUM
ejpam-462	285	32	*	*	PUNCT
ejpam-462	285	33	0.0690	0.0690	NUM
ejpam-462	285	34	0.0320	0.0320	NUM
ejpam-462	285	35	*	*	SYM
ejpam-462	285	36	0.0335	0.0335	NUM
ejpam-462	285	37	70	70	NUM
ejpam-462	285	38	0.0711	0.0711	NUM
ejpam-462	285	39	*	*	PUNCT
ejpam-462	285	40	0.0729	0.0729	NUM
ejpam-462	285	41	0.0339	0.0339	NUM
ejpam-462	285	42	*	*	PUNCT
ejpam-462	285	43	0.0349	0.0349	NUM
ejpam-462	285	44	80	80	NUM
ejpam-462	285	45	0.0645	0.0645	NUM
ejpam-462	285	46	*	*	PUNCT
ejpam-462	285	47	0.0669	0.0669	NUM
ejpam-462	285	48	0.0315	0.0315	NUM
ejpam-462	285	49	*	*	PUNCT
ejpam-462	285	50	0.0327	0.0327	NUM
ejpam-462	285	51	90	90	NUM
ejpam-462	285	52	0.0652	0.0652	NUM
ejpam-462	285	53	*	*	PUNCT
ejpam-462	285	54	0.0670	0.0670	NUM
ejpam-462	285	55	0.0319	0.0319	NUM
ejpam-462	285	56	*	*	PUNCT
ejpam-462	285	57	0.0329	0.0329	NUM
ejpam-462	285	58	100	100	NUM
ejpam-462	285	59	0.0684	0.0684	NUM
ejpam-462	285	60	*	*	PUNCT
ejpam-462	285	61	0.0699	0.0699	NUM
ejpam-462	285	62	0.0333	0.0333	NUM
ejpam-462	285	63	*	*	SYM
ejpam-462	285	64	0.0340	0.0340	NUM
ejpam-462	285	65	and	and	CCONJ
ejpam-462	285	66	saturated	saturated	ADJ
ejpam-462	285	67	models	model	NOUN
ejpam-462	285	68	performed	perform	VERB
ejpam-462	285	69	similarly	similarly	ADV
ejpam-462	285	70	when	when	SCONJ
ejpam-462	285	71	used	use	VERB
ejpam-462	285	72	to	to	PART
ejpam-462	285	73	make	make	VERB
ejpam-462	285	74	out	out	ADP
ejpam-462	285	75	-	-	PUNCT
ejpam-462	285	76	of	of	ADP
ejpam-462	285	77	-	-	PUNCT
ejpam-462	285	78	sample	sample	NOUN
ejpam-462	285	79	predictions	prediction	NOUN
ejpam-462	285	80	for	for	ADP
ejpam-462	285	81	t	t	NOUN
ejpam-462	285	82	=	=	SYM
ejpam-462	285	83	t+1	t+1	PROPN
ejpam-462	285	84	.	.	PUNCT
ejpam-462	285	85	.	.	PUNCT
ejpam-462	285	86	.	.	PUNCT
ejpam-462	286	1	t+100	t+100	X
ejpam-462	286	2	periods	period	VERB
ejpam-462	286	3	ahead	ahead	ADV
ejpam-462	286	4	.	.	PUNCT
ejpam-462	287	1	having	having	AUX
ejpam-462	287	2	said	say	VERB
ejpam-462	287	3	that	that	PRON
ejpam-462	287	4	,	,	PUNCT
ejpam-462	287	5	we	we	PRON
ejpam-462	287	6	see	see	VERB
ejpam-462	287	7	immense	immense	ADJ
ejpam-462	287	8	value	value	NOUN
ejpam-462	287	9	in	in	ADP
ejpam-462	287	10	these	these	DET
ejpam-462	287	11	methods	method	NOUN
ejpam-462	287	12	when	when	SCONJ
ejpam-462	287	13	we	we	PRON
ejpam-462	287	14	consider	consider	VERB
ejpam-462	287	15	the	the	DET
ejpam-462	287	16	forecast	forecast	NOUN
ejpam-462	287	17	precision	precision	NOUN
ejpam-462	287	18	of	of	ADP
ejpam-462	287	19	the	the	DET
ejpam-462	287	20	subset	subset	NOUN
ejpam-462	287	21	var	var	PROPN
ejpam-462	287	22	model	model	PROPN
ejpam-462	287	23	.	.	PUNCT
ejpam-462	288	1	we	we	PRON
ejpam-462	288	2	utilized	utilize	VERB
ejpam-462	288	3	the	the	DET
ejpam-462	288	4	error	error	NOUN
ejpam-462	288	5	term	term	NOUN
ejpam-462	288	6	bootstrapping	bootstrappe	VERB
ejpam-462	288	7	procedure	procedure	NOUN
ejpam-462	288	8	to	to	PART
ejpam-462	288	9	perform	perform	VERB
ejpam-462	288	10	this	this	DET
ejpam-462	288	11	evaluation	evaluation	NOUN
ejpam-462	288	12	,	,	PUNCT
ejpam-462	288	13	with	with	ADP
ejpam-462	288	14	results	result	NOUN
ejpam-462	288	15	in	in	ADP
ejpam-462	288	16	table	table	NOUN
ejpam-462	288	17	6	6	NUM
ejpam-462	288	18	.	.	PUNCT
ejpam-462	289	1	the	the	DET
ejpam-462	289	2	bootstrap	bootstrap	NOUN
ejpam-462	289	3	procedure	procedure	NOUN
ejpam-462	289	4	was	be	AUX
ejpam-462	289	5	executed	execute	VERB
ejpam-462	289	6	b	b	NOUN
ejpam-462	289	7	=	=	SYM
ejpam-462	289	8	2000	2000	NUM
ejpam-462	289	9	times	time	NOUN
ejpam-462	289	10	,	,	PUNCT
ejpam-462	289	11	in	in	ADP
ejpam-462	289	12	approximately	approximately	ADV
ejpam-462	289	13	4.5	4.5	NUM
ejpam-462	289	14	minutes	minute	NOUN
ejpam-462	289	15	,	,	PUNCT
ejpam-462	289	16	using	use	VERB
ejpam-462	289	17	a	a	DET
ejpam-462	289	18	forecast	forecast	NOUN
ejpam-462	289	19	time	time	NOUN
ejpam-462	289	20	horizon	horizon	NOUN
ejpam-462	289	21	of	of	ADP
ejpam-462	289	22	100	100	NUM
ejpam-462	289	23	days	day	NOUN
ejpam-462	289	24	.	.	PUNCT
ejpam-462	290	1	for	for	ADP
ejpam-462	290	2	both	both	CCONJ
ejpam-462	290	3	the	the	DET
ejpam-462	290	4	saturated	saturate	VERB
ejpam-462	290	5	and	and	CCONJ
ejpam-462	290	6	best	good	ADJ
ejpam-462	290	7	subset	subset	NOUN
ejpam-462	290	8	models	model	NOUN
ejpam-462	290	9	,	,	PUNCT
ejpam-462	290	10	the	the	DET
ejpam-462	290	11	mean	mean	NOUN
ejpam-462	290	12	squared	square	VERB
ejpam-462	290	13	error	error	NOUN
ejpam-462	290	14	(	(	PUNCT
ejpam-462	290	15	9	9	NUM
ejpam-462	290	16	)	)	PUNCT
ejpam-462	290	17	was	be	AUX
ejpam-462	290	18	computed	compute	VERB
ejpam-462	290	19	across	across	ADP
ejpam-462	290	20	all	all	DET
ejpam-462	290	21	simulations	simulation	NOUN
ejpam-462	290	22	.	.	PUNCT
ejpam-462	291	1	as	as	SCONJ
ejpam-462	291	2	can	can	AUX
ejpam-462	291	3	be	be	AUX
ejpam-462	291	4	seen	see	VERB
ejpam-462	291	5	,	,	PUNCT
ejpam-462	291	6	for	for	ADP
ejpam-462	291	7	all	all	DET
ejpam-462	291	8	time	time	NOUN
ejpam-462	291	9	steps	step	NOUN
ejpam-462	291	10	considered	consider	VERB
ejpam-462	291	11	,	,	PUNCT
ejpam-462	291	12	the	the	DET
ejpam-462	291	13	subset	subset	NOUN
ejpam-462	291	14	var	var	PROPN
ejpam-462	291	15	model	model	NOUN
ejpam-462	291	16	provided	provide	VERB
ejpam-462	291	17	a	a	DET
ejpam-462	291	18	much	much	ADV
ejpam-462	291	19	tighter	tight	ADJ
ejpam-462	291	20	forecast	forecast	NOUN
ejpam-462	291	21	precision	precision	NOUN
ejpam-462	291	22	than	than	ADP
ejpam-462	291	23	the	the	DET
ejpam-462	291	24	saturated	saturate	VERB
ejpam-462	291	25	model	model	NOUN
ejpam-462	291	26	,	,	PUNCT
ejpam-462	291	27	as	as	SCONJ
ejpam-462	291	28	measured	measure	VERB
ejpam-462	291	29	by	by	ADP
ejpam-462	291	30	mse	mse	PROPN
ejpam-462	291	31	.	.	PUNCT
ejpam-462	292	1	finally	finally	ADV
ejpam-462	292	2	,	,	PUNCT
ejpam-462	292	3	using	use	VERB
ejpam-462	292	4	the	the	DET
ejpam-462	292	5	best	good	ADJ
ejpam-462	292	6	subset	subset	VERB
ejpam-462	292	7	var	var	PROPN
ejpam-462	292	8	model	model	PROPN
ejpam-462	292	9	,	,	PUNCT
ejpam-462	292	10	the	the	DET
ejpam-462	292	11	residuals	residual	NOUN
ejpam-462	292	12	were	be	AUX
ejpam-462	292	13	computed	compute	VERB
ejpam-462	292	14	and	and	CCONJ
ejpam-462	292	15	−4	−4	X
ejpam-462	292	16	−2	−2	NOUN
ejpam-462	292	17	0	0	NUM
ejpam-462	292	18	2	2	NUM
ejpam-462	292	19	4	4	NUM
ejpam-462	292	20	0	0	NUM
ejpam-462	292	21	0.1	0.1	NUM
ejpam-462	292	22	0.2	0.2	NUM
ejpam-462	292	23	0.3	0.3	NUM
ejpam-462	292	24	0.4	0.4	NUM
ejpam-462	292	25	test	test	NOUN
ejpam-462	292	26	for	for	ADP
ejpam-462	292	27	kurtosis	kurtosis	NOUN
ejpam-462	292	28	*	*	PUNCT
ejpam-462	292	29	test	test	NOUN
ejpam-462	292	30	stat	stat	NOUN
ejpam-462	292	31	:	:	PUNCT
ejpam-462	292	32	0.30	0.30	NUM
ejpam-462	292	33	p−value	p−value	NOUN
ejpam-462	292	34	:	:	PUNCT
ejpam-462	292	35	0.76	0.76	NUM
ejpam-462	292	36	0	0	NUM
ejpam-462	292	37	5	5	NUM
ejpam-462	292	38	10	10	NUM
ejpam-462	292	39	15	15	NUM
ejpam-462	292	40	0	0	NUM
ejpam-462	292	41	0.05	0.05	NUM
ejpam-462	292	42	0.1	0.1	NUM
ejpam-462	292	43	0.15	0.15	NUM
ejpam-462	292	44	0.2	0.2	NUM
ejpam-462	292	45	test	test	NOUN
ejpam-462	292	46	for	for	ADP
ejpam-462	292	47	skewness	skewness	NOUN
ejpam-462	292	48	*	*	NOUN
ejpam-462	292	49	test	test	NOUN
ejpam-462	292	50	stat	stat	NOUN
ejpam-462	292	51	:	:	PUNCT
ejpam-462	292	52	3.97	3.97	NUM
ejpam-462	292	53	p−value	p−value	NOUN
ejpam-462	292	54	:	:	PUNCT
ejpam-462	292	55	0.41	0.41	NUM
ejpam-462	292	56	figure	figure	NOUN
ejpam-462	292	57	2	2	NUM
ejpam-462	292	58	:	:	PUNCT
ejpam-462	292	59	multivariate	multivariate	NOUN
ejpam-462	292	60	normality	normality	NOUN
ejpam-462	292	61	test	test	NOUN
ejpam-462	292	62	results	result	NOUN
ejpam-462	292	63	for	for	ADP
ejpam-462	292	64	residuals	residual	NOUN
ejpam-462	292	65	.	.	PUNCT
ejpam-462	293	1	analyzed	analyze	VERB
ejpam-462	293	2	to	to	PART
ejpam-462	293	3	determine	determine	VERB
ejpam-462	293	4	how	how	SCONJ
ejpam-462	293	5	well	well	ADV
ejpam-462	293	6	they	they	PRON
ejpam-462	293	7	met	meet	VERB
ejpam-462	293	8	the	the	DET
ejpam-462	293	9	standard	standard	ADJ
ejpam-462	293	10	ols	ol	NOUN
ejpam-462	293	11	assumptions	assumption	NOUN
ejpam-462	293	12	of	of	ADP
ejpam-462	293	13	gaussianity	gaussianity	NOUN
ejpam-462	293	14	.	.	PUNCT
ejpam-462	294	1	we	we	PRON
ejpam-462	294	2	employed	employ	VERB
ejpam-462	294	3	the	the	DET
ejpam-462	294	4	tests	test	NOUN
ejpam-462	294	5	for	for	ADP
ejpam-462	294	6	multivariate	multivariate	NOUN
ejpam-462	294	7	skewness	skewness	NOUN
ejpam-462	294	8	and	and	CCONJ
ejpam-462	294	9	kurtosis	kurtosis	NOUN
ejpam-462	294	10	of	of	ADP
ejpam-462	294	11	[	[	X
ejpam-462	294	12	16	16	NUM
ejpam-462	294	13	]	]	PUNCT
ejpam-462	294	14	,	,	PUNCT
ejpam-462	294	15	and	and	CCONJ
ejpam-462	294	16	found	find	VERB
ejpam-462	294	17	the	the	DET
ejpam-462	294	18	data	datum	NOUN
ejpam-462	294	19	fit	fit	VERB
ejpam-462	294	20	the	the	DET
ejpam-462	294	21	a.	a.	NOUN
ejpam-462	294	22	howe	howe	NOUN
ejpam-462	294	23	and	and	CCONJ
ejpam-462	294	24	h.	h.	PROPN
ejpam-462	294	25	bozdogan	bozdogan	PROPN
ejpam-462	294	26	/	/	SYM
ejpam-462	294	27	eur	eur	PROPN
ejpam-462	294	28	.	.	PUNCT
ejpam-462	295	1	j.	j.	PROPN
ejpam-462	295	2	pure	pure	PROPN
ejpam-462	295	3	appl	appl	PROPN
ejpam-462	295	4	.	.	PROPN
ejpam-462	295	5	math	math	PROPN
ejpam-462	295	6	,	,	PUNCT
ejpam-462	295	7	3	3	NUM
ejpam-462	295	8	(	(	PUNCT
ejpam-462	295	9	2010	2010	NUM
ejpam-462	295	10	)	)	PUNCT
ejpam-462	295	11	,	,	PUNCT
ejpam-462	295	12	382	382	NUM
ejpam-462	295	13	-	-	SYM
ejpam-462	295	14	405	405	NUM
ejpam-462	295	15	396	396	NUM
ejpam-462	295	16	assumption	assumption	NOUN
ejpam-462	295	17	of	of	ADP
ejpam-462	295	18	normality	normality	NOUN
ejpam-462	295	19	very	very	ADV
ejpam-462	295	20	well	well	ADV
ejpam-462	295	21	,	,	PUNCT
ejpam-462	295	22	as	as	SCONJ
ejpam-462	295	23	can	can	AUX
ejpam-462	295	24	be	be	AUX
ejpam-462	295	25	seen	see	VERB
ejpam-462	295	26	in	in	ADP
ejpam-462	295	27	figure	figure	NOUN
ejpam-462	295	28	2	2	NUM
ejpam-462	295	29	.	.	PUNCT
ejpam-462	296	1	additionally	additionally	ADV
ejpam-462	296	2	,	,	PUNCT
ejpam-462	296	3	we	we	PRON
ejpam-462	296	4	evaluated	evaluate	VERB
ejpam-462	296	5	the	the	DET
ejpam-462	296	6	sample	sample	NOUN
ejpam-462	296	7	autocorrelation	autocorrelation	NOUN
ejpam-462	296	8	coefficient	coefficient	NOUN
ejpam-462	296	9	for	for	ADP
ejpam-462	296	10	orders	order	NOUN
ejpam-462	296	11	one	one	NUM
ejpam-462	296	12	to	to	ADP
ejpam-462	296	13	five	five	NUM
ejpam-462	296	14	;	;	PUNCT
ejpam-462	296	15	the	the	DET
ejpam-462	296	16	strongest	strong	ADJ
ejpam-462	296	17	correlation	correlation	NOUN
ejpam-462	296	18	was	be	AUX
ejpam-462	296	19	−0.0408	−0.0408	ADV
ejpam-462	296	20	virtually	virtually	ADV
ejpam-462	296	21	negligible	negligible	ADJ
ejpam-462	296	22	.	.	PUNCT
ejpam-462	297	1	figure	figure	NOUN
ejpam-462	297	2	3	3	NUM
ejpam-462	297	3	shows	show	VERB
ejpam-462	297	4	the	the	DET
ejpam-462	297	5	time	time	NOUN
ejpam-462	297	6	-	-	PUNCT
ejpam-462	297	7	ordered	order	VERB
ejpam-462	297	8	plots	plot	NOUN
ejpam-462	297	9	of	of	ADP
ejpam-462	297	10	the	the	DET
ejpam-462	297	11	residuals	residual	NOUN
ejpam-462	297	12	from	from	ADP
ejpam-462	297	13	each	each	DET
ejpam-462	297	14	response	response	NOUN
ejpam-462	297	15	.	.	PUNCT
ejpam-462	298	1	it	it	PRON
ejpam-462	298	2	is	be	AUX
ejpam-462	298	3	clear	clear	ADJ
ejpam-462	298	4	that	that	SCONJ
ejpam-462	298	5	the	the	DET
ejpam-462	298	6	residuals	residual	NOUN
ejpam-462	298	7	are	be	AUX
ejpam-462	298	8	homoskedastic	homoskedastic	ADJ
ejpam-462	298	9	.	.	PUNCT
ejpam-462	299	1	so	so	ADV
ejpam-462	299	2	here	here	ADV
ejpam-462	299	3	we	we	PRON
ejpam-462	299	4	see	see	VERB
ejpam-462	299	5	that	that	SCONJ
ejpam-462	299	6	the	the	DET
ejpam-462	299	7	error	error	NOUN
ejpam-462	299	8	0	0	NUM
ejpam-462	299	9	50	50	NUM
ejpam-462	299	10	100	100	NUM
ejpam-462	299	11	150	150	NUM
ejpam-462	299	12	200	200	NUM
ejpam-462	299	13	−1	−1	NOUN
ejpam-462	299	14	−0.5	−0.5	NOUN
ejpam-462	299	15	0	0	NUM
ejpam-462	299	16	0.5	0.5	NUM
ejpam-462	299	17	1	1	NUM
ejpam-462	299	18	residuals	residual	NOUN
ejpam-462	299	19	for	for	ADP
ejpam-462	299	20	x	x	SYM
ejpam-462	299	21	1	1	NUM
ejpam-462	299	22	0	0	NUM
ejpam-462	299	23	50	50	NUM
ejpam-462	299	24	100	100	NUM
ejpam-462	299	25	150	150	NUM
ejpam-462	299	26	200	200	NUM
ejpam-462	299	27	−0.5	−0.5	NOUN
ejpam-462	299	28	0	0	NUM
ejpam-462	299	29	0.5	0.5	NUM
ejpam-462	299	30	residuals	residual	NOUN
ejpam-462	299	31	for	for	ADP
ejpam-462	299	32	x	x	SYM
ejpam-462	299	33	2	2	NUM
ejpam-462	299	34	figure	figure	NOUN
ejpam-462	299	35	3	3	NUM
ejpam-462	299	36	:	:	PUNCT
ejpam-462	299	37	time	time	NOUN
ejpam-462	299	38	-	-	PUNCT
ejpam-462	299	39	ordered	order	VERB
ejpam-462	299	40	plot	plot	NOUN
ejpam-462	299	41	of	of	ADP
ejpam-462	299	42	residuals	residual	NOUN
ejpam-462	299	43	displaying	display	VERB
ejpam-462	299	44	homoskedasti	homoskedasti	NOUN
ejpam-462	299	45	ity	ity	PROPN
ejpam-462	299	46	.	.	PUNCT
ejpam-462	299	47	terms	term	NOUN
ejpam-462	299	48	from	from	ADP
ejpam-462	299	49	the	the	DET
ejpam-462	299	50	best	good	ADJ
ejpam-462	299	51	subset	subset	NOUN
ejpam-462	299	52	model	model	NOUN
ejpam-462	299	53	show	show	VERB
ejpam-462	299	54	no	no	DET
ejpam-462	299	55	departure	departure	NOUN
ejpam-462	299	56	from	from	ADP
ejpam-462	299	57	the	the	DET
ejpam-462	299	58	assumption	assumption	NOUN
ejpam-462	299	59	of	of	ADP
ejpam-462	299	60	uncorrelated	uncorrelated	ADJ
ejpam-462	299	61	homoskedastic	homoskedastic	ADJ
ejpam-462	299	62	multivariate	multivariate	NOUN
ejpam-462	299	63	normality	normality	NOUN
ejpam-462	299	64	.	.	PUNCT
ejpam-462	300	1	and	and	CCONJ
ejpam-462	300	2	yet	yet	ADV
ejpam-462	300	3	,	,	PUNCT
ejpam-462	300	4	our	our	PRON
ejpam-462	300	5	first	first	ADJ
ejpam-462	300	6	experiment	experiment	NOUN
ejpam-462	300	7	suggested	suggest	VERB
ejpam-462	300	8	the	the	DET
ejpam-462	300	9	model	model	NOUN
ejpam-462	300	10	was	be	AUX
ejpam-462	300	11	misspecified	misspecifie	VERB
ejpam-462	300	12	.	.	PUNCT
ejpam-462	301	1	thus	thus	ADV
ejpam-462	301	2	,	,	PUNCT
ejpam-462	301	3	the	the	DET
ejpam-462	301	4	use	use	NOUN
ejpam-462	301	5	of	of	ADP
ejpam-462	301	6	stricter	strict	ADJ
ejpam-462	301	7	misspecification	misspecification	NOUN
ejpam-462	301	8	-	-	PUNCT
ejpam-462	301	9	resistent	resistent	ADJ
ejpam-462	301	10	criteria	criterion	NOUN
ejpam-462	301	11	may	may	AUX
ejpam-462	301	12	be	be	AUX
ejpam-462	301	13	justified	justify	VERB
ejpam-462	301	14	even	even	ADV
ejpam-462	301	15	when	when	SCONJ
ejpam-462	301	16	the	the	DET
ejpam-462	301	17	model	model	NOUN
ejpam-462	301	18	seems	seem	VERB
ejpam-462	301	19	correct	correct	ADJ
ejpam-462	301	20	.	.	PUNCT
ejpam-462	302	1	we	we	PRON
ejpam-462	302	2	propose	propose	VERB
ejpam-462	302	3	that	that	SCONJ
ejpam-462	302	4	this	this	PRON
ejpam-462	302	5	is	be	AUX
ejpam-462	302	6	the	the	DET
ejpam-462	302	7	case	case	NOUN
ejpam-462	302	8	for	for	ADP
ejpam-462	302	9	var	var	NOUN
ejpam-462	302	10	modeling	modeling	NOUN
ejpam-462	302	11	,	,	PUNCT
ejpam-462	302	12	in	in	ADP
ejpam-462	302	13	general	general	ADJ
ejpam-462	302	14	.	.	PUNCT
ejpam-462	303	1	5.2	5.2	NUM
ejpam-462	303	2	.	.	PUNCT
ejpam-462	303	3	selecting	select	VERB
ejpam-462	303	4	an	an	DET
ejpam-462	303	5	economically	economically	ADV
ejpam-462	303	6	valuable	valuable	ADJ
ejpam-462	303	7	trading	trading	NOUN
ejpam-462	303	8	model	model	NOUN
ejpam-462	303	9	our	our	PRON
ejpam-462	303	10	application	application	NOUN
ejpam-462	303	11	example	example	NOUN
ejpam-462	303	12	was	be	AUX
ejpam-462	303	13	performed	perform	VERB
ejpam-462	303	14	using	use	VERB
ejpam-462	303	15	the	the	DET
ejpam-462	303	16	first	first	ADJ
ejpam-462	303	17	3	3	NUM
ejpam-462	303	18	months	month	NOUN
ejpam-462	303	19	of	of	ADP
ejpam-462	303	20	2002	2002	NUM
ejpam-462	303	21	(	(	PUNCT
ejpam-462	303	22	approximately	approximately	ADV
ejpam-462	303	23	60	60	NUM
ejpam-462	303	24	trading	trading	NOUN
ejpam-462	303	25	days	day	NOUN
ejpam-462	303	26	)	)	PUNCT
ejpam-462	303	27	as	as	ADP
ejpam-462	303	28	the	the	DET
ejpam-462	303	29	training	training	NOUN
ejpam-462	303	30	period	period	NOUN
ejpam-462	303	31	,	,	PUNCT
ejpam-462	303	32	and	and	CCONJ
ejpam-462	303	33	the	the	DET
ejpam-462	303	34	ensuing	ensue	VERB
ejpam-462	303	35	3	3	NUM
ejpam-462	303	36	months	month	NOUN
ejpam-462	303	37	as	as	ADP
ejpam-462	303	38	the	the	DET
ejpam-462	303	39	trading	trading	NOUN
ejpam-462	303	40	period	period	NOUN
ejpam-462	303	41	.	.	PUNCT
ejpam-462	304	1	using	use	VERB
ejpam-462	304	2	the	the	DET
ejpam-462	304	3	usual	usual	ADJ
ejpam-462	304	4	benchmark	benchmark	NOUN
ejpam-462	304	5	of	of	ADP
ejpam-462	304	6	standard	standard	PROPN
ejpam-462	304	7	&	&	CCONJ
ejpam-462	304	8	poor	poor	PROPN
ejpam-462	304	9	’s	’s	PART
ejpam-462	304	10	s&p	s&p	PROPN
ejpam-462	304	11	500	500	NUM
ejpam-462	304	12	,	,	PUNCT
ejpam-462	304	13	the	the	DET
ejpam-462	304	14	uncompounded	uncompounded	ADJ
ejpam-462	304	15	return	return	NOUN
ejpam-462	304	16	for	for	ADP
ejpam-462	304	17	the	the	DET
ejpam-462	304	18	in	in	ADP
ejpam-462	304	19	-	-	PUNCT
ejpam-462	304	20	sample	sample	NOUN
ejpam-462	304	21	period	period	NOUN
ejpam-462	304	22	is	be	AUX
ejpam-462	304	23	−0.40	−0.40	NOUN
ejpam-462	304	24	%	%	NOUN
ejpam-462	304	25	.	.	PUNCT
ejpam-462	305	1	the	the	DET
ejpam-462	305	2	index	index	NOUN
ejpam-462	305	3	lost	lose	VERB
ejpam-462	305	4	15.28	15.28	NUM
ejpam-462	305	5	%	%	NOUN
ejpam-462	305	6	during	during	ADP
ejpam-462	305	7	the	the	DET
ejpam-462	305	8	testing	testing	NOUN
ejpam-462	305	9	period	period	NOUN
ejpam-462	305	10	.	.	PUNCT
ejpam-462	306	1	figure	figure	NOUN
ejpam-462	306	2	4	4	NUM
ejpam-462	306	3	shows	show	VERB
ejpam-462	306	4	the	the	DET
ejpam-462	306	5	activity	activity	NOUN
ejpam-462	306	6	of	of	ADP
ejpam-462	306	7	the	the	DET
ejpam-462	306	8	spx	spx	NOUN
ejpam-462	306	9	over	over	ADP
ejpam-462	306	10	the	the	DET
ejpam-462	306	11	entire	entire	ADJ
ejpam-462	306	12	period	period	NOUN
ejpam-462	306	13	,	,	PUNCT
ejpam-462	306	14	along	along	ADP
ejpam-462	306	15	with	with	ADP
ejpam-462	306	16	its	its	PRON
ejpam-462	306	17	daily	daily	ADJ
ejpam-462	306	18	changes	change	NOUN
ejpam-462	306	19	.	.	PUNCT
ejpam-462	307	1	all	all	DET
ejpam-462	307	2	analysis	analysis	NOUN
ejpam-462	307	3	was	be	AUX
ejpam-462	307	4	performed	perform	VERB
ejpam-462	307	5	using	use	VERB
ejpam-462	307	6	uncompounded	uncompounded	ADJ
ejpam-462	307	7	returns	return	NOUN
ejpam-462	307	8	;	;	PUNCT
ejpam-462	307	9	this	this	PRON
ejpam-462	307	10	was	be	AUX
ejpam-462	307	11	accomplished	accomplish	VERB
ejpam-462	307	12	by	by	ADP
ejpam-462	307	13	decomposing	decompose	VERB
ejpam-462	307	14	the	the	DET
ejpam-462	307	15	series	series	NOUN
ejpam-462	307	16	into	into	ADP
ejpam-462	307	17	its	its	PRON
ejpam-462	307	18	relative	relative	ADJ
ejpam-462	307	19	daily	daily	ADJ
ejpam-462	307	20	changes	change	NOUN
ejpam-462	307	21	:	:	PUNCT
ejpam-462	307	22	�	�	PROPN
ejpam-462	307	23	yt	yt	VERB
ejpam-462	307	24	−	−	PROPN
ejpam-462	307	25	yt−1	yt−1	PROPN
ejpam-462	307	26	�	�	PROPN
ejpam-462	307	27	/yt−1	/yt−1	PROPN
ejpam-462	307	28	.	.	PUNCT
ejpam-462	308	1	a	a	DET
ejpam-462	308	2	cumulative	cumulative	ADJ
ejpam-462	308	3	sum	sum	NOUN
ejpam-462	308	4	was	be	AUX
ejpam-462	308	5	then	then	ADV
ejpam-462	308	6	computed	compute	VERB
ejpam-462	308	7	on	on	ADP
ejpam-462	308	8	these	these	DET
ejpam-462	308	9	daily	daily	ADJ
ejpam-462	308	10	returns	return	NOUN
ejpam-462	308	11	.	.	PUNCT
ejpam-462	309	1	this	this	PRON
ejpam-462	309	2	gives	give	VERB
ejpam-462	309	3	a	a	DET
ejpam-462	309	4	simple	simple	ADJ
ejpam-462	309	5	measure	measure	NOUN
ejpam-462	309	6	of	of	ADP
ejpam-462	309	7	trading	trading	NOUN
ejpam-462	309	8	activity	activity	NOUN
ejpam-462	309	9	,	,	PUNCT
ejpam-462	309	10	and	and	CCONJ
ejpam-462	309	11	acts	act	VERB
ejpam-462	309	12	to	to	PART
ejpam-462	309	13	more	more	ADV
ejpam-462	309	14	conservatively	conservatively	ADV
ejpam-462	309	15	estimate	estimate	VERB
ejpam-462	309	16	the	the	DET
ejpam-462	309	17	value	value	NOUN
ejpam-462	309	18	of	of	ADP
ejpam-462	309	19	a	a	DET
ejpam-462	309	20	given	give	VERB
ejpam-462	309	21	model	model	NOUN
ejpam-462	309	22	.	.	PUNCT
ejpam-462	310	1	in	in	ADP
ejpam-462	310	2	preparing	prepare	VERB
ejpam-462	310	3	the	the	DET
ejpam-462	310	4	predictor	predictor	NOUN
ejpam-462	310	5	variables	variable	NOUN
ejpam-462	310	6	,	,	PUNCT
ejpam-462	310	7	the	the	DET
ejpam-462	310	8	data	datum	NOUN
ejpam-462	310	9	used	use	VERB
ejpam-462	310	10	a.	a.	NOUN
ejpam-462	310	11	howe	howe	NOUN
ejpam-462	310	12	and	and	CCONJ
ejpam-462	310	13	h.	h.	PROPN
ejpam-462	310	14	bozdogan	bozdogan	PROPN
ejpam-462	310	15	/	/	SYM
ejpam-462	310	16	eur	eur	PROPN
ejpam-462	310	17	.	.	PUNCT
ejpam-462	311	1	j.	j.	PROPN
ejpam-462	311	2	pure	pure	PROPN
ejpam-462	311	3	appl	appl	PROPN
ejpam-462	311	4	.	.	PROPN
ejpam-462	311	5	math	math	PROPN
ejpam-462	311	6	,	,	PUNCT
ejpam-462	311	7	3	3	NUM
ejpam-462	311	8	(	(	PUNCT
ejpam-462	311	9	2010	2010	NUM
ejpam-462	311	10	)	)	PUNCT
ejpam-462	311	11	,	,	PUNCT
ejpam-462	311	12	382	382	NUM
ejpam-462	311	13	-	-	SYM
ejpam-462	311	14	405	405	NUM
ejpam-462	311	15	397	397	NUM
ejpam-462	311	16	s	s	NOUN
ejpam-462	311	17	&	&	CCONJ
ejpam-462	311	18	p	p	NOUN
ejpam-462	311	19	5	5	NUM
ejpam-462	311	20	00	00	NUM
ejpam-462	311	21	in−sample	in−sample	NOUN
ejpam-462	311	22	(	(	PUNCT
ejpam-462	311	23	ro	ro	NOUN
ejpam-462	311	24	)	)	PUNCT
ejpam-462	311	25	out−sample	out−sample	ADV
ejpam-462	311	26	(	(	PUNCT
ejpam-462	311	27	bx	bx	NOUN
ejpam-462	311	28	)	)	PUNCT
ejpam-462	311	29	∆	∆	X
ejpam-462	311	30	1	1	NUM
ejpam-462	311	31	figure	figure	NOUN
ejpam-462	311	32	4	4	NUM
ejpam-462	311	33	:	:	PUNCT
ejpam-462	311	34	s&p	s&p	PROPN
ejpam-462	311	35	500	500	NUM
ejpam-462	311	36	ben	ben	PROPN
ejpam-462	311	37	hmark	hmark	VERB
ejpam-462	311	38	daily	daily	ADJ
ejpam-462	311	39	values	value	NOUN
ejpam-462	311	40	and	and	CCONJ
ejpam-462	311	41	changes	change	NOUN
ejpam-462	311	42	.	.	PUNCT
ejpam-462	312	1	was	be	AUX
ejpam-462	312	2	begun	begin	VERB
ejpam-462	312	3	six	six	NUM
ejpam-462	312	4	days	day	NOUN
ejpam-462	312	5	prior	prior	ADV
ejpam-462	312	6	to	to	ADP
ejpam-462	312	7	the	the	DET
ejpam-462	312	8	1st	1st	ADJ
ejpam-462	312	9	day	day	NOUN
ejpam-462	312	10	of	of	ADP
ejpam-462	312	11	2002	2002	NUM
ejpam-462	312	12	.	.	PUNCT
ejpam-462	313	1	after	after	ADP
ejpam-462	313	2	all	all	DET
ejpam-462	313	3	five	five	NUM
ejpam-462	313	4	lags	lag	NOUN
ejpam-462	313	5	were	be	AUX
ejpam-462	313	6	computed	compute	VERB
ejpam-462	313	7	on	on	ADP
ejpam-462	313	8	the	the	DET
ejpam-462	313	9	first	first	ADJ
ejpam-462	313	10	differences	difference	NOUN
ejpam-462	313	11	,	,	PUNCT
ejpam-462	313	12	these	these	DET
ejpam-462	313	13	conditional	conditional	ADJ
ejpam-462	313	14	observations	observation	NOUN
ejpam-462	313	15	were	be	AUX
ejpam-462	313	16	dropped	drop	VERB
ejpam-462	313	17	.	.	PUNCT
ejpam-462	314	1	this	this	PRON
ejpam-462	314	2	was	be	AUX
ejpam-462	314	3	done	do	VERB
ejpam-462	314	4	so	so	SCONJ
ejpam-462	314	5	as	as	SCONJ
ejpam-462	314	6	to	to	PART
ejpam-462	314	7	maintain	maintain	VERB
ejpam-462	314	8	a	a	DET
ejpam-462	314	9	constant	constant	ADJ
ejpam-462	314	10	number	number	NOUN
ejpam-462	314	11	of	of	ADP
ejpam-462	314	12	usable	usable	ADJ
ejpam-462	314	13	observations	observation	NOUN
ejpam-462	314	14	across	across	ADP
ejpam-462	314	15	all	all	DET
ejpam-462	314	16	models	model	NOUN
ejpam-462	314	17	.	.	PUNCT
ejpam-462	315	1	in	in	ADP
ejpam-462	315	2	time	time	NOUN
ejpam-462	315	3	series	series	PROPN
ejpam-462	315	4	analysis	analysis	NOUN
ejpam-462	315	5	,	,	PUNCT
ejpam-462	315	6	we	we	PRON
ejpam-462	315	7	are	be	AUX
ejpam-462	315	8	mostly	mostly	ADV
ejpam-462	315	9	interested	interested	ADJ
ejpam-462	315	10	in	in	ADP
ejpam-462	315	11	forecasting	forecasting	NOUN
ejpam-462	315	12	,	,	PUNCT
ejpam-462	315	13	conditional	conditional	ADJ
ejpam-462	315	14	upon	upon	SCONJ
ejpam-462	315	15	existing	exist	VERB
ejpam-462	315	16	data	datum	NOUN
ejpam-462	315	17	.	.	PUNCT
ejpam-462	316	1	in	in	ADP
ejpam-462	316	2	the	the	DET
ejpam-462	316	3	specific	specific	ADJ
ejpam-462	316	4	specialization	specialization	NOUN
ejpam-462	316	5	of	of	ADP
ejpam-462	316	6	trading	trading	NOUN
ejpam-462	316	7	,	,	PUNCT
ejpam-462	316	8	a	a	DET
ejpam-462	316	9	model	model	NOUN
ejpam-462	316	10	that	that	PRON
ejpam-462	316	11	has	have	VERB
ejpam-462	316	12	a	a	DET
ejpam-462	316	13	higher	high	ADJ
ejpam-462	316	14	out	out	ADP
ejpam-462	316	15	-	-	PUNCT
ejpam-462	316	16	of	of	ADP
ejpam-462	316	17	-	-	PUNCT
ejpam-462	316	18	sample	sample	NOUN
ejpam-462	316	19	return	return	NOUN
ejpam-462	316	20	is	be	AUX
ejpam-462	316	21	deemed	deem	VERB
ejpam-462	316	22	to	to	PART
ejpam-462	316	23	have	have	VERB
ejpam-462	316	24	stronger	strong	ADJ
ejpam-462	316	25	forecast	forecast	NOUN
ejpam-462	316	26	power	power	NOUN
ejpam-462	316	27	.	.	PUNCT
ejpam-462	317	1	due	due	ADP
ejpam-462	317	2	to	to	ADP
ejpam-462	317	3	the	the	DET
ejpam-462	317	4	much	much	ADV
ejpam-462	317	5	higher	high	ADJ
ejpam-462	317	6	dimensionality	dimensionality	NOUN
ejpam-462	317	7	of	of	ADP
ejpam-462	317	8	this	this	DET
ejpam-462	317	9	dataset	dataset	NOUN
ejpam-462	317	10	,	,	PUNCT
ejpam-462	317	11	the	the	DET
ejpam-462	317	12	chances	chance	NOUN
ejpam-462	317	13	of	of	ADP
ejpam-462	317	14	overparameterization	overparameterization	NOUN
ejpam-462	317	15	are	be	AUX
ejpam-462	317	16	higher	high	ADJ
ejpam-462	317	17	.	.	PUNCT
ejpam-462	318	1	additionally	additionally	ADV
ejpam-462	318	2	,	,	PUNCT
ejpam-462	318	3	since	since	SCONJ
ejpam-462	318	4	we	we	PRON
ejpam-462	318	5	are	be	AUX
ejpam-462	318	6	dealing	deal	VERB
ejpam-462	318	7	with	with	ADP
ejpam-462	318	8	financial	financial	ADJ
ejpam-462	318	9	data	datum	NOUN
ejpam-462	318	10	,	,	PUNCT
ejpam-462	318	11	we	we	PRON
ejpam-462	318	12	expect	expect	VERB
ejpam-462	318	13	heavier	heavy	ADJ
ejpam-462	318	14	tails	tail	NOUN
ejpam-462	318	15	.	.	PUNCT
ejpam-462	319	1	thus	thus	ADV
ejpam-462	319	2	,	,	PUNCT
ejpam-462	319	3	the	the	DET
ejpam-462	319	4	model	model	NOUN
ejpam-462	319	5	selection	selection	NOUN
ejpam-462	319	6	information	information	NOUN
ejpam-462	319	7	criteria	criterion	NOUN
ejpam-462	319	8	we	we	PRON
ejpam-462	319	9	employ	employ	VERB
ejpam-462	319	10	is	be	AUX
ejpam-462	319	11	icom	icom	PROPN
ejpam-462	319	12	pm	pm	VERB
ejpam-462	319	13	isp_peu	isp_peu	PROPN
ejpam-462	319	14	with	with	ADP
ejpam-462	319	15	a	a	DET
ejpam-462	319	16	strict	strict	ADJ
ejpam-462	319	17	and	and	CCONJ
ejpam-462	319	18	misspecification	misspecification	NOUN
ejpam-462	319	19	-	-	PUNCT
ejpam-462	319	20	robust	robust	ADJ
ejpam-462	319	21	penalty	penalty	NOUN
ejpam-462	319	22	term	term	NOUN
ejpam-462	319	23	.	.	PUNCT
ejpam-462	320	1	using	use	VERB
ejpam-462	320	2	the	the	DET
ejpam-462	320	3	ga	ga	PROPN
ejpam-462	320	4	settings	setting	NOUN
ejpam-462	320	5	in	in	ADP
ejpam-462	320	6	table	table	NOUN
ejpam-462	320	7	2	2	NUM
ejpam-462	320	8	,	,	PUNCT
ejpam-462	320	9	100	100	NUM
ejpam-462	320	10	replications	replication	NOUN
ejpam-462	320	11	of	of	ADP
ejpam-462	320	12	the	the	DET
ejpam-462	320	13	genetic	genetic	ADJ
ejpam-462	320	14	algorithm	algorithm	NOUN
ejpam-462	320	15	were	be	AUX
ejpam-462	320	16	executed	execute	VERB
ejpam-462	320	17	.	.	PUNCT
ejpam-462	321	1	replications	replication	NOUN
ejpam-462	321	2	that	that	PRON
ejpam-462	321	3	did	do	AUX
ejpam-462	321	4	not	not	PART
ejpam-462	321	5	terminate	terminate	VERB
ejpam-462	321	6	early	early	ADJ
ejpam-462	321	7	eval0	eval0	NOUN
ejpam-462	321	8	50	50	NUM
ejpam-462	321	9	100	100	NUM
ejpam-462	321	10	−6000	−6000	PROPN
ejpam-462	321	11	−4000	−4000	NOUN
ejpam-462	321	12	−2000	−2000	PROPN
ejpam-462	321	13	0	0	NUM
ejpam-462	321	14	2000	2000	NUM
ejpam-462	321	15	4000	4000	NUM
ejpam-462	321	16	ga	ga	PROPN
ejpam-462	321	17	progress	progress	PROPN
ejpam-462	321	18	min	min	PROPN
ejpam-462	321	19	.	.	PROPN
ejpam-462	321	20	avg	avg	PROPN
ejpam-462	321	21	.	.	PUNCT
ejpam-462	322	1	−100	−100	PROPN
ejpam-462	322	2	0	0	NUM
ejpam-462	322	3	100	100	NUM
ejpam-462	322	4	200	200	NUM
ejpam-462	322	5	residuals	residual	NOUN
ejpam-462	322	6	figure	figure	NOUN
ejpam-462	322	7	5	5	NUM
ejpam-462	322	8	:	:	PUNCT
ejpam-462	322	9	ga	ga	NOUN
ejpam-462	322	10	progress	progress	NOUN
ejpam-462	322	11	and	and	CCONJ
ejpam-462	322	12	residuals	residual	VERB
ejpam-462	322	13	plot	plot	NOUN
ejpam-462	322	14	from	from	ADP
ejpam-462	322	15	best	good	ADJ
ejpam-462	322	16	subset	subset	ADJ
ejpam-462	322	17	model	model	NOUN
ejpam-462	322	18	.	.	PUNCT
ejpam-462	323	1	uated	uated	ADJ
ejpam-462	323	2	at	at	ADP
ejpam-462	323	3	most	most	ADV
ejpam-462	323	4	15,000	15,000	NUM
ejpam-462	323	5	unique	unique	ADJ
ejpam-462	323	6	subset	subset	NOUN
ejpam-462	323	7	var	var	NOUN
ejpam-462	323	8	models	model	NOUN
ejpam-462	323	9	,	,	PUNCT
ejpam-462	323	10	with	with	ADP
ejpam-462	323	11	average	average	ADJ
ejpam-462	323	12	running	running	NOUN
ejpam-462	323	13	time	time	NOUN
ejpam-462	323	14	approximately	approximately	ADV
ejpam-462	323	15	15	15	NUM
ejpam-462	323	16	minutes	minute	NOUN
ejpam-462	323	17	.	.	PUNCT
ejpam-462	324	1	due	due	ADP
ejpam-462	324	2	to	to	ADP
ejpam-462	324	3	the	the	DET
ejpam-462	324	4	vast	vast	ADJ
ejpam-462	324	5	number	number	NOUN
ejpam-462	324	6	of	of	ADP
ejpam-462	324	7	possible	possible	ADJ
ejpam-462	324	8	subset	subset	NOUN
ejpam-462	324	9	models	model	NOUN
ejpam-462	324	10	(	(	PUNCT
ejpam-462	324	11	9.808×	9.808×	NOUN
ejpam-462	324	12	1055	1055	NUM
ejpam-462	324	13	)	)	PUNCT
ejpam-462	324	14	(	(	PUNCT
ejpam-462	324	15	and	and	CCONJ
ejpam-462	324	16	inherent	inherent	ADJ
ejpam-462	324	17	a.	a.	NOUN
ejpam-462	324	18	howe	howe	NOUN
ejpam-462	324	19	and	and	CCONJ
ejpam-462	324	20	h.	h.	PROPN
ejpam-462	324	21	bozdogan	bozdogan	PROPN
ejpam-462	324	22	/	/	SYM
ejpam-462	324	23	eur	eur	PROPN
ejpam-462	324	24	.	.	PUNCT
ejpam-462	325	1	j.	j.	PROPN
ejpam-462	325	2	pure	pure	PROPN
ejpam-462	325	3	appl	appl	PROPN
ejpam-462	325	4	.	.	PROPN
ejpam-462	325	5	math	math	PROPN
ejpam-462	325	6	,	,	PUNCT
ejpam-462	325	7	3	3	NUM
ejpam-462	325	8	(	(	PUNCT
ejpam-462	325	9	2010	2010	NUM
ejpam-462	325	10	)	)	PUNCT
ejpam-462	325	11	,	,	PUNCT
ejpam-462	325	12	382	382	NUM
ejpam-462	325	13	-	-	SYM
ejpam-462	325	14	405	405	NUM
ejpam-462	325	15	398	398	NUM
ejpam-462	325	16	randomness	randomness	NOUN
ejpam-462	325	17	of	of	ADP
ejpam-462	325	18	the	the	DET
ejpam-462	325	19	ga	ga	PROPN
ejpam-462	325	20	)	)	PUNCT
ejpam-462	326	1	,	,	PUNCT
ejpam-462	326	2	there	there	PRON
ejpam-462	326	3	was	be	VERB
ejpam-462	326	4	much	much	ADJ
ejpam-462	326	5	variety	variety	NOUN
ejpam-462	326	6	in	in	ADP
ejpam-462	326	7	results	result	NOUN
ejpam-462	326	8	across	across	ADP
ejpam-462	326	9	all	all	DET
ejpam-462	326	10	replications	replication	NOUN
ejpam-462	326	11	.	.	PUNCT
ejpam-462	327	1	according	accord	VERB
ejpam-462	327	2	to	to	ADP
ejpam-462	327	3	the	the	DET
ejpam-462	327	4	ga	ga	PROPN
ejpam-462	327	5	progress	progress	NOUN
ejpam-462	327	6	plot	plot	NOUN
ejpam-462	327	7	in	in	ADP
ejpam-462	327	8	figure	figure	NOUN
ejpam-462	327	9	5	5	NUM
ejpam-462	327	10	,	,	PUNCT
ejpam-462	327	11	the	the	DET
ejpam-462	327	12	best	good	ADJ
ejpam-462	327	13	replication	replication	NOUN
ejpam-462	327	14	had	have	AUX
ejpam-462	327	15	converged	converge	VERB
ejpam-462	327	16	to	to	ADP
ejpam-462	327	17	its	its	PRON
ejpam-462	327	18	final	final	ADJ
ejpam-462	327	19	solution	solution	NOUN
ejpam-462	327	20	before	before	ADP
ejpam-462	327	21	the	the	DET
ejpam-462	327	22	40th	40th	ADJ
ejpam-462	327	23	generation	generation	NOUN
ejpam-462	327	24	.	.	PUNCT
ejpam-462	328	1	the	the	DET
ejpam-462	328	2	right	right	ADJ
ejpam-462	328	3	pane	pane	NOUN
ejpam-462	328	4	of	of	ADP
ejpam-462	328	5	figure	figure	NOUN
ejpam-462	328	6	5	5	NUM
ejpam-462	328	7	shows	show	VERB
ejpam-462	328	8	histograms	histogram	NOUN
ejpam-462	328	9	of	of	ADP
ejpam-462	328	10	the	the	DET
ejpam-462	328	11	residuals	residual	NOUN
ejpam-462	328	12	from	from	ADP
ejpam-462	328	13	the	the	DET
ejpam-462	328	14	best	good	ADJ
ejpam-462	328	15	subset	subset	NOUN
ejpam-462	328	16	model	model	NOUN
ejpam-462	328	17	;	;	PUNCT
ejpam-462	328	18	note	note	VERB
ejpam-462	328	19	the	the	DET
ejpam-462	328	20	general	general	ADJ
ejpam-462	328	21	gaussian	gaussian	NOUN
ejpam-462	328	22	look	look	NOUN
ejpam-462	328	23	,	,	PUNCT
ejpam-462	328	24	though	though	SCONJ
ejpam-462	328	25	the	the	DET
ejpam-462	328	26	residuals	residual	NOUN
ejpam-462	328	27	from	from	ADP
ejpam-462	328	28	some	some	DET
ejpam-462	328	29	indices	index	NOUN
ejpam-462	328	30	are	be	AUX
ejpam-462	328	31	clearly	clearly	ADV
ejpam-462	328	32	non	non	ADJ
ejpam-462	328	33	-	-	ADJ
ejpam-462	328	34	normal	normal	ADJ
ejpam-462	328	35	.	.	PUNCT
ejpam-462	329	1	overall	overall	ADJ
ejpam-462	329	2	,	,	PUNCT
ejpam-462	329	3	though	though	ADV
ejpam-462	329	4	,	,	PUNCT
ejpam-462	329	5	there	there	PRON
ejpam-462	329	6	appears	appear	VERB
ejpam-462	329	7	to	to	PART
ejpam-462	329	8	be	be	AUX
ejpam-462	329	9	no	no	DET
ejpam-462	329	10	significant	significant	ADJ
ejpam-462	329	11	departure	departure	NOUN
ejpam-462	329	12	from	from	ADP
ejpam-462	329	13	gaussianity	gaussianity	NOUN
ejpam-462	329	14	,	,	PUNCT
ejpam-462	329	15	using	use	VERB
ejpam-462	329	16	mardia	mardia	NOUN
ejpam-462	329	17	’s	’s	PART
ejpam-462	329	18	tests	test	NOUN
ejpam-462	329	19	.	.	PUNCT
ejpam-462	330	1	additionally	additionally	ADV
ejpam-462	330	2	,	,	PUNCT
ejpam-462	330	3	we	we	PRON
ejpam-462	330	4	evaluated	evaluate	VERB
ejpam-462	330	5	the	the	DET
ejpam-462	330	6	condition	condition	NOUN
ejpam-462	330	7	of	of	ADP
ejpam-462	330	8	autocorrelation	autocorrelation	NOUN
ejpam-462	330	9	in	in	ADP
ejpam-462	330	10	the	the	DET
ejpam-462	330	11	residuals	residual	NOUN
ejpam-462	330	12	when	when	SCONJ
ejpam-462	330	13	the	the	DET
ejpam-462	330	14	model	model	NOUN
ejpam-462	330	15	was	be	AUX
ejpam-462	330	16	used	use	VERB
ejpam-462	330	17	to	to	PART
ejpam-462	330	18	predict	predict	VERB
ejpam-462	330	19	the	the	DET
ejpam-462	330	20	spx	spx	PROPN
ejpam-462	330	21	daily	daily	ADJ
ejpam-462	330	22	moves	move	NOUN
ejpam-462	330	23	.	.	PUNCT
ejpam-462	331	1	1st	1st	NOUN
ejpam-462	331	2	through	through	ADP
ejpam-462	331	3	6th	6th	ADJ
ejpam-462	331	4	order	order	NOUN
ejpam-462	331	5	autocorrelations	autocorrelation	NOUN
ejpam-462	331	6	were	be	AUX
ejpam-462	331	7	−0.0635	−0.0635	PROPN
ejpam-462	331	8	,	,	PUNCT
ejpam-462	331	9	0.0016	0.0016	NUM
ejpam-462	331	10	,	,	PUNCT
ejpam-462	331	11	0.1242	0.1242	NUM
ejpam-462	331	12	,	,	PUNCT
ejpam-462	331	13	−0.0102,−0.0193	−0.0102,−0.0193	NOUN
ejpam-462	331	14	,	,	PUNCT
ejpam-462	331	15	−0.0175	−0.0175	X
ejpam-462	331	16	all	all	PRON
ejpam-462	331	17	very	very	ADV
ejpam-462	331	18	small	small	ADJ
ejpam-462	331	19	.	.	PUNCT
ejpam-462	332	1	finally	finally	ADV
ejpam-462	332	2	,	,	PUNCT
ejpam-462	332	3	in	in	ADP
ejpam-462	332	4	assessing	assess	VERB
ejpam-462	332	5	the	the	DET
ejpam-462	332	6	ols	ol	NOUN
ejpam-462	332	7	assumptions	assumption	NOUN
ejpam-462	332	8	,	,	PUNCT
ejpam-462	332	9	we	we	PRON
ejpam-462	332	10	inspected	inspect	VERB
ejpam-462	332	11	the	the	DET
ejpam-462	332	12	time	time	NOUN
ejpam-462	332	13	-	-	PUNCT
ejpam-462	332	14	ordered	order	VERB
ejpam-462	332	15	plot	plot	NOUN
ejpam-462	332	16	of	of	ADP
ejpam-462	332	17	these	these	DET
ejpam-462	332	18	residuals	residual	NOUN
ejpam-462	332	19	;	;	PUNCT
ejpam-462	332	20	there	there	PRON
ejpam-462	332	21	was	be	VERB
ejpam-462	332	22	no	no	DET
ejpam-462	332	23	sign	sign	NOUN
ejpam-462	332	24	of	of	ADP
ejpam-462	332	25	heteroskedasticity	heteroskedasticity	NOUN
ejpam-462	332	26	.	.	PUNCT
ejpam-462	333	1	the	the	DET
ejpam-462	333	2	overall	overall	ADJ
ejpam-462	333	3	best	good	ADJ
ejpam-462	333	4	model	model	NOUN
ejpam-462	333	5	achieved	achieve	VERB
ejpam-462	333	6	a	a	DET
ejpam-462	333	7	dramatic	dramatic	ADJ
ejpam-462	333	8	decrease	decrease	NOUN
ejpam-462	333	9	in	in	ADP
ejpam-462	333	10	the	the	DET
ejpam-462	333	11	number	number	NOUN
ejpam-462	333	12	of	of	ADP
ejpam-462	333	13	parameters	parameter	NOUN
ejpam-462	333	14	from	from	ADP
ejpam-462	333	15	the	the	DET
ejpam-462	333	16	saturated	saturate	VERB
ejpam-462	333	17	model	model	NOUN
ejpam-462	333	18	approximately	approximately	ADV
ejpam-462	333	19	80	80	NUM
ejpam-462	333	20	%	%	NOUN
ejpam-462	333	21	.	.	PUNCT
ejpam-462	334	1	the	the	DET
ejpam-462	334	2	38	38	NUM
ejpam-462	334	3	(	(	PUNCT
ejpam-462	334	4	out	out	ADP
ejpam-462	334	5	of	of	ADP
ejpam-462	334	6	186	186	NUM
ejpam-462	334	7	)	)	PUNCT
ejpam-462	334	8	coefficients	coefficient	NOUN
ejpam-462	334	9	selected	select	VERB
ejpam-462	334	10	by	by	ADP
ejpam-462	334	11	the	the	DET
ejpam-462	334	12	best	good	ADJ
ejpam-462	334	13	model	model	NOUN
ejpam-462	334	14	are	be	AUX
ejpam-462	334	15	shown	show	VERB
ejpam-462	334	16	in	in	ADP
ejpam-462	334	17	table	table	NOUN
ejpam-462	334	18	7	7	NUM
ejpam-462	334	19	.	.	PUNCT
ejpam-462	335	1	for	for	ADP
ejpam-462	335	2	comparison	comparison	NOUN
ejpam-462	335	3	purposes	purpose	NOUN
ejpam-462	335	4	,	,	PUNCT
ejpam-462	335	5	we	we	PRON
ejpam-462	335	6	also	also	ADV
ejpam-462	335	7	performed	perform	VERB
ejpam-462	335	8	100	100	NUM
ejpam-462	335	9	replications	replication	NOUN
ejpam-462	335	10	of	of	ADP
ejpam-462	335	11	the	the	DET
ejpam-462	335	12	modeling	modeling	NOUN
ejpam-462	335	13	process	process	NOUN
ejpam-462	335	14	using	use	VERB
ejpam-462	335	15	aic	aic	PROPN
ejpam-462	335	16	to	to	PART
ejpam-462	335	17	drive	drive	VERB
ejpam-462	335	18	the	the	DET
ejpam-462	335	19	model	model	NOUN
ejpam-462	335	20	selection	selection	NOUN
ejpam-462	335	21	.	.	PUNCT
ejpam-462	336	1	the	the	DET
ejpam-462	336	2	best	well	ADV
ejpam-462	336	3	subset	subset	NOUN
ejpam-462	336	4	model	model	NOUN
ejpam-462	336	5	identified	identify	VERB
ejpam-462	336	6	by	by	ADP
ejpam-462	336	7	aic	aic	PROPN
ejpam-462	336	8	used	use	VERB
ejpam-462	336	9	82	82	NUM
ejpam-462	336	10	predictors	predictor	NOUN
ejpam-462	336	11	,	,	PUNCT
ejpam-462	336	12	more	more	ADJ
ejpam-462	336	13	than	than	ADP
ejpam-462	336	14	twice	twice	ADV
ejpam-462	336	15	as	as	ADV
ejpam-462	336	16	many	many	ADJ
ejpam-462	336	17	as	as	SCONJ
ejpam-462	336	18	shown	show	VERB
ejpam-462	336	19	here	here	ADV
ejpam-462	336	20	leading	lead	VERB
ejpam-462	336	21	to	to	ADP
ejpam-462	336	22	less	less	ADV
ejpam-462	336	23	precise	precise	ADJ
ejpam-462	336	24	forecasts	forecast	NOUN
ejpam-462	336	25	.	.	PUNCT
ejpam-462	337	1	it	it	PRON
ejpam-462	337	2	is	be	AUX
ejpam-462	337	3	interesting	interesting	ADJ
ejpam-462	337	4	to	to	PART
ejpam-462	337	5	note	note	VERB
ejpam-462	337	6	that	that	SCONJ
ejpam-462	337	7	this	this	DET
ejpam-462	337	8	parsimonious	parsimonious	ADJ
ejpam-462	337	9	model	model	NOUN
ejpam-462	337	10	only	only	ADV
ejpam-462	337	11	utilized	utilize	VERB
ejpam-462	337	12	nine	nine	NUM
ejpam-462	337	13	predictors	predictor	NOUN
ejpam-462	337	14	to	to	PART
ejpam-462	337	15	trade	trade	VERB
ejpam-462	337	16	the	the	DET
ejpam-462	337	17	target	target	NOUN
ejpam-462	337	18	index	index	NOUN
ejpam-462	337	19	,	,	PUNCT
ejpam-462	337	20	the	the	DET
ejpam-462	337	21	four	four	NUM
ejpam-462	337	22	most	most	ADV
ejpam-462	337	23	important	important	ADJ
ejpam-462	337	24	of	of	ADP
ejpam-462	337	25	which	which	PRON
ejpam-462	337	26	were	be	AUX
ejpam-462	337	27	:	:	PUNCT
ejpam-462	337	28	•	•	NUM
ejpam-462	337	29	xau	xau	X
ejpam-462	337	30	5th	5th	ADJ
ejpam-462	337	31	lag	lag	NOUN
ejpam-462	337	32	−0.393	−0.393	PROPN
ejpam-462	337	33	•	•	NUM
ejpam-462	337	34	rut	rut	NOUN
ejpam-462	337	35	2nd	2nd	PROPN
ejpam-462	337	36	lag	lag	VERB
ejpam-462	337	37	0.386	0.386	NUM
ejpam-462	337	38	•	•	NOUN
ejpam-462	337	39	spx	spx	PROPN
ejpam-462	337	40	2nd	2nd	PROPN
ejpam-462	337	41	lag	lag	NOUN
ejpam-462	337	42	−0.347	−0.347	ADJ
ejpam-462	337	43	•	•	ADP
ejpam-462	337	44	xau	xau	PROPN
ejpam-462	337	45	4th	4th	PROPN
ejpam-462	337	46	lag	lag	NOUN
ejpam-462	337	47	0.155	0.155	NUM
ejpam-462	337	48	according	accord	VERB
ejpam-462	337	49	to	to	ADP
ejpam-462	337	50	this	this	DET
ejpam-462	337	51	model	model	NOUN
ejpam-462	337	52	,	,	PUNCT
ejpam-462	337	53	the	the	DET
ejpam-462	337	54	spx	spx	PROPN
ejpam-462	337	55	is	be	AUX
ejpam-462	337	56	mostly	mostly	ADV
ejpam-462	337	57	influenced	influence	VERB
ejpam-462	337	58	by	by	ADP
ejpam-462	337	59	the	the	DET
ejpam-462	337	60	amex	amex	PROPN
ejpam-462	337	61	gold	gold	PROPN
ejpam-462	337	62	producers	producer	NOUN
ejpam-462	337	63	index	index	NOUN
ejpam-462	337	64	,	,	PUNCT
ejpam-462	337	65	the	the	DET
ejpam-462	337	66	russell	russell	PROPN
ejpam-462	337	67	2000	2000	NUM
ejpam-462	337	68	index	index	NOUN
ejpam-462	337	69	,	,	PUNCT
ejpam-462	337	70	and	and	CCONJ
ejpam-462	337	71	itself	itself	PRON
ejpam-462	337	72	.	.	PUNCT
ejpam-462	338	1	after	after	SCONJ
ejpam-462	338	2	the	the	DET
ejpam-462	338	3	best	good	ADJ
ejpam-462	338	4	var	var	NOUN
ejpam-462	338	5	coefficients	coefficient	NOUN
ejpam-462	338	6	were	be	AUX
ejpam-462	338	7	determined	determine	VERB
ejpam-462	338	8	by	by	ADP
ejpam-462	338	9	the	the	DET
ejpam-462	338	10	genetic	genetic	ADJ
ejpam-462	338	11	algorithm	algorithm	NOUN
ejpam-462	338	12	,	,	PUNCT
ejpam-462	338	13	the	the	DET
ejpam-462	338	14	direction	direction	NOUN
ejpam-462	338	15	of	of	ADP
ejpam-462	338	16	daily	daily	ADJ
ejpam-462	338	17	moves	move	NOUN
ejpam-462	338	18	was	be	AUX
ejpam-462	338	19	predicted	predict	VERB
ejpam-462	338	20	by	by	ADP
ejpam-462	338	21	si	si	PROPN
ejpam-462	338	22	gnum(õspx	gnum(õspx	PROPN
ejpam-462	338	23	t	t	PROPN
ejpam-462	338	24	)	)	PUNCT
ejpam-462	338	25	.	.	PUNCT
ejpam-462	339	1	interpreting	interpret	VERB
ejpam-462	339	2	these	these	DET
ejpam-462	339	3	predictions	prediction	NOUN
ejpam-462	339	4	as	as	ADP
ejpam-462	339	5	buy	buy	NOUN
ejpam-462	339	6	-	-	PUNCT
ejpam-462	339	7	long	long	ADJ
ejpam-462	339	8	or	or	CCONJ
ejpam-462	339	9	sell	sell	NOUN
ejpam-462	339	10	-	-	PUNCT
ejpam-462	339	11	short	short	ADJ
ejpam-462	339	12	signals	signal	NOUN
ejpam-462	339	13	,	,	PUNCT
ejpam-462	339	14	trading	trading	NOUN
ejpam-462	339	15	was	be	AUX
ejpam-462	339	16	simulated	simulate	VERB
ejpam-462	339	17	over	over	ADP
ejpam-462	339	18	the	the	DET
ejpam-462	339	19	entire	entire	ADJ
ejpam-462	339	20	6	6	NUM
ejpam-462	339	21	month	month	NOUN
ejpam-462	339	22	period	period	NOUN
ejpam-462	339	23	,	,	PUNCT
ejpam-462	339	24	with	with	ADP
ejpam-462	339	25	uncompounded	uncompounded	ADJ
ejpam-462	339	26	returns	return	NOUN
ejpam-462	339	27	accumulated	accumulate	VERB
ejpam-462	339	28	and	and	CCONJ
ejpam-462	339	29	shown	show	VERB
ejpam-462	339	30	in	in	ADP
ejpam-462	339	31	figure	figure	NOUN
ejpam-462	339	32	6	6	NUM
ejpam-462	339	33	.	.	PUNCT
ejpam-462	340	1	the	the	DET
ejpam-462	340	2	model	model	NOUN
ejpam-462	340	3	did	do	AUX
ejpam-462	340	4	not	not	PART
ejpam-462	340	5	perform	perform	VERB
ejpam-462	340	6	all	all	DET
ejpam-462	340	7	that	that	PRON
ejpam-462	340	8	well	well	ADV
ejpam-462	340	9	over	over	ADP
ejpam-462	340	10	the	the	DET
ejpam-462	340	11	in	in	ADP
ejpam-462	340	12	-	-	PUNCT
ejpam-462	340	13	sample	sample	NOUN
ejpam-462	340	14	period	period	NOUN
ejpam-462	340	15	,	,	PUNCT
ejpam-462	340	16	racking	rack	VERB
ejpam-462	340	17	up	up	ADP
ejpam-462	340	18	more	more	ADJ
ejpam-462	340	19	than	than	ADP
ejpam-462	340	20	3	3	NUM
ejpam-462	340	21	%	%	NOUN
ejpam-462	340	22	in	in	ADP
ejpam-462	340	23	losses	loss	NOUN
ejpam-462	340	24	while	while	SCONJ
ejpam-462	340	25	the	the	DET
ejpam-462	340	26	index	index	NOUN
ejpam-462	340	27	was	be	AUX
ejpam-462	340	28	flat	flat	ADJ
ejpam-462	340	29	.	.	PUNCT
ejpam-462	341	1	in	in	ADP
ejpam-462	341	2	the	the	DET
ejpam-462	341	3	testing	testing	NOUN
ejpam-462	341	4	period	period	NOUN
ejpam-462	341	5	,	,	PUNCT
ejpam-462	341	6	however	however	ADV
ejpam-462	341	7	,	,	PUNCT
ejpam-462	341	8	while	while	SCONJ
ejpam-462	341	9	the	the	DET
ejpam-462	341	10	index	index	NOUN
ejpam-462	341	11	lost	lose	VERB
ejpam-462	341	12	more	more	ADJ
ejpam-462	341	13	than	than	ADP
ejpam-462	341	14	15	15	NUM
ejpam-462	341	15	%	%	NOUN
ejpam-462	341	16	,	,	PUNCT
ejpam-462	341	17	the	the	DET
ejpam-462	341	18	model	model	NOUN
ejpam-462	341	19	made	make	VERB
ejpam-462	341	20	more	more	ADJ
ejpam-462	341	21	than	than	ADP
ejpam-462	341	22	17	17	NUM
ejpam-462	341	23	%	%	NOUN
ejpam-462	341	24	far	far	ADV
ejpam-462	341	25	outperforming	outperform	VERB
ejpam-462	341	26	the	the	DET
ejpam-462	341	27	benchmark	benchmark	NOUN
ejpam-462	341	28	.	.	PUNCT
ejpam-462	342	1	who	who	PRON
ejpam-462	342	2	would	would	AUX
ejpam-462	342	3	n’t	not	PART
ejpam-462	342	4	be	be	AUX
ejpam-462	342	5	happy	happy	ADJ
ejpam-462	342	6	with	with	ADP
ejpam-462	342	7	+17	+17	NUM
ejpam-462	342	8	%	%	NOUN
ejpam-462	342	9	gains	gain	NOUN
ejpam-462	342	10	while	while	SCONJ
ejpam-462	342	11	the	the	DET
ejpam-462	342	12	stock	stock	NOUN
ejpam-462	342	13	market	market	NOUN
ejpam-462	342	14	lost	lose	VERB
ejpam-462	342	15	so	so	ADV
ejpam-462	342	16	much	much	ADJ
ejpam-462	342	17	ground	ground	NOUN
ejpam-462	342	18	?	?	PUNCT
ejpam-462	343	1	out	out	ADP
ejpam-462	343	2	of	of	ADP
ejpam-462	343	3	the	the	DET
ejpam-462	343	4	100	100	NUM
ejpam-462	343	5	replications	replication	NOUN
ejpam-462	343	6	,	,	PUNCT
ejpam-462	343	7	90	90	NUM
ejpam-462	343	8	of	of	ADP
ejpam-462	343	9	the	the	DET
ejpam-462	343	10	models	model	NOUN
ejpam-462	343	11	outperformed	outperform	VERB
ejpam-462	343	12	the	the	DET
ejpam-462	343	13	index	index	NOUN
ejpam-462	343	14	for	for	ADP
ejpam-462	343	15	the	the	DET
ejpam-462	343	16	training	training	NOUN
ejpam-462	343	17	period	period	NOUN
ejpam-462	343	18	.	.	PUNCT
ejpam-462	344	1	while	while	SCONJ
ejpam-462	344	2	only	only	ADV
ejpam-462	344	3	15	15	NUM
ejpam-462	344	4	%	%	NOUN
ejpam-462	344	5	lost	lose	VERB
ejpam-462	344	6	money	money	NOUN
ejpam-462	344	7	during	during	ADP
ejpam-462	344	8	the	the	DET
ejpam-462	344	9	testing	testing	NOUN
ejpam-462	344	10	period	period	NOUN
ejpam-462	344	11	,	,	PUNCT
ejpam-462	344	12	all	all	PRON
ejpam-462	344	13	outperformed	outperform	VERB
ejpam-462	344	14	the	the	DET
ejpam-462	344	15	benchmark	benchmark	NOUN
ejpam-462	344	16	.	.	PUNCT
ejpam-462	345	1	in	in	ADP
ejpam-462	345	2	table	table	NOUN
ejpam-462	345	3	8	8	NUM
ejpam-462	345	4	,	,	PUNCT
ejpam-462	345	5	we	we	PRON
ejpam-462	345	6	’ve	’ve	AUX
ejpam-462	345	7	provided	provide	VERB
ejpam-462	345	8	results	result	NOUN
ejpam-462	345	9	from	from	ADP
ejpam-462	345	10	the	the	DET
ejpam-462	345	11	best	good	ADJ
ejpam-462	345	12	seven	seven	NUM
ejpam-462	345	13	models	model	NOUN
ejpam-462	345	14	(	(	PUNCT
ejpam-462	345	15	associated	associate	VERB
ejpam-462	345	16	with	with	ADP
ejpam-462	345	17	seven	seven	NUM
ejpam-462	345	18	lowest	low	ADJ
ejpam-462	345	19	icom	icom	PROPN
ejpam-462	345	20	p	p	PROPN
ejpam-462	345	21	values	value	NOUN
ejpam-462	345	22	)	)	PUNCT
ejpam-462	345	23	across	across	ADP
ejpam-462	345	24	all	all	DET
ejpam-462	345	25	simulations	simulation	NOUN
ejpam-462	345	26	.	.	PUNCT
ejpam-462	346	1	assuming	assume	VERB
ejpam-462	346	2	we	we	PRON
ejpam-462	346	3	were	be	AUX
ejpam-462	346	4	performing	perform	VERB
ejpam-462	346	5	the	the	DET
ejpam-462	346	6	model	model	NOUN
ejpam-462	346	7	training	training	NOUN
ejpam-462	346	8	in	in	ADP
ejpam-462	346	9	real	real	ADJ
ejpam-462	346	10	time	time	NOUN
ejpam-462	346	11	,	,	PUNCT
ejpam-462	346	12	clearly	clearly	ADV
ejpam-462	346	13	we	we	PRON
ejpam-462	346	14	would	would	AUX
ejpam-462	346	15	have	have	AUX
ejpam-462	346	16	been	be	AUX
ejpam-462	346	17	more	more	ADV
ejpam-462	346	18	interested	interested	ADJ
ejpam-462	346	19	in	in	ADP
ejpam-462	346	20	the	the	DET
ejpam-462	346	21	models	model	NOUN
ejpam-462	346	22	with	with	ADP
ejpam-462	346	23	both	both	CCONJ
ejpam-462	346	24	low	low	ADJ
ejpam-462	346	25	scores	score	NOUN
ejpam-462	346	26	and	and	CCONJ
ejpam-462	346	27	high	high	ADJ
ejpam-462	346	28	in	in	ADP
ejpam-462	346	29	-	-	PUNCT
ejpam-462	346	30	sample	sample	NOUN
ejpam-462	346	31	returns	return	NOUN
ejpam-462	346	32	.	.	PUNCT
ejpam-462	347	1	several	several	ADJ
ejpam-462	347	2	of	of	ADP
ejpam-462	347	3	these	these	DET
ejpam-462	347	4	models	model	NOUN
ejpam-462	347	5	had	have	VERB
ejpam-462	347	6	very	very	ADV
ejpam-462	347	7	good	good	ADJ
ejpam-462	347	8	out	out	ADP
ejpam-462	347	9	-	-	PUNCT
ejpam-462	347	10	of	of	ADP
ejpam-462	347	11	-	-	PUNCT
ejpam-462	347	12	sample	sample	NOUN
ejpam-462	347	13	performance	performance	NOUN
ejpam-462	347	14	.	.	PUNCT
ejpam-462	348	1	thus	thus	ADV
ejpam-462	348	2	,	,	PUNCT
ejpam-462	348	3	even	even	ADV
ejpam-462	348	4	if	if	SCONJ
ejpam-462	348	5	we	we	PRON
ejpam-462	348	6	were	be	AUX
ejpam-462	348	7	to	to	PART
ejpam-462	348	8	pass	pass	VERB
ejpam-462	348	9	over	over	ADP
ejpam-462	348	10	the	the	DET
ejpam-462	348	11	best	good	ADJ
ejpam-462	348	12	model	model	NOUN
ejpam-462	348	13	according	accord	VERB
ejpam-462	348	14	to	to	ADP
ejpam-462	348	15	icom	icom	PROPN
ejpam-462	348	16	p	p	PROPN
ejpam-462	348	17	,	,	PUNCT
ejpam-462	348	18	the	the	DET
ejpam-462	348	19	next	next	ADJ
ejpam-462	348	20	several	several	ADJ
ejpam-462	348	21	would	would	AUX
ejpam-462	348	22	perform	perform	VERB
ejpam-462	348	23	admirably	admirably	ADV
ejpam-462	348	24	.	.	PUNCT
ejpam-462	349	1	in	in	ADP
ejpam-462	349	2	fact	fact	NOUN
ejpam-462	349	3	,	,	PUNCT
ejpam-462	349	4	the	the	DET
ejpam-462	349	5	first	first	ADJ
ejpam-462	349	6	two	two	NUM
ejpam-462	349	7	have	have	VERB
ejpam-462	349	8	such	such	ADJ
ejpam-462	349	9	similar	similar	ADJ
ejpam-462	349	10	icom	icom	PROPN
ejpam-462	349	11	p	p	NOUN
ejpam-462	349	12	scores	score	NOUN
ejpam-462	349	13	(	(	PUNCT
ejpam-462	349	14	not	not	PART
ejpam-462	349	15	e1	e1	VERB
ejpam-462	349	16	apart	apart	ADV
ejpam-462	349	17	)	)	PUNCT
ejpam-462	349	18	that	that	SCONJ
ejpam-462	349	19	the	the	DET
ejpam-462	349	20	models	model	NOUN
ejpam-462	349	21	are	be	AUX
ejpam-462	349	22	indistinguishable	indistinguishable	ADJ
ejpam-462	349	23	.	.	PUNCT
ejpam-462	350	1	this	this	DET
ejpam-462	350	2	table	table	NOUN
ejpam-462	350	3	bolsters	bolster	VERB
ejpam-462	350	4	our	our	PRON
ejpam-462	350	5	confidence	confidence	NOUN
ejpam-462	350	6	that	that	SCONJ
ejpam-462	350	7	out	out	ADV
ejpam-462	350	8	-	-	PUNCT
ejpam-462	350	9	of	of	ADP
ejpam-462	350	10	-	-	PUNCT
ejpam-462	350	11	sample	sample	NOUN
ejpam-462	350	12	performance	performance	NOUN
ejpam-462	350	13	of	of	ADP
ejpam-462	350	14	our	our	PRON
ejpam-462	350	15	procedure	procedure	NOUN
ejpam-462	350	16	is	be	AUX
ejpam-462	350	17	generally	generally	ADV
ejpam-462	350	18	good	good	ADJ
ejpam-462	350	19	,	,	PUNCT
ejpam-462	350	20	despite	despite	SCONJ
ejpam-462	350	21	the	the	DET
ejpam-462	350	22	specific	specific	ADJ
ejpam-462	350	23	evolutionary	evolutionary	ADJ
ejpam-462	350	24	trajectory	trajectory	NOUN
ejpam-462	350	25	followed	follow	VERB
ejpam-462	350	26	by	by	ADP
ejpam-462	350	27	the	the	DET
ejpam-462	350	28	population	population	NOUN
ejpam-462	350	29	of	of	ADP
ejpam-462	350	30	chromosomes	chromosome	NOUN
ejpam-462	350	31	leading	lead	VERB
ejpam-462	350	32	to	to	ADP
ejpam-462	350	33	this	this	DET
ejpam-462	350	34	specific	specific	ADJ
ejpam-462	350	35	overall	overall	ADJ
ejpam-462	350	36	best	good	ADJ
ejpam-462	350	37	solution	solution	NOUN
ejpam-462	350	38	.	.	PUNCT
ejpam-462	351	1	finally	finally	ADV
ejpam-462	351	2	,	,	PUNCT
ejpam-462	351	3	we	we	PRON
ejpam-462	351	4	address	address	VERB
ejpam-462	351	5	the	the	DET
ejpam-462	351	6	precision	precision	NOUN
ejpam-462	351	7	of	of	ADP
ejpam-462	351	8	the	the	DET
ejpam-462	351	9	forecast	forecast	NOUN
ejpam-462	351	10	errors	error	NOUN
ejpam-462	351	11	from	from	ADP
ejpam-462	351	12	this	this	DET
ejpam-462	351	13	very	very	ADV
ejpam-462	351	14	parsimonious	parsimonious	ADJ
ejpam-462	351	15	model	model	NOUN
ejpam-462	351	16	,	,	PUNCT
ejpam-462	351	17	using	use	VERB
ejpam-462	351	18	the	the	DET
ejpam-462	351	19	procedure	procedure	NOUN
ejpam-462	351	20	detailed	detail	VERB
ejpam-462	351	21	in	in	ADP
ejpam-462	351	22	section	section	NOUN
ejpam-462	351	23	2.2	2.2	NUM
ejpam-462	351	24	.	.	PUNCT
ejpam-462	352	1	in	in	ADP
ejpam-462	352	2	the	the	DET
ejpam-462	352	3	interest	interest	NOUN
ejpam-462	352	4	of	of	ADP
ejpam-462	352	5	simplified	simplified	ADJ
ejpam-462	352	6	output	output	NOUN
ejpam-462	352	7	,	,	PUNCT
ejpam-462	352	8	the	the	DET
ejpam-462	352	9	entire	entire	ADJ
ejpam-462	352	10	a.	a.	NOUN
ejpam-462	352	11	howe	howe	NOUN
ejpam-462	352	12	and	and	CCONJ
ejpam-462	352	13	h.	h.	PROPN
ejpam-462	352	14	bozdogan	bozdogan	PROPN
ejpam-462	352	15	/	/	SYM
ejpam-462	352	16	eur	eur	PROPN
ejpam-462	352	17	.	.	PUNCT
ejpam-462	353	1	j.	j.	PROPN
ejpam-462	353	2	pure	pure	PROPN
ejpam-462	353	3	appl	appl	PROPN
ejpam-462	353	4	.	.	PROPN
ejpam-462	353	5	math	math	PROPN
ejpam-462	353	6	,	,	PUNCT
ejpam-462	353	7	3	3	NUM
ejpam-462	353	8	(	(	PUNCT
ejpam-462	353	9	2010	2010	NUM
ejpam-462	353	10	)	)	PUNCT
ejpam-462	353	11	,	,	PUNCT
ejpam-462	353	12	382	382	NUM
ejpam-462	353	13	-	-	SYM
ejpam-462	353	14	405	405	NUM
ejpam-462	353	15	399	399	NUM
ejpam-462	353	16	−10	−10	NOUN
ejpam-462	353	17	−5	−5	ADV
ejpam-462	353	18	0	0	NUM
ejpam-462	353	19	5	5	NUM
ejpam-462	353	20	10	10	NUM
ejpam-462	353	21	p	p	NOUN
ejpam-462	353	22	er	er	INTJ
ejpam-462	353	23	ce	ce	NOUN
ejpam-462	353	24	nt	not	PART
ejpam-462	353	25	01/02/2002	01/02/2002	NUM
ejpam-462	353	26	−	−	NOUN
ejpam-462	353	27	03/28/2002	03/28/2002	NUM
ejpam-462	353	28	index	index	NOUN
ejpam-462	353	29	:	:	PUNCT
ejpam-462	354	1	−0.40	−0.40	ADP
ejpam-462	354	2	%	%	NOUN
ejpam-462	354	3	,	,	PUNCT
ejpam-462	354	4	model	model	NOUN
ejpam-462	354	5	:	:	PUNCT
ejpam-462	354	6	−3.14	−3.14	NOUN
ejpam-462	354	7	%	%	NOUN
ejpam-462	354	8	benchmark	benchmark	NOUN
ejpam-462	354	9	model	model	NOUN
ejpam-462	354	10	0	0	NUM
ejpam-462	354	11	20	20	NUM
ejpam-462	354	12	40	40	NUM
ejpam-462	354	13	60	60	NUM
ejpam-462	354	14	80	80	NUM
ejpam-462	354	15	100	100	NUM
ejpam-462	354	16	120	120	NUM
ejpam-462	354	17	140	140	NUM
ejpam-462	354	18	−20	−20	NOUN
ejpam-462	354	19	−10	−10	X
ejpam-462	354	20	0	0	NUM
ejpam-462	354	21	10	10	NUM
ejpam-462	354	22	20	20	NUM
ejpam-462	354	23	day	day	NOUN
ejpam-462	354	24	p	p	PROPN
ejpam-462	354	25	er	er	INTJ
ejpam-462	354	26	ce	ce	NOUN
ejpam-462	354	27	nt	not	PART
ejpam-462	354	28	01/02/2002	01/02/2002	NUM
ejpam-462	354	29	−	−	PROPN
ejpam-462	354	30	06/28/2002	06/28/2002	NUM
ejpam-462	354	31	index	index	NOUN
ejpam-462	354	32	:	:	PUNCT
ejpam-462	354	33	−15.68	−15.68	ADJ
ejpam-462	354	34	%	%	NOUN
ejpam-462	354	35	,	,	PUNCT
ejpam-462	354	36	model	model	NOUN
ejpam-462	354	37	:	:	PUNCT
ejpam-462	354	38	14.00	14.00	NUM
ejpam-462	354	39	%	%	NOUN
ejpam-462	354	40	benchmark	benchmark	NOUN
ejpam-462	354	41	model	model	NOUN
ejpam-462	354	42	figure	figure	NOUN
ejpam-462	354	43	6	6	NUM
ejpam-462	354	44	:	:	PUNCT
ejpam-462	354	45	trading	trading	NOUN
ejpam-462	354	46	results	result	NOUN
ejpam-462	354	47	from	from	ADP
ejpam-462	354	48	best	good	ADJ
ejpam-462	354	49	subset	subset	ADJ
ejpam-462	354	50	model	model	NOUN
ejpam-462	354	51	.	.	PUNCT
ejpam-462	355	1	forecast	forecast	PROPN
ejpam-462	355	2	horizon	horizon	PROPN
ejpam-462	355	3	was	be	AUX
ejpam-462	355	4	divided	divide	VERB
ejpam-462	355	5	into	into	ADP
ejpam-462	355	6	increments	increment	NOUN
ejpam-462	355	7	of	of	ADP
ejpam-462	355	8	10	10	NUM
ejpam-462	355	9	.	.	PUNCT
ejpam-462	356	1	table	table	NOUN
ejpam-462	356	2	9	9	NUM
ejpam-462	356	3	shows	show	VERB
ejpam-462	356	4	the	the	DET
ejpam-462	356	5	mse	mse	PROPN
ejpam-462	356	6	’s	’s	X
ejpam-462	356	7	for	for	ADP
ejpam-462	356	8	just	just	ADV
ejpam-462	356	9	the	the	DET
ejpam-462	356	10	spx	spx	PROPN
ejpam-462	356	11	index	index	NOUN
ejpam-462	356	12	.	.	PUNCT
ejpam-462	357	1	even	even	ADV
ejpam-462	357	2	as	as	ADV
ejpam-462	357	3	far	far	ADV
ejpam-462	357	4	as	as	ADP
ejpam-462	357	5	100	100	NUM
ejpam-462	357	6	observations	observation	NOUN
ejpam-462	357	7	into	into	ADP
ejpam-462	357	8	the	the	DET
ejpam-462	357	9	future	future	NOUN
ejpam-462	357	10	,	,	PUNCT
ejpam-462	357	11	we	we	PRON
ejpam-462	357	12	see	see	VERB
ejpam-462	357	13	that	that	SCONJ
ejpam-462	357	14	the	the	DET
ejpam-462	357	15	subset	subset	NOUN
ejpam-462	357	16	model	model	NOUN
ejpam-462	357	17	made	make	VERB
ejpam-462	357	18	substantially	substantially	ADV
ejpam-462	357	19	(	(	PUNCT
ejpam-462	357	20	order	order	NOUN
ejpam-462	357	21	of	of	ADP
ejpam-462	357	22	2	2	NUM
ejpam-462	357	23	or	or	CCONJ
ejpam-462	357	24	better	well	ADJ
ejpam-462	357	25	)	)	PUNCT
ejpam-462	357	26	more	more	ADV
ejpam-462	357	27	precise	precise	ADJ
ejpam-462	357	28	forecasts	forecast	NOUN
ejpam-462	357	29	than	than	ADP
ejpam-462	357	30	the	the	DET
ejpam-462	357	31	saturated	saturate	VERB
ejpam-462	357	32	model	model	NOUN
ejpam-462	357	33	.	.	PUNCT
ejpam-462	358	1	we	we	PRON
ejpam-462	358	2	can	can	AUX
ejpam-462	358	3	also	also	ADV
ejpam-462	358	4	see	see	VERB
ejpam-462	358	5	this	this	PRON
ejpam-462	358	6	demonstrated	demonstrate	VERB
ejpam-462	358	7	graphically	graphically	ADV
ejpam-462	358	8	in	in	ADP
ejpam-462	358	9	figure	figure	NOUN
ejpam-462	358	10	7	7	NUM
ejpam-462	358	11	.	.	PUNCT
ejpam-462	359	1	it	it	PRON
ejpam-462	359	2	is	be	AUX
ejpam-462	359	3	interesting	interesting	ADJ
ejpam-462	359	4	to	to	PART
ejpam-462	359	5	note	note	VERB
ejpam-462	359	6	how	how	SCONJ
ejpam-462	359	7	similar	similar	ADJ
ejpam-462	359	8	the	the	DET
ejpam-462	359	9	point	point	NOUN
ejpam-462	359	10	estimates	estimate	NOUN
ejpam-462	359	11	were	be	AUX
ejpam-462	359	12	for	for	ADP
ejpam-462	359	13	both	both	DET
ejpam-462	359	14	models	model	NOUN
ejpam-462	359	15	.	.	PUNCT
ejpam-462	360	1	at	at	ADP
ejpam-462	360	2	least	least	ADJ
ejpam-462	360	3	on	on	ADP
ejpam-462	360	4	this	this	DET
ejpam-462	360	5	wide	wide	ADJ
ejpam-462	360	6	scale	scale	NOUN
ejpam-462	360	7	,	,	PUNCT
ejpam-462	360	8	they	they	PRON
ejpam-462	360	9	overlap	overlap	VERB
ejpam-462	360	10	enough	enough	ADV
ejpam-462	360	11	to	to	PART
ejpam-462	360	12	blur	blur	VERB
ejpam-462	360	13	the	the	DET
ejpam-462	360	14	differences	difference	NOUN
ejpam-462	360	15	.	.	PUNCT
ejpam-462	361	1	we	we	PRON
ejpam-462	361	2	see	see	VERB
ejpam-462	361	3	,	,	PUNCT
ejpam-462	361	4	however	however	ADV
ejpam-462	361	5	,	,	PUNCT
ejpam-462	361	6	how	how	SCONJ
ejpam-462	361	7	much	much	ADV
ejpam-462	361	8	wider	wide	ADJ
ejpam-462	361	9	are	be	AUX
ejpam-462	361	10	the	the	DET
ejpam-462	361	11	error	error	NOUN
ejpam-462	361	12	bands	band	NOUN
ejpam-462	361	13	(	(	PUNCT
ejpam-462	361	14	±2σ̂	±2σ̂	NOUN
ejpam-462	361	15	)	)	PUNCT
ejpam-462	361	16	when	when	SCONJ
ejpam-462	361	17	constructed	construct	VERB
ejpam-462	361	18	using	use	VERB
ejpam-462	361	19	the	the	DET
ejpam-462	361	20	saturated	saturate	VERB
ejpam-462	361	21	model	model	NOUN
ejpam-462	361	22	.	.	PUNCT
ejpam-462	362	1	thus	thus	ADV
ejpam-462	362	2	,	,	PUNCT
ejpam-462	362	3	the	the	DET
ejpam-462	362	4	methods	method	NOUN
ejpam-462	362	5	presented	present	VERB
ejpam-462	362	6	have	have	AUX
ejpam-462	362	7	allowed	allow	VERB
ejpam-462	362	8	us	we	PRON
ejpam-462	362	9	to	to	PART
ejpam-462	362	10	build	build	VERB
ejpam-462	362	11	a	a	DET
ejpam-462	362	12	model	model	NOUN
ejpam-462	362	13	that	that	PRON
ejpam-462	362	14	is	be	AUX
ejpam-462	362	15	:	:	PUNCT
ejpam-462	362	16	•	•	PRON
ejpam-462	362	17	not	not	PART
ejpam-462	362	18	overly	overly	ADV
ejpam-462	362	19	complex	complex	ADJ
ejpam-462	362	20	•	•	NOUN
ejpam-462	362	21	fits	fit	VERB
ejpam-462	362	22	the	the	DET
ejpam-462	362	23	data	datum	NOUN
ejpam-462	362	24	extremely	extremely	ADV
ejpam-462	362	25	well	well	ADV
ejpam-462	362	26	•	•	NOUN
ejpam-462	362	27	is	be	AUX
ejpam-462	362	28	very	very	ADV
ejpam-462	362	29	precise	precise	ADJ
ejpam-462	362	30	a.	a.	NOUN
ejpam-462	362	31	howe	howe	NOUN
ejpam-462	362	32	and	and	CCONJ
ejpam-462	362	33	h.	h.	PROPN
ejpam-462	362	34	bozdogan	bozdogan	PROPN
ejpam-462	362	35	/	/	SYM
ejpam-462	362	36	eur	eur	PROPN
ejpam-462	362	37	.	.	PUNCT
ejpam-462	363	1	j.	j.	PROPN
ejpam-462	363	2	pure	pure	PROPN
ejpam-462	363	3	appl	appl	PROPN
ejpam-462	363	4	.	.	PROPN
ejpam-462	363	5	math	math	PROPN
ejpam-462	363	6	,	,	PUNCT
ejpam-462	363	7	3	3	NUM
ejpam-462	363	8	(	(	PUNCT
ejpam-462	363	9	2010	2010	NUM
ejpam-462	363	10	)	)	PUNCT
ejpam-462	363	11	,	,	PUNCT
ejpam-462	363	12	382	382	NUM
ejpam-462	363	13	-	-	SYM
ejpam-462	363	14	405	405	NUM
ejpam-462	363	15	400	400	NUM
ejpam-462	363	16	10	10	NUM
ejpam-462	363	17	20	20	NUM
ejpam-462	363	18	30	30	NUM
ejpam-462	363	19	40	40	NUM
ejpam-462	363	20	50	50	NUM
ejpam-462	363	21	60	60	NUM
ejpam-462	363	22	70	70	NUM
ejpam-462	363	23	80	80	NUM
ejpam-462	363	24	90	90	NUM
ejpam-462	363	25	100	100	NUM
ejpam-462	363	26	subset	subset	VERB
ejpam-462	363	27	±2σ	±2σ	PRON
ejpam-462	363	28	saturated	saturate	VERB
ejpam-462	363	29	±2σ	±2σ	PROPN
ejpam-462	363	30	figure	figure	NOUN
ejpam-462	363	31	7	7	NUM
ejpam-462	363	32	:	:	PUNCT
ejpam-462	363	33	s&p	s&p	PROPN
ejpam-462	363	34	500	500	NUM
ejpam-462	363	35	fore	fore	NOUN
ejpam-462	363	36	ast	ast	NOUN
ejpam-462	363	37	point	point	NOUN
ejpam-462	363	38	estimates	estimate	NOUN
ejpam-462	363	39	and	and	CCONJ
ejpam-462	363	40	error	error	NOUN
ejpam-462	363	41	bands	band	NOUN
ejpam-462	363	42	for	for	ADP
ejpam-462	363	43	subset	subset	NOUN
ejpam-462	363	44	and	and	CCONJ
ejpam-462	363	45	saturated	saturated	ADJ
ejpam-462	363	46	models	model	NOUN
ejpam-462	363	47	.	.	PUNCT
ejpam-462	364	1	a.	a.	NOUN
ejpam-462	364	2	howe	howe	PROPN
ejpam-462	364	3	and	and	CCONJ
ejpam-462	364	4	h.	h.	PROPN
ejpam-462	364	5	bozdogan	bozdogan	PROPN
ejpam-462	364	6	/	/	SYM
ejpam-462	364	7	eur	eur	PROPN
ejpam-462	364	8	.	.	PUNCT
ejpam-462	365	1	j.	j.	PROPN
ejpam-462	365	2	pure	pure	PROPN
ejpam-462	365	3	appl	appl	PROPN
ejpam-462	365	4	.	.	PROPN
ejpam-462	365	5	math	math	PROPN
ejpam-462	365	6	,	,	PUNCT
ejpam-462	365	7	3	3	NUM
ejpam-462	365	8	(	(	PUNCT
ejpam-462	365	9	2010	2010	NUM
ejpam-462	365	10	)	)	PUNCT
ejpam-462	365	11	,	,	PUNCT
ejpam-462	365	12	382	382	NUM
ejpam-462	365	13	-	-	SYM
ejpam-462	365	14	405	405	NUM
ejpam-462	365	15	401table	401table	PROPN
ejpam-462	365	16	7	7	NUM
ejpam-462	365	17	:	:	PUNCT
ejpam-462	365	18	estimated	estimate	VERB
ejpam-462	365	19	coe	coe	PROPN
ejpam-462	365	20	�	�	PROPN
ejpam-462	365	21	ients	ient	NOUN
ejpam-462	365	22	from	from	ADP
ejpam-462	365	23	best	good	ADJ
ejpam-462	365	24	subset	subset	VERB
ejpam-462	365	25	var	var	NOUN
ejpam-462	365	26	model	model	NOUN
ejpam-462	365	27	.	.	PUNCT
ejpam-462	366	1	dj20	dj20	PROPN
ejpam-462	366	2	mid	mid	ADJ
ejpam-462	366	3	ndx	ndx	PROPN
ejpam-462	366	4	rut	rut	NOUN
ejpam-462	366	5	spx	spx	PROPN
ejpam-462	366	6	xau	xau	PROPN
ejpam-462	366	7	const	const	PROPN
ejpam-462	366	8	8.130	8.130	NUM
ejpam-462	366	9	·	·	PUNCT
ejpam-462	366	10	·	·	PUNCT
ejpam-462	366	11	·	·	PUNCT
ejpam-462	366	12	·	·	PUNCT
ejpam-462	366	13	·	·	PUNCT
ejpam-462	366	14	dj20(1	dj20(1	X
ejpam-462	366	15	)	)	PUNCT
ejpam-462	366	16	·	·	PUNCT
ejpam-462	366	17	·	·	PUNCT
ejpam-462	366	18	·	·	PUNCT
ejpam-462	366	19	·	·	PUNCT
ejpam-462	366	20	·	·	PUNCT
ejpam-462	366	21	·	·	PUNCT
ejpam-462	366	22	mid(1	mid(1	NUM
ejpam-462	366	23	)	)	PUNCT
ejpam-462	366	24	0.459	0.459	NUM
ejpam-462	366	25	·	·	PUNCT
ejpam-462	366	26	·	·	PUNCT
ejpam-462	366	27	·	·	PUNCT
ejpam-462	367	1	−0.039	−0.039	PROPN
ejpam-462	367	2	−0.008	−0.008	NOUN
ejpam-462	367	3	ndx(1	ndx(1	ADV
ejpam-462	367	4	)	)	PUNCT
ejpam-462	367	5	0.797	0.797	NUM
ejpam-462	367	6	·	·	PUNCT
ejpam-462	367	7	·	·	PUNCT
ejpam-462	367	8	·	·	PUNCT
ejpam-462	367	9	·	·	PUNCT
ejpam-462	367	10	·	·	PUNCT
ejpam-462	367	11	rut(1	rut(1	NOUN
ejpam-462	367	12	)	)	PUNCT
ejpam-462	367	13	−4.267	−4.267	PROPN
ejpam-462	367	14	·	·	PUNCT
ejpam-462	367	15	·	·	PUNCT
ejpam-462	367	16	·	·	PUNCT
ejpam-462	367	17	·	·	PUNCT
ejpam-462	367	18	·	·	PUNCT
ejpam-462	367	19	spx(1	spx(1	NOUN
ejpam-462	367	20	)	)	PUNCT
ejpam-462	367	21	·	·	PUNCT
ejpam-462	367	22	·	·	PUNCT
ejpam-462	367	23	·	·	PUNCT
ejpam-462	368	1	−0.022	−0.022	X
ejpam-462	368	2	·	·	PUNCT
ejpam-462	368	3	·	·	PUNCT
ejpam-462	368	4	xau(1	xau(1	NOUN
ejpam-462	368	5	)	)	PUNCT
ejpam-462	368	6	·	·	PUNCT
ejpam-462	368	7	·	·	PUNCT
ejpam-462	368	8	·	·	PUNCT
ejpam-462	368	9	·	·	PUNCT
ejpam-462	368	10	·	·	PUNCT
ejpam-462	368	11	·	·	PUNCT
ejpam-462	368	12	dj20(2	dj20(2	X
ejpam-462	368	13	)	)	PUNCT
ejpam-462	368	14	·	·	PUNCT
ejpam-462	368	15	·	·	PUNCT
ejpam-462	368	16	·	·	PUNCT
ejpam-462	368	17	·	·	PUNCT
ejpam-462	368	18	·	·	PUNCT
ejpam-462	368	19	·	·	PUNCT
ejpam-462	368	20	mid(2	mid(2	NOUN
ejpam-462	368	21	)	)	PUNCT
ejpam-462	368	22	·	·	PUNCT
ejpam-462	368	23	·	·	PUNCT
ejpam-462	368	24	·	·	PUNCT
ejpam-462	368	25	·	·	PUNCT
ejpam-462	368	26	·	·	PUNCT
ejpam-462	368	27	·	·	PUNCT
ejpam-462	368	28	ndx(2	ndx(2	X
ejpam-462	368	29	)	)	PUNCT
ejpam-462	368	30	·	·	PUNCT
ejpam-462	368	31	·	·	PUNCT
ejpam-462	368	32	·	·	PUNCT
ejpam-462	368	33	·	·	PUNCT
ejpam-462	369	1	0.049	0.049	NUM
ejpam-462	369	2	·	·	PUNCT
ejpam-462	369	3	rut(2	rut(2	NOUN
ejpam-462	369	4	)	)	PUNCT
ejpam-462	369	5	·	·	PUNCT
ejpam-462	369	6	·	·	PUNCT
ejpam-462	369	7	·	·	PUNCT
ejpam-462	370	1	0.133	0.133	NUM
ejpam-462	370	2	0.386	0.386	NUM
ejpam-462	370	3	·	·	PUNCT
ejpam-462	370	4	spx(2	spx(2	X
ejpam-462	370	5	)	)	PUNCT
ejpam-462	370	6	·	·	PUNCT
ejpam-462	370	7	·	·	PUNCT
ejpam-462	370	8	·	·	PUNCT
ejpam-462	370	9	·	·	PUNCT
ejpam-462	370	10	−0.347	−0.347	ADJ
ejpam-462	370	11	·	·	PUNCT
ejpam-462	370	12	xau(2	xau(2	NUM
ejpam-462	370	13	)	)	PUNCT
ejpam-462	370	14	·	·	PUNCT
ejpam-462	370	15	·	·	PUNCT
ejpam-462	371	1	0.332	0.332	NUM
ejpam-462	371	2	−0.022	−0.022	PROPN
ejpam-462	371	3	·	·	PUNCT
ejpam-462	371	4	·	·	PUNCT
ejpam-462	371	5	dj20(3	dj20(3	NOUN
ejpam-462	371	6	)	)	PUNCT
ejpam-462	371	7	·	·	PUNCT
ejpam-462	371	8	·	·	PUNCT
ejpam-462	371	9	·	·	PUNCT
ejpam-462	371	10	·	·	PUNCT
ejpam-462	371	11	·	·	PUNCT
ejpam-462	371	12	·	·	PUNCT
ejpam-462	371	13	mid(3	mid(3	NOUN
ejpam-462	371	14	)	)	PUNCT
ejpam-462	371	15	·	·	PUNCT
ejpam-462	371	16	0.157	0.157	NUM
ejpam-462	371	17	·	·	PUNCT
ejpam-462	371	18	·	·	PUNCT
ejpam-462	371	19	·	·	PUNCT
ejpam-462	371	20	·	·	PUNCT
ejpam-462	371	21	ndx(3	ndx(3	X
ejpam-462	371	22	)	)	PUNCT
ejpam-462	371	23	·	·	PUNCT
ejpam-462	371	24	·	·	PUNCT
ejpam-462	371	25	·	·	PUNCT
ejpam-462	371	26	·	·	PUNCT
ejpam-462	371	27	·	·	PUNCT
ejpam-462	371	28	−0.012	−0.012	NOUN
ejpam-462	371	29	rut(3	rut(3	NOUN
ejpam-462	371	30	)	)	PUNCT
ejpam-462	371	31	·	·	PUNCT
ejpam-462	372	1	−0.192	−0.192	X
ejpam-462	372	2	·	·	PUNCT
ejpam-462	372	3	·	·	PUNCT
ejpam-462	372	4	−0.087	−0.087	PROPN
ejpam-462	372	5	·	·	PUNCT
ejpam-462	372	6	spx(3	spx(3	NOUN
ejpam-462	372	7	)	)	PUNCT
ejpam-462	372	8	·	·	PUNCT
ejpam-462	373	1	−0.017	−0.017	NUM
ejpam-462	373	2	·	·	PUNCT
ejpam-462	373	3	·	·	PUNCT
ejpam-462	373	4	·	·	PUNCT
ejpam-462	373	5	·	·	PUNCT
ejpam-462	373	6	xau(3	xau(3	NUM
ejpam-462	373	7	)	)	PUNCT
ejpam-462	373	8	−3.555	−3.555	PROPN
ejpam-462	373	9	·	·	PUNCT
ejpam-462	373	10	·	·	PUNCT
ejpam-462	373	11	·	·	PUNCT
ejpam-462	373	12	·	·	PUNCT
ejpam-462	373	13	·	·	PUNCT
ejpam-462	373	14	dj20(4	dj20(4	NOUN
ejpam-462	373	15	)	)	PUNCT
ejpam-462	373	16	·	·	PUNCT
ejpam-462	373	17	·	·	PUNCT
ejpam-462	374	1	0.079	0.079	NUM
ejpam-462	374	2	−0.007	−0.007	NOUN
ejpam-462	374	3	·	·	PUNCT
ejpam-462	374	4	·	·	PUNCT
ejpam-462	374	5	mid(4	mid(4	ADJ
ejpam-462	374	6	)	)	PUNCT
ejpam-462	374	7	4.454	4.454	NUM
ejpam-462	374	8	·	·	PUNCT
ejpam-462	374	9	·	·	PUNCT
ejpam-462	374	10	·	·	PUNCT
ejpam-462	374	11	·	·	PUNCT
ejpam-462	374	12	·	·	PUNCT
ejpam-462	374	13	ndx(4	ndx(4	X
ejpam-462	374	14	)	)	PUNCT
ejpam-462	374	15	0.401	0.401	NUM
ejpam-462	374	16	−0.014	−0.014	X
ejpam-462	374	17	·	·	PUNCT
ejpam-462	374	18	·	·	PUNCT
ejpam-462	374	19	·	·	PUNCT
ejpam-462	374	20	·	·	PUNCT
ejpam-462	374	21	rut(4	rut(4	NOUN
ejpam-462	374	22	)	)	PUNCT
ejpam-462	374	23	−4.938	−4.938	CCONJ
ejpam-462	374	24	0.025	0.025	NUM
ejpam-462	374	25	−0.470	−0.470	NOUN
ejpam-462	374	26	·	·	PUNCT
ejpam-462	374	27	·	·	PUNCT
ejpam-462	374	28	·	·	PUNCT
ejpam-462	374	29	spx(4	spx(4	NOUN
ejpam-462	374	30	)	)	PUNCT
ejpam-462	374	31	−1.824	−1.824	NOUN
ejpam-462	374	32	·	·	PUNCT
ejpam-462	374	33	·	·	PUNCT
ejpam-462	374	34	·	·	PUNCT
ejpam-462	374	35	·	·	PUNCT
ejpam-462	374	36	·	·	PUNCT
ejpam-462	374	37	xau(4	xau(4	X
ejpam-462	374	38	)	)	PUNCT
ejpam-462	374	39	·	·	PUNCT
ejpam-462	375	1	0.174	0.174	NUM
ejpam-462	375	2	−0.635	−0.635	NOUN
ejpam-462	375	3	·	·	PUNCT
ejpam-462	375	4	0.155	0.155	NUM
ejpam-462	375	5	0.064	0.064	NUM
ejpam-462	375	6	dj20(5	dj20(5	PROPN
ejpam-462	375	7	)	)	PUNCT
ejpam-462	375	8	·	·	PUNCT
ejpam-462	375	9	·	·	PUNCT
ejpam-462	375	10	·	·	PUNCT
ejpam-462	375	11	·	·	PUNCT
ejpam-462	375	12	·	·	PUNCT
ejpam-462	375	13	·	·	PUNCT
ejpam-462	375	14	mid(5	mid(5	X
ejpam-462	375	15	)	)	PUNCT
ejpam-462	375	16	·	·	PUNCT
ejpam-462	376	1	0.009	0.009	NUM
ejpam-462	376	2	·	·	PUNCT
ejpam-462	376	3	·	·	PUNCT
ejpam-462	376	4	·	·	PUNCT
ejpam-462	376	5	·	·	PUNCT
ejpam-462	376	6	ndx(5	ndx(5	NUM
ejpam-462	376	7	)	)	PUNCT
ejpam-462	376	8	·	·	PUNCT
ejpam-462	376	9	·	·	PUNCT
ejpam-462	376	10	·	·	PUNCT
ejpam-462	376	11	·	·	PUNCT
ejpam-462	376	12	·	·	PUNCT
ejpam-462	376	13	·	·	PUNCT
ejpam-462	376	14	rut(5	rut(5	NOUN
ejpam-462	376	15	)	)	PUNCT
ejpam-462	376	16	·	·	PUNCT
ejpam-462	376	17	·	·	PUNCT
ejpam-462	376	18	0.322	0.322	NUM
ejpam-462	376	19	·	·	PUNCT
ejpam-462	376	20	−0.058	−0.058	PROPN
ejpam-462	376	21	·	·	PUNCT
ejpam-462	376	22	spx(5	spx(5	PROPN
ejpam-462	376	23	)	)	PUNCT
ejpam-462	376	24	·	·	PUNCT
ejpam-462	376	25	·	·	PUNCT
ejpam-462	376	26	·	·	PUNCT
ejpam-462	376	27	·	·	PUNCT
ejpam-462	376	28	0.021	0.021	NUM
ejpam-462	376	29	·	·	PUNCT
ejpam-462	376	30	xau(5	xau(5	NOUN
ejpam-462	376	31	)	)	PUNCT
ejpam-462	376	32	−6.665	−6.665	ADV
ejpam-462	376	33	·	·	PUNCT
ejpam-462	376	34	·	·	PUNCT
ejpam-462	376	35	·	·	PUNCT
ejpam-462	376	36	−0.393	−0.393	VERB
ejpam-462	376	37	·	·	SYM
ejpam-462	376	38	table	table	NOUN
ejpam-462	376	39	8	8	NUM
ejpam-462	376	40	:	:	PUNCT
ejpam-462	376	41	trading	trading	NOUN
ejpam-462	376	42	results	result	NOUN
ejpam-462	376	43	from	from	ADP
ejpam-462	376	44	best	good	ADJ
ejpam-462	376	45	7	7	NUM
ejpam-462	376	46	subset	subset	VERB
ejpam-462	376	47	var	var	NOUN
ejpam-462	376	48	models	model	NOUN
ejpam-462	376	49	.	.	PUNCT
ejpam-462	377	1	score	score	NOUN
ejpam-462	377	2	in	in	ADP
ejpam-462	377	3	-	-	PUNCT
ejpam-462	377	4	sample	sample	NOUN
ejpam-462	377	5	%	%	NOUN
ejpam-462	377	6	out	out	ADP
ejpam-462	377	7	-	-	PUNCT
ejpam-462	377	8	sample	sample	NOUN
ejpam-462	377	9	%	%	NOUN
ejpam-462	377	10	−4284.11	−4284.11	INTJ
ejpam-462	378	1	−3.14	−3.14	PROPN
ejpam-462	378	2	17.14	17.14	NUM
ejpam-462	378	3	−4283.64	−4283.64	PROPN
ejpam-462	378	4	7.40	7.40	NUM
ejpam-462	378	5	18.16	18.16	NUM
ejpam-462	378	6	−4277.51	−4277.51	PROPN
ejpam-462	379	1	3.49	3.49	NUM
ejpam-462	379	2	5.95	5.95	NUM
ejpam-462	379	3	−4277.35	−4277.35	NOUN
ejpam-462	379	4	0.09	0.09	NUM
ejpam-462	379	5	13.38	13.38	NUM
ejpam-462	379	6	−4276.85	−4276.85	PROPN
ejpam-462	379	7	13.33	13.33	NUM
ejpam-462	379	8	15.65	15.65	NUM
ejpam-462	379	9	−4275.28	−4275.28	PROPN
ejpam-462	379	10	3.27	3.27	NUM
ejpam-462	379	11	24.73	24.73	NUM
ejpam-462	379	12	−4274.25	−4274.25	PROPN
ejpam-462	379	13	10.64	10.64	NUM
ejpam-462	379	14	28.25	28.25	NUM
ejpam-462	379	15	a.	a.	NOUN
ejpam-462	379	16	howe	howe	NOUN
ejpam-462	379	17	and	and	CCONJ
ejpam-462	379	18	h.	h.	PROPN
ejpam-462	379	19	bozdogan	bozdogan	PROPN
ejpam-462	379	20	/	/	SYM
ejpam-462	379	21	eur	eur	PROPN
ejpam-462	379	22	.	.	PUNCT
ejpam-462	380	1	j.	j.	PROPN
ejpam-462	380	2	pure	pure	PROPN
ejpam-462	380	3	appl	appl	PROPN
ejpam-462	380	4	.	.	PROPN
ejpam-462	380	5	math	math	PROPN
ejpam-462	380	6	,	,	PUNCT
ejpam-462	380	7	3	3	NUM
ejpam-462	380	8	(	(	PUNCT
ejpam-462	380	9	2010	2010	NUM
ejpam-462	380	10	)	)	PUNCT
ejpam-462	380	11	,	,	PUNCT
ejpam-462	380	12	382	382	NUM
ejpam-462	380	13	-	-	SYM
ejpam-462	380	14	405	405	NUM
ejpam-462	380	15	402	402	NUM
ejpam-462	380	16	table	table	NOUN
ejpam-462	380	17	9	9	NUM
ejpam-462	380	18	:	:	PUNCT
ejpam-462	380	19	mean	mean	VERB
ejpam-462	380	20	squared	square	VERB
ejpam-462	380	21	errors	error	NOUN
ejpam-462	380	22	for	for	ADP
ejpam-462	380	23	s&p	s&p	PROPN
ejpam-462	380	24	500	500	NUM
ejpam-462	380	25	.	.	PUNCT
ejpam-462	381	1	step	step	NOUN
ejpam-462	381	2	msesub	msesub	PROPN
ejpam-462	381	3	,	,	PUNCT
ejpam-462	381	4	i	i	PRON
ejpam-462	381	5	msesat	msesat	VERB
ejpam-462	381	6	,	,	PUNCT
ejpam-462	381	7	i	i	PRON
ejpam-462	381	8	10	10	NUM
ejpam-462	381	9	154.2658	154.2658	NUM
ejpam-462	381	10	*	*	SYM
ejpam-462	381	11	322.3142	322.3142	NUM
ejpam-462	381	12	20	20	NUM
ejpam-462	381	13	146.0149	146.0149	NUM
ejpam-462	381	14	*	*	SYM
ejpam-462	381	15	303.9236	303.9236	NUM
ejpam-462	381	16	30	30	NUM
ejpam-462	381	17	148.3140	148.3140	NUM
ejpam-462	381	18	*	*	SYM
ejpam-462	381	19	309.1208	309.1208	NUM
ejpam-462	381	20	40	40	NUM
ejpam-462	381	21	149.6718	149.6718	NUM
ejpam-462	381	22	*	*	SYM
ejpam-462	381	23	305.8698	305.8698	NUM
ejpam-462	381	24	50	50	NUM
ejpam-462	381	25	148.4665	148.4665	NUM
ejpam-462	381	26	*	*	NUM
ejpam-462	381	27	309.1991	309.1991	NUM
ejpam-462	381	28	60	60	NUM
ejpam-462	381	29	151.9430	151.9430	NUM
ejpam-462	381	30	*	*	SYM
ejpam-462	381	31	311.2008	311.2008	NUM
ejpam-462	381	32	70	70	NUM
ejpam-462	381	33	155.3841	155.3841	NUM
ejpam-462	381	34	*	*	SYM
ejpam-462	381	35	310.0720	310.0720	NUM
ejpam-462	381	36	80	80	NUM
ejpam-462	381	37	149.8774	149.8774	NUM
ejpam-462	381	38	*	*	SYM
ejpam-462	381	39	311.3456	311.3456	NUM
ejpam-462	381	40	90	90	NUM
ejpam-462	381	41	151.9360	151.9360	NUM
ejpam-462	381	42	*	*	SYM
ejpam-462	381	43	309.3476	309.3476	NUM
ejpam-462	381	44	100	100	NUM
ejpam-462	381	45	153.6293	153.6293	NUM
ejpam-462	381	46	*	*	SYM
ejpam-462	381	47	317.7458	317.7458	NUM
ejpam-462	381	48	a.	a.	NOUN
ejpam-462	381	49	howe	howe	NOUN
ejpam-462	381	50	and	and	CCONJ
ejpam-462	381	51	h.	h.	PROPN
ejpam-462	381	52	bozdogan	bozdogan	PROPN
ejpam-462	381	53	/	/	SYM
ejpam-462	381	54	eur	eur	PROPN
ejpam-462	381	55	.	.	PUNCT
ejpam-462	382	1	j.	j.	PROPN
ejpam-462	382	2	pure	pure	PROPN
ejpam-462	382	3	appl	appl	PROPN
ejpam-462	382	4	.	.	PROPN
ejpam-462	382	5	math	math	PROPN
ejpam-462	382	6	,	,	PUNCT
ejpam-462	382	7	3	3	NUM
ejpam-462	382	8	(	(	PUNCT
ejpam-462	382	9	2010	2010	NUM
ejpam-462	382	10	)	)	PUNCT
ejpam-462	382	11	,	,	PUNCT
ejpam-462	382	12	382	382	NUM
ejpam-462	382	13	-	-	SYM
ejpam-462	382	14	405	405	NUM
ejpam-462	382	15	403	403	NUM
ejpam-462	382	16	6	6	NUM
ejpam-462	382	17	.	.	PUNCT
ejpam-462	383	1	concluding	conclude	VERB
ejpam-462	383	2	remarks	remark	NOUN
ejpam-462	383	3	in	in	ADP
ejpam-462	383	4	this	this	DET
ejpam-462	383	5	paper	paper	NOUN
ejpam-462	383	6	,	,	PUNCT
ejpam-462	383	7	we	we	PRON
ejpam-462	383	8	have	have	AUX
ejpam-462	383	9	set	set	VERB
ejpam-462	383	10	forth	forth	ADP
ejpam-462	383	11	the	the	DET
ejpam-462	383	12	idea	idea	NOUN
ejpam-462	383	13	that	that	SCONJ
ejpam-462	383	14	the	the	DET
ejpam-462	383	15	genetic	genetic	ADJ
ejpam-462	383	16	algorithm	algorithm	NOUN
ejpam-462	383	17	,	,	PUNCT
ejpam-462	383	18	along	along	ADP
ejpam-462	383	19	with	with	ADP
ejpam-462	383	20	the	the	DET
ejpam-462	383	21	appropriate	appropriate	ADJ
ejpam-462	383	22	form	form	NOUN
ejpam-462	383	23	of	of	ADP
ejpam-462	383	24	icom	icom	PROPN
ejpam-462	383	25	p	p	X
ejpam-462	383	26	,	,	PUNCT
ejpam-462	383	27	can	can	AUX
ejpam-462	383	28	be	be	AUX
ejpam-462	383	29	used	use	VERB
ejpam-462	383	30	to	to	PART
ejpam-462	383	31	select	select	VERB
ejpam-462	383	32	a	a	DET
ejpam-462	383	33	vector	vector	NOUN
ejpam-462	383	34	autoregressive	autoregressive	ADJ
ejpam-462	383	35	model	model	NOUN
ejpam-462	383	36	that	that	PRON
ejpam-462	383	37	exhibits	exhibit	VERB
ejpam-462	383	38	accurate	accurate	ADJ
ejpam-462	383	39	and	and	CCONJ
ejpam-462	383	40	efficient	efficient	ADJ
ejpam-462	383	41	forecast	forecast	NOUN
ejpam-462	383	42	performance	performance	NOUN
ejpam-462	383	43	.	.	PUNCT
ejpam-462	384	1	our	our	PRON
ejpam-462	384	2	research	research	NOUN
ejpam-462	384	3	suggests	suggest	VERB
ejpam-462	384	4	that	that	SCONJ
ejpam-462	384	5	,	,	PUNCT
ejpam-462	384	6	when	when	SCONJ
ejpam-462	384	7	modeling	model	VERB
ejpam-462	384	8	complex	complex	ADJ
ejpam-462	384	9	vector	vector	NOUN
ejpam-462	384	10	autoregressions	autoregression	NOUN
ejpam-462	384	11	,	,	PUNCT
ejpam-462	384	12	a	a	DET
ejpam-462	384	13	strict	strict	ADJ
ejpam-462	384	14	criterion	criterion	NOUN
ejpam-462	384	15	that	that	PRON
ejpam-462	384	16	is	be	AUX
ejpam-462	384	17	robust	robust	ADJ
ejpam-462	384	18	to	to	PART
ejpam-462	384	19	model	model	NOUN
ejpam-462	384	20	misspecification	misspecification	NOUN
ejpam-462	384	21	is	be	AUX
ejpam-462	384	22	required	require	VERB
ejpam-462	384	23	even	even	ADV
ejpam-462	384	24	when	when	SCONJ
ejpam-462	384	25	there	there	PRON
ejpam-462	384	26	is	be	VERB
ejpam-462	384	27	no	no	DET
ejpam-462	384	28	sign	sign	NOUN
ejpam-462	384	29	of	of	ADP
ejpam-462	384	30	heteroskedasticity	heteroskedasticity	NOUN
ejpam-462	384	31	,	,	PUNCT
ejpam-462	384	32	non	non	ADJ
ejpam-462	384	33	-	-	NOUN
ejpam-462	384	34	gaussianity	gaussianity	NOUN
ejpam-462	384	35	,	,	PUNCT
ejpam-462	384	36	or	or	CCONJ
ejpam-462	384	37	autocorrelation	autocorrelation	NOUN
ejpam-462	384	38	in	in	ADP
ejpam-462	384	39	the	the	DET
ejpam-462	384	40	model	model	NOUN
ejpam-462	384	41	residuals	residual	NOUN
ejpam-462	384	42	.	.	PUNCT
ejpam-462	385	1	we	we	PRON
ejpam-462	385	2	have	have	AUX
ejpam-462	385	3	demonstrated	demonstrate	VERB
ejpam-462	385	4	our	our	PRON
ejpam-462	385	5	claims	claim	NOUN
ejpam-462	385	6	by	by	ADP
ejpam-462	385	7	creating	create	VERB
ejpam-462	385	8	a	a	DET
ejpam-462	385	9	valuable	valuable	ADJ
ejpam-462	385	10	trading	trading	NOUN
ejpam-462	385	11	model	model	NOUN
ejpam-462	385	12	for	for	ADP
ejpam-462	385	13	the	the	DET
ejpam-462	385	14	standard	standard	ADJ
ejpam-462	385	15	and	and	CCONJ
ejpam-462	385	16	poor	poor	ADJ
ejpam-462	385	17	s&p	s&p	PROPN
ejpam-462	385	18	500	500	NUM
ejpam-462	385	19	index	index	NOUN
ejpam-462	385	20	from	from	ADP
ejpam-462	385	21	a	a	DET
ejpam-462	385	22	universe	universe	NOUN
ejpam-462	385	23	of	of	ADP
ejpam-462	385	24	the	the	DET
ejpam-462	385	25	first	first	ADJ
ejpam-462	385	26	five	five	NUM
ejpam-462	385	27	lags	lag	NOUN
ejpam-462	385	28	of	of	ADP
ejpam-462	385	29	six	six	NUM
ejpam-462	385	30	major	major	ADJ
ejpam-462	385	31	market	market	NOUN
ejpam-462	385	32	indices	index	NOUN
ejpam-462	385	33	.	.	PUNCT
ejpam-462	386	1	in	in	ADP
ejpam-462	386	2	our	our	PRON
ejpam-462	386	3	analysis	analysis	NOUN
ejpam-462	386	4	,	,	PUNCT
ejpam-462	386	5	we	we	PRON
ejpam-462	386	6	have	have	AUX
ejpam-462	386	7	assumed	assume	VERB
ejpam-462	386	8	there	there	PRON
ejpam-462	386	9	are	be	VERB
ejpam-462	386	10	no	no	DET
ejpam-462	386	11	trading	trading	NOUN
ejpam-462	386	12	fees	fee	NOUN
ejpam-462	386	13	associated	associate	VERB
ejpam-462	386	14	with	with	ADP
ejpam-462	386	15	implementing	implement	VERB
ejpam-462	386	16	the	the	DET
ejpam-462	386	17	model	model	NOUN
ejpam-462	386	18	.	.	PUNCT
ejpam-462	387	1	indeed	indeed	ADV
ejpam-462	387	2	,	,	PUNCT
ejpam-462	387	3	the	the	DET
ejpam-462	387	4	best	good	ADJ
ejpam-462	387	5	model	model	NOUN
ejpam-462	387	6	switched	switch	VERB
ejpam-462	387	7	positions	position	NOUN
ejpam-462	387	8	(	(	PUNCT
ejpam-462	387	9	long	long	ADV
ejpam-462	387	10	/	/	SYM
ejpam-462	387	11	short	short	ADJ
ejpam-462	387	12	)	)	PUNCT
ejpam-462	387	13	34	34	NUM
ejpam-462	387	14	times	time	NOUN
ejpam-462	387	15	during	during	ADP
ejpam-462	387	16	the	the	DET
ejpam-462	387	17	60day	60day	NOUN
ejpam-462	387	18	testing	testing	NOUN
ejpam-462	387	19	period	period	NOUN
ejpam-462	387	20	,	,	PUNCT
ejpam-462	387	21	so	so	SCONJ
ejpam-462	387	22	trading	trading	NOUN
ejpam-462	387	23	fees	fee	NOUN
ejpam-462	387	24	could	could	AUX
ejpam-462	387	25	add	add	VERB
ejpam-462	387	26	up	up	ADP
ejpam-462	387	27	quickly	quickly	ADV
ejpam-462	387	28	.	.	PUNCT
ejpam-462	388	1	there	there	PRON
ejpam-462	388	2	are	be	VERB
ejpam-462	388	3	at	at	ADV
ejpam-462	388	4	least	least	ADJ
ejpam-462	388	5	two	two	NUM
ejpam-462	388	6	mutual	mutual	ADJ
ejpam-462	388	7	fund	fund	NOUN
ejpam-462	388	8	companies	company	NOUN
ejpam-462	388	9	(	(	PUNCT
ejpam-462	388	10	profunds	profund	NOUN
ejpam-462	388	11	,	,	PUNCT
ejpam-462	388	12	rydex	rydex	NOUN
ejpam-462	388	13	)	)	PUNCT
ejpam-462	388	14	that	that	PRON
ejpam-462	388	15	offer	offer	VERB
ejpam-462	388	16	market	market	NOUN
ejpam-462	388	17	index	index	NOUN
ejpam-462	388	18	tracking	tracking	NOUN
ejpam-462	388	19	funds	fund	NOUN
ejpam-462	388	20	.	.	PUNCT
ejpam-462	389	1	they	they	PRON
ejpam-462	389	2	both	both	PRON
ejpam-462	389	3	allow	allow	VERB
ejpam-462	389	4	daily	daily	ADJ
ejpam-462	389	5	trading	trading	NOUN
ejpam-462	389	6	,	,	PUNCT
ejpam-462	389	7	at	at	ADP
ejpam-462	389	8	least	least	ADJ
ejpam-462	389	9	they	they	PRON
ejpam-462	389	10	used	use	VERB
ejpam-462	389	11	to	to	PART
ejpam-462	389	12	,	,	PUNCT
ejpam-462	389	13	so	so	SCONJ
ejpam-462	389	14	this	this	DET
ejpam-462	389	15	assumption	assumption	NOUN
ejpam-462	389	16	is	be	AUX
ejpam-462	389	17	not	not	PART
ejpam-462	389	18	too	too	ADV
ejpam-462	389	19	wildly	wildly	ADV
ejpam-462	389	20	made	make	VERB
ejpam-462	389	21	.	.	PUNCT
ejpam-462	390	1	of	of	ADP
ejpam-462	390	2	course	course	NOUN
ejpam-462	390	3	,	,	PUNCT
ejpam-462	390	4	in	in	ADP
ejpam-462	390	5	an	an	DET
ejpam-462	390	6	effort	effort	NOUN
ejpam-462	390	7	to	to	PART
ejpam-462	390	8	appropriately	appropriately	ADV
ejpam-462	390	9	diversify	diversify	VERB
ejpam-462	390	10	,	,	PUNCT
ejpam-462	390	11	one	one	PRON
ejpam-462	390	12	would	would	AUX
ejpam-462	390	13	be	be	AUX
ejpam-462	390	14	interested	interested	ADJ
ejpam-462	390	15	in	in	ADP
ejpam-462	390	16	trading	trade	VERB
ejpam-462	390	17	other	other	ADJ
ejpam-462	390	18	indices	index	NOUN
ejpam-462	390	19	as	as	ADV
ejpam-462	390	20	well	well	ADV
ejpam-462	390	21	.	.	PUNCT
ejpam-462	391	1	this	this	DET
ejpam-462	391	2	method	method	NOUN
ejpam-462	391	3	would	would	AUX
ejpam-462	391	4	be	be	AUX
ejpam-462	391	5	one	one	NUM
ejpam-462	391	6	voice	voice	NOUN
ejpam-462	391	7	in	in	ADP
ejpam-462	391	8	a	a	DET
ejpam-462	391	9	portfolio	portfolio	NOUN
ejpam-462	391	10	of	of	ADP
ejpam-462	391	11	models	model	NOUN
ejpam-462	391	12	.	.	PUNCT
ejpam-462	392	1	in	in	ADP
ejpam-462	392	2	table	table	NOUN
ejpam-462	392	3	1	1	NUM
ejpam-462	392	4	,	,	PUNCT
ejpam-462	392	5	we	we	PRON
ejpam-462	392	6	noted	note	VERB
ejpam-462	392	7	the	the	DET
ejpam-462	392	8	high	high	ADJ
ejpam-462	392	9	multicollinearity	multicollinearity	NOUN
ejpam-462	392	10	between	between	ADP
ejpam-462	392	11	the	the	DET
ejpam-462	392	12	indices	index	NOUN
ejpam-462	392	13	modeled	model	VERB
ejpam-462	392	14	.	.	PUNCT
ejpam-462	393	1	a	a	DET
ejpam-462	393	2	quick	quick	ADJ
ejpam-462	393	3	review	review	NOUN
ejpam-462	393	4	of	of	ADP
ejpam-462	393	5	the	the	DET
ejpam-462	393	6	table	table	NOUN
ejpam-462	393	7	,	,	PUNCT
ejpam-462	393	8	however	however	ADV
ejpam-462	393	9	,	,	PUNCT
ejpam-462	393	10	will	will	AUX
ejpam-462	393	11	show	show	VERB
ejpam-462	393	12	that	that	SCONJ
ejpam-462	393	13	the	the	DET
ejpam-462	393	14	amex	amex	PROPN
ejpam-462	393	15	gold	gold	PROPN
ejpam-462	393	16	producer	producer	NOUN
ejpam-462	393	17	index	index	NOUN
ejpam-462	393	18	xau	xau	ADV
ejpam-462	393	19	was	be	AUX
ejpam-462	393	20	only	only	ADV
ejpam-462	393	21	slightly	slightly	ADV
ejpam-462	393	22	negatively	negatively	ADV
ejpam-462	393	23	correlated	correlate	VERB
ejpam-462	393	24	with	with	ADP
ejpam-462	393	25	any	any	PRON
ejpam-462	393	26	of	of	ADP
ejpam-462	393	27	the	the	DET
ejpam-462	393	28	others	other	NOUN
ejpam-462	393	29	.	.	PUNCT
ejpam-462	394	1	additionally	additionally	ADV
ejpam-462	394	2	,	,	PUNCT
ejpam-462	394	3	two	two	NUM
ejpam-462	394	4	lags	lag	NOUN
ejpam-462	394	5	of	of	ADP
ejpam-462	394	6	xau	xau	PROPN
ejpam-462	394	7	were	be	AUX
ejpam-462	394	8	selected	select	VERB
ejpam-462	394	9	for	for	ADP
ejpam-462	394	10	spx	spx	PROPN
ejpam-462	394	11	.	.	PUNCT
ejpam-462	395	1	this	this	PRON
ejpam-462	395	2	suggests	suggest	VERB
ejpam-462	395	3	that	that	SCONJ
ejpam-462	395	4	a	a	DET
ejpam-462	395	5	valuable	valuable	ADJ
ejpam-462	395	6	modification	modification	NOUN
ejpam-462	395	7	would	would	AUX
ejpam-462	395	8	be	be	AUX
ejpam-462	395	9	to	to	PART
ejpam-462	395	10	include	include	VERB
ejpam-462	395	11	uncorrelated	uncorrelate	VERB
ejpam-462	395	12	,	,	PUNCT
ejpam-462	395	13	and	and	CCONJ
ejpam-462	395	14	even	even	ADV
ejpam-462	395	15	negatively	negatively	ADV
ejpam-462	395	16	correlated	correlate	VERB
ejpam-462	395	17	predictors	predictor	NOUN
ejpam-462	395	18	,	,	PUNCT
ejpam-462	395	19	in	in	ADP
ejpam-462	395	20	order	order	NOUN
ejpam-462	395	21	to	to	PART
ejpam-462	395	22	achieve	achieve	VERB
ejpam-462	395	23	a	a	DET
ejpam-462	395	24	model	model	NOUN
ejpam-462	395	25	that	that	PRON
ejpam-462	395	26	uses	use	VERB
ejpam-462	395	27	as	as	ADV
ejpam-462	395	28	much	much	ADJ
ejpam-462	395	29	information	information	NOUN
ejpam-462	395	30	as	as	ADP
ejpam-462	395	31	possible	possible	ADJ
ejpam-462	395	32	and	and	CCONJ
ejpam-462	395	33	is	be	AUX
ejpam-462	395	34	market	market	NOUN
ejpam-462	395	35	neutral	neutral	ADJ
ejpam-462	395	36	.	.	PUNCT
ejpam-462	396	1	to	to	PART
ejpam-462	396	2	operationalize	operationalize	VERB
ejpam-462	396	3	these	these	DET
ejpam-462	396	4	methods	method	NOUN
ejpam-462	396	5	,	,	PUNCT
ejpam-462	396	6	several	several	ADJ
ejpam-462	396	7	implementation	implementation	NOUN
ejpam-462	396	8	modifications	modification	NOUN
ejpam-462	396	9	would	would	AUX
ejpam-462	396	10	have	have	VERB
ejpam-462	396	11	to	to	PART
ejpam-462	396	12	be	be	AUX
ejpam-462	396	13	made	make	VERB
ejpam-462	396	14	.	.	PUNCT
ejpam-462	397	1	past	past	ADJ
ejpam-462	397	2	experience	experience	NOUN
ejpam-462	397	3	has	have	AUX
ejpam-462	397	4	shown	show	VERB
ejpam-462	397	5	us	we	PRON
ejpam-462	397	6	that	that	SCONJ
ejpam-462	397	7	over	over	ADP
ejpam-462	397	8	time	time	NOUN
ejpam-462	397	9	,	,	PUNCT
ejpam-462	397	10	predictive	predictive	ADJ
ejpam-462	397	11	relationships	relationship	NOUN
ejpam-462	397	12	between	between	ADP
ejpam-462	397	13	indices	index	NOUN
ejpam-462	397	14	change	change	VERB
ejpam-462	397	15	.	.	PUNCT
ejpam-462	398	1	there	there	PRON
ejpam-462	398	2	was	be	VERB
ejpam-462	398	3	a	a	DET
ejpam-462	398	4	time	time	NOUN
ejpam-462	398	5	(	(	PUNCT
ejpam-462	398	6	1998	1998	NUM
ejpam-462	398	7	-	-	SYM
ejpam-462	398	8	2002	2002	NUM
ejpam-462	398	9	)	)	PUNCT
ejpam-462	398	10	when	when	SCONJ
ejpam-462	398	11	a	a	DET
ejpam-462	398	12	very	very	ADV
ejpam-462	398	13	naive	naive	ADJ
ejpam-462	398	14	model	model	NOUN
ejpam-462	398	15	based	base	VERB
ejpam-462	398	16	on	on	ADP
ejpam-462	398	17	1	1	NUM
ejpam-462	398	18	,	,	PUNCT
ejpam-462	398	19	2	2	NUM
ejpam-462	398	20	,	,	PUNCT
ejpam-462	398	21	or	or	CCONJ
ejpam-462	398	22	3	3	NUM
ejpam-462	398	23	lags	lag	NOUN
ejpam-462	398	24	of	of	ADP
ejpam-462	398	25	the	the	DET
ejpam-462	398	26	daily	daily	ADJ
ejpam-462	398	27	changes	change	NOUN
ejpam-462	398	28	in	in	ADP
ejpam-462	398	29	the	the	DET
ejpam-462	398	30	spx	spx	PROPN
ejpam-462	398	31	,	,	PUNCT
ejpam-462	398	32	rut	rut	NOUN
ejpam-462	398	33	,	,	PUNCT
ejpam-462	398	34	and	and	CCONJ
ejpam-462	398	35	mid	mid	PROPN
ejpam-462	398	36	could	could	AUX
ejpam-462	398	37	very	very	ADV
ejpam-462	398	38	effectively	effectively	ADV
ejpam-462	398	39	predict	predict	VERB
ejpam-462	398	40	the	the	DET
ejpam-462	398	41	indices	index	NOUN
ejpam-462	398	42	daily	daily	ADJ
ejpam-462	398	43	moves	move	NOUN
ejpam-462	398	44	.	.	PUNCT
ejpam-462	399	1	these	these	DET
ejpam-462	399	2	relationships	relationship	NOUN
ejpam-462	399	3	largely	largely	ADV
ejpam-462	399	4	broke	break	VERB
ejpam-462	399	5	down	down	ADP
ejpam-462	399	6	after	after	ADP
ejpam-462	399	7	that	that	DET
ejpam-462	399	8	period	period	NOUN
ejpam-462	399	9	.	.	PUNCT
ejpam-462	400	1	additionally	additionally	ADV
ejpam-462	400	2	,	,	PUNCT
ejpam-462	400	3	it	it	PRON
ejpam-462	400	4	has	have	AUX
ejpam-462	400	5	been	be	AUX
ejpam-462	400	6	seen	see	VERB
ejpam-462	400	7	that	that	SCONJ
ejpam-462	400	8	predictor	predictor	NOUN
ejpam-462	400	9	indices	index	NOUN
ejpam-462	400	10	can	can	AUX
ejpam-462	400	11	move	move	VERB
ejpam-462	400	12	in	in	ADV
ejpam-462	400	13	and	and	CCONJ
ejpam-462	400	14	out	out	ADP
ejpam-462	400	15	of	of	ADP
ejpam-462	400	16	a	a	DET
ejpam-462	400	17	model	model	NOUN
ejpam-462	400	18	quickly	quickly	ADV
ejpam-462	400	19	,	,	PUNCT
ejpam-462	400	20	even	even	ADV
ejpam-462	400	21	on	on	ADP
ejpam-462	400	22	a	a	DET
ejpam-462	400	23	weekly	weekly	ADJ
ejpam-462	400	24	basis	basis	NOUN
ejpam-462	400	25	.	.	PUNCT
ejpam-462	401	1	as	as	ADP
ejpam-462	401	2	such	such	ADJ
ejpam-462	401	3	,	,	PUNCT
ejpam-462	401	4	this	this	DET
ejpam-462	401	5	modeling	modeling	NOUN
ejpam-462	401	6	procedure	procedure	NOUN
ejpam-462	401	7	would	would	AUX
ejpam-462	401	8	need	need	VERB
ejpam-462	401	9	to	to	PART
ejpam-462	401	10	be	be	AUX
ejpam-462	401	11	retrained	retrain	VERB
ejpam-462	401	12	periodically	periodically	ADV
ejpam-462	401	13	.	.	PUNCT
ejpam-462	402	1	secondly	secondly	ADV
ejpam-462	402	2	,	,	PUNCT
ejpam-462	402	3	a	a	DET
ejpam-462	402	4	question	question	NOUN
ejpam-462	402	5	that	that	PRON
ejpam-462	402	6	must	must	AUX
ejpam-462	402	7	be	be	AUX
ejpam-462	402	8	answered	answer	VERB
ejpam-462	402	9	is	be	AUX
ejpam-462	402	10	how	how	SCONJ
ejpam-462	402	11	long	long	ADJ
ejpam-462	402	12	are	be	AUX
ejpam-462	402	13	the	the	DET
ejpam-462	402	14	optimal	optimal	ADJ
ejpam-462	402	15	training	training	NOUN
ejpam-462	402	16	/	/	SYM
ejpam-462	402	17	testing	testing	NOUN
ejpam-462	402	18	periods	period	NOUN
ejpam-462	402	19	.	.	PUNCT
ejpam-462	403	1	in	in	ADP
ejpam-462	403	2	this	this	DET
ejpam-462	403	3	empirical	empirical	ADJ
ejpam-462	403	4	work	work	NOUN
ejpam-462	403	5	,	,	PUNCT
ejpam-462	403	6	we	we	PRON
ejpam-462	403	7	demonstrated	demonstrate	VERB
ejpam-462	403	8	our	our	PRON
ejpam-462	403	9	ideas	idea	NOUN
ejpam-462	403	10	using	use	VERB
ejpam-462	403	11	3	3	NUM
ejpam-462	403	12	months	month	NOUN
ejpam-462	403	13	for	for	ADP
ejpam-462	403	14	each	each	PRON
ejpam-462	403	15	.	.	PUNCT
ejpam-462	404	1	it	it	PRON
ejpam-462	404	2	seems	seem	VERB
ejpam-462	404	3	unlikely	unlikely	ADJ
ejpam-462	404	4	that	that	SCONJ
ejpam-462	404	5	the	the	DET
ejpam-462	404	6	same	same	ADJ
ejpam-462	404	7	indices	index	NOUN
ejpam-462	404	8	would	would	AUX
ejpam-462	404	9	consistently	consistently	ADV
ejpam-462	404	10	retain	retain	VERB
ejpam-462	404	11	their	their	PRON
ejpam-462	404	12	predictive	predictive	ADJ
ejpam-462	404	13	power	power	NOUN
ejpam-462	404	14	over	over	ADP
ejpam-462	404	15	entire	entire	ADJ
ejpam-462	404	16	quarters	quarter	NOUN
ejpam-462	404	17	.	.	PUNCT
ejpam-462	405	1	it	it	PRON
ejpam-462	405	2	is	be	AUX
ejpam-462	405	3	anticipated	anticipate	VERB
ejpam-462	405	4	that	that	SCONJ
ejpam-462	405	5	better	well	ADJ
ejpam-462	405	6	results	result	NOUN
ejpam-462	405	7	would	would	AUX
ejpam-462	405	8	be	be	AUX
ejpam-462	405	9	achieved	achieve	VERB
ejpam-462	405	10	by	by	ADP
ejpam-462	405	11	retraining	retrain	VERB
ejpam-462	405	12	the	the	DET
ejpam-462	405	13	model	model	NOUN
ejpam-462	405	14	more	more	ADV
ejpam-462	405	15	frequently	frequently	ADV
ejpam-462	405	16	.	.	PUNCT
ejpam-462	406	1	the	the	DET
ejpam-462	406	2	appropriate	appropriate	ADJ
ejpam-462	406	3	training	training	NOUN
ejpam-462	406	4	period	period	NOUN
ejpam-462	406	5	is	be	AUX
ejpam-462	406	6	also	also	ADV
ejpam-462	406	7	an	an	DET
ejpam-462	406	8	important	important	ADJ
ejpam-462	406	9	consideration	consideration	NOUN
ejpam-462	406	10	.	.	PUNCT
ejpam-462	407	1	if	if	SCONJ
ejpam-462	407	2	it	it	PRON
ejpam-462	407	3	is	be	AUX
ejpam-462	407	4	too	too	ADV
ejpam-462	407	5	short	short	ADJ
ejpam-462	407	6	,	,	PUNCT
ejpam-462	407	7	the	the	DET
ejpam-462	407	8	model	model	NOUN
ejpam-462	407	9	may	may	AUX
ejpam-462	407	10	be	be	AUX
ejpam-462	407	11	unduly	unduly	ADV
ejpam-462	407	12	influenced	influence	VERB
ejpam-462	407	13	by	by	ADP
ejpam-462	407	14	unstable	unstable	ADJ
ejpam-462	407	15	short	short	ADJ
ejpam-462	407	16	-	-	PUNCT
ejpam-462	407	17	term	term	NOUN
ejpam-462	407	18	parameter	parameter	NOUN
ejpam-462	407	19	shifts	shift	NOUN
ejpam-462	407	20	;	;	PUNCT
ejpam-462	407	21	however	however	ADV
ejpam-462	407	22	,	,	PUNCT
ejpam-462	407	23	if	if	SCONJ
ejpam-462	407	24	the	the	DET
ejpam-462	407	25	period	period	NOUN
ejpam-462	407	26	is	be	AUX
ejpam-462	407	27	too	too	ADV
ejpam-462	407	28	long	long	ADJ
ejpam-462	407	29	,	,	PUNCT
ejpam-462	407	30	the	the	DET
ejpam-462	407	31	model	model	NOUN
ejpam-462	407	32	will	will	AUX
ejpam-462	407	33	miss	miss	VERB
ejpam-462	407	34	trend	trend	NOUN
ejpam-462	407	35	reversals	reversal	NOUN
ejpam-462	407	36	and	and	CCONJ
ejpam-462	407	37	react	react	VERB
ejpam-462	407	38	too	too	ADV
ejpam-462	407	39	slowly	slowly	ADV
ejpam-462	407	40	.	.	PUNCT
ejpam-462	408	1	we	we	PRON
ejpam-462	408	2	have	have	AUX
ejpam-462	408	3	seen	see	VERB
ejpam-462	408	4	economically	economically	ADV
ejpam-462	408	5	valuable	valuable	ADJ
ejpam-462	408	6	trading	trading	NOUN
ejpam-462	408	7	models	model	NOUN
ejpam-462	408	8	with	with	ADP
ejpam-462	408	9	training	training	NOUN
ejpam-462	408	10	periods	period	NOUN
ejpam-462	408	11	as	as	ADV
ejpam-462	408	12	long	long	ADV
ejpam-462	408	13	as	as	ADP
ejpam-462	408	14	a	a	DET
ejpam-462	408	15	year	year	NOUN
ejpam-462	408	16	,	,	PUNCT
ejpam-462	408	17	and	and	CCONJ
ejpam-462	408	18	as	as	ADV
ejpam-462	408	19	short	short	ADJ
ejpam-462	408	20	as	as	ADP
ejpam-462	408	21	two	two	NUM
ejpam-462	408	22	weeks	week	NOUN
ejpam-462	408	23	.	.	PUNCT
ejpam-462	409	1	these	these	DET
ejpam-462	409	2	two	two	NUM
ejpam-462	409	3	settings	setting	NOUN
ejpam-462	409	4	can	can	AUX
ejpam-462	409	5	be	be	AUX
ejpam-462	409	6	determined	determine	VERB
ejpam-462	409	7	empirically	empirically	ADV
ejpam-462	409	8	using	use	VERB
ejpam-462	409	9	historical	historical	ADJ
ejpam-462	409	10	back	back	NOUN
ejpam-462	409	11	-	-	PUNCT
ejpam-462	409	12	testing	testing	NOUN
ejpam-462	409	13	.	.	PUNCT
ejpam-462	410	1	lastly	lastly	ADV
ejpam-462	410	2	,	,	PUNCT
ejpam-462	410	3	there	there	PRON
ejpam-462	410	4	are	be	VERB
ejpam-462	410	5	computational	computational	ADJ
ejpam-462	410	6	issues	issue	NOUN
ejpam-462	410	7	to	to	PART
ejpam-462	410	8	be	be	AUX
ejpam-462	410	9	considered	consider	VERB
ejpam-462	410	10	with	with	ADP
ejpam-462	410	11	this	this	DET
ejpam-462	410	12	type	type	NOUN
ejpam-462	410	13	of	of	ADP
ejpam-462	410	14	model	model	NOUN
ejpam-462	410	15	.	.	PUNCT
ejpam-462	411	1	the	the	DET
ejpam-462	411	2	complexity	complexity	NOUN
ejpam-462	411	3	of	of	ADP
ejpam-462	411	4	our	our	PRON
ejpam-462	411	5	problem	problem	NOUN
ejpam-462	411	6	requires	require	VERB
ejpam-462	411	7	consideration	consideration	NOUN
ejpam-462	411	8	of	of	ADP
ejpam-462	411	9	the	the	DET
ejpam-462	411	10	feasibility	feasibility	NOUN
ejpam-462	411	11	of	of	ADP
ejpam-462	411	12	subset	subset	NOUN
ejpam-462	411	13	selection	selection	NOUN
ejpam-462	411	14	,	,	PUNCT
ejpam-462	411	15	given	give	VERB
ejpam-462	411	16	existing	exist	VERB
ejpam-462	411	17	computational	computational	ADJ
ejpam-462	411	18	power	power	NOUN
ejpam-462	411	19	.	.	PUNCT
ejpam-462	412	1	while	while	SCONJ
ejpam-462	412	2	one	one	NUM
ejpam-462	412	3	simulation	simulation	NOUN
ejpam-462	412	4	took	take	VERB
ejpam-462	412	5	at	at	ADV
ejpam-462	412	6	most	most	ADV
ejpam-462	412	7	15	15	NUM
ejpam-462	412	8	minutes	minute	NOUN
ejpam-462	412	9	,	,	PUNCT
ejpam-462	412	10	obtaining	obtain	VERB
ejpam-462	412	11	results	result	NOUN
ejpam-462	412	12	across	across	ADP
ejpam-462	412	13	many	many	ADJ
ejpam-462	412	14	simulations	simulation	NOUN
ejpam-462	412	15	is	be	AUX
ejpam-462	412	16	recommended	recommend	VERB
ejpam-462	412	17	,	,	PUNCT
ejpam-462	412	18	due	due	ADP
ejpam-462	412	19	to	to	ADP
ejpam-462	412	20	the	the	DET
ejpam-462	412	21	fact	fact	NOUN
ejpam-462	412	22	that	that	SCONJ
ejpam-462	412	23	there	there	PRON
ejpam-462	412	24	are	be	VERB
ejpam-462	412	25	9.808×1055	9.808×1055	NUM
ejpam-462	412	26	possible	possible	ADJ
ejpam-462	412	27	references	reference	NOUN
ejpam-462	412	28	404	404	NUM
ejpam-462	412	29	subset	subset	VERB
ejpam-462	412	30	var	var	NOUN
ejpam-462	412	31	models	model	NOUN
ejpam-462	412	32	.	.	PUNCT
ejpam-462	413	1	the	the	DET
ejpam-462	413	2	100	100	NUM
ejpam-462	413	3	replications	replication	NOUN
ejpam-462	413	4	executed	execute	VERB
ejpam-462	413	5	in	in	ADP
ejpam-462	413	6	approximately	approximately	ADV
ejpam-462	413	7	24	24	NUM
ejpam-462	413	8	-	-	SYM
ejpam-462	413	9	25	25	NUM
ejpam-462	413	10	hours	hour	NOUN
ejpam-462	413	11	at	at	ADP
ejpam-462	413	12	most	most	ADV
ejpam-462	413	13	an	an	DET
ejpam-462	413	14	estimated	estimate	VERB
ejpam-462	413	15	1,500,000	1,500,000	NUM
ejpam-462	413	16	unique	unique	ADJ
ejpam-462	413	17	models	model	NOUN
ejpam-462	413	18	were	be	AUX
ejpam-462	413	19	evaluated	evaluate	VERB
ejpam-462	413	20	.	.	PUNCT
ejpam-462	414	1	while	while	SCONJ
ejpam-462	414	2	this	this	PRON
ejpam-462	414	3	seems	seem	VERB
ejpam-462	414	4	large	large	ADJ
ejpam-462	414	5	,	,	PUNCT
ejpam-462	414	6	it	it	PRON
ejpam-462	414	7	is	be	AUX
ejpam-462	414	8	insignificant	insignificant	ADJ
ejpam-462	414	9	compared	compare	VERB
ejpam-462	414	10	to	to	ADP
ejpam-462	414	11	the	the	DET
ejpam-462	414	12	number	number	NOUN
ejpam-462	414	13	possible	possible	ADJ
ejpam-462	414	14	.	.	PUNCT
ejpam-462	415	1	accelerating	accelerate	VERB
ejpam-462	415	2	or	or	CCONJ
ejpam-462	415	3	distributing	distribute	VERB
ejpam-462	415	4	the	the	DET
ejpam-462	415	5	computations	computation	NOUN
ejpam-462	415	6	so	so	SCONJ
ejpam-462	415	7	as	as	SCONJ
ejpam-462	415	8	to	to	PART
ejpam-462	415	9	better	well	ADV
ejpam-462	415	10	search	search	VERB
ejpam-462	415	11	the	the	DET
ejpam-462	415	12	model	model	NOUN
ejpam-462	415	13	space	space	NOUN
ejpam-462	415	14	would	would	AUX
ejpam-462	415	15	be	be	AUX
ejpam-462	415	16	a	a	DET
ejpam-462	415	17	valuable	valuable	ADJ
ejpam-462	415	18	contribution	contribution	NOUN
ejpam-462	415	19	.	.	PUNCT
ejpam-462	416	1	references	reference	NOUN
ejpam-462	416	2	[	[	X
ejpam-462	416	3	1	1	NUM
ejpam-462	416	4	]	]	PUNCT
ejpam-462	416	5	h	h	NOUN
ejpam-462	416	6	akaike	akaike	ADJ
ejpam-462	416	7	.	.	PUNCT
ejpam-462	417	1	information	information	NOUN
ejpam-462	417	2	theory	theory	NOUN
ejpam-462	417	3	and	and	CCONJ
ejpam-462	417	4	an	an	DET
ejpam-462	417	5	extension	extension	NOUN
ejpam-462	417	6	of	of	ADP
ejpam-462	417	7	the	the	DET
ejpam-462	417	8	maximum	maximum	ADJ
ejpam-462	417	9	likelihood	likelihood	NOUN
ejpam-462	417	10	principle	principle	NOUN
ejpam-462	417	11	.	.	PUNCT
ejpam-462	418	1	in	in	ADP
ejpam-462	418	2	b.n	b.n	PROPN
ejpam-462	418	3	.	.	PROPN
ejpam-462	418	4	petrox	petrox	PROPN
ejpam-462	418	5	and	and	CCONJ
ejpam-462	418	6	f.	f.	PROPN
ejpam-462	418	7	csaki	csaki	PROPN
ejpam-462	418	8	,	,	PUNCT
ejpam-462	418	9	editors	editor	NOUN
ejpam-462	418	10	,	,	PUNCT
ejpam-462	418	11	second	second	ADJ
ejpam-462	418	12	international	international	ADJ
ejpam-462	418	13	symposium	symposium	NOUN
ejpam-462	418	14	on	on	ADP
ejpam-462	418	15	information	information	NOUN
ejpam-462	418	16	theory	theory	NOUN
ejpam-462	418	17	.	.	PUNCT
ejpam-462	419	1	,	,	PUNCT
ejpam-462	419	2	pages	page	NOUN
ejpam-462	419	3	267–281	267–281	NUM
ejpam-462	419	4	,	,	PUNCT
ejpam-462	419	5	budapest	budapest	NOUN
ejpam-462	419	6	,	,	PUNCT
ejpam-462	419	7	1973	1973	NUM
ejpam-462	419	8	.	.	PUNCT
ejpam-462	420	1	academiai	academiai	PROPN
ejpam-462	420	2	kiado	kiado	PROPN
ejpam-462	420	3	.	.	PUNCT
ejpam-462	421	1	[	[	X
ejpam-462	421	2	2	2	NUM
ejpam-462	421	3	]	]	X
ejpam-462	421	4	l	l	NOUN
ejpam-462	421	5	bauwens	bauwen	NOUN
ejpam-462	421	6	and	and	CCONJ
ejpam-462	421	7	m	m	PROPN
ejpam-462	421	8	lubrano	lubrano	PROPN
ejpam-462	421	9	.	.	PUNCT
ejpam-462	422	1	identification	identification	NOUN
ejpam-462	422	2	restrictions	restriction	NOUN
ejpam-462	422	3	and	and	CCONJ
ejpam-462	422	4	posterior	posterior	ADJ
ejpam-462	422	5	densities	density	NOUN
ejpam-462	422	6	in	in	ADP
ejpam-462	422	7	cointegrated	cointegrate	VERB
ejpam-462	422	8	gaussian	gaussian	ADJ
ejpam-462	422	9	var	var	NOUN
ejpam-462	422	10	systems	system	NOUN
ejpam-462	422	11	.	.	PUNCT
ejpam-462	423	1	in	in	ADP
ejpam-462	423	2	t.m	t.m	PROPN
ejpam-462	423	3	.	.	PROPN
ejpam-462	423	4	fomby	fomby	PROPN
ejpam-462	423	5	and	and	CCONJ
ejpam-462	423	6	r.	r.	PROPN
ejpam-462	423	7	carter	carter	PROPN
ejpam-462	423	8	hill	hill	PROPN
ejpam-462	423	9	,	,	PUNCT
ejpam-462	423	10	editors	editor	NOUN
ejpam-462	423	11	,	,	PUNCT
ejpam-462	423	12	advances	advance	NOUN
ejpam-462	423	13	in	in	ADP
ejpam-462	423	14	econometrics	econometric	NOUN
ejpam-462	423	15	.	.	PUNCT
ejpam-462	424	1	,	,	PUNCT
ejpam-462	424	2	volume	volume	NOUN
ejpam-462	424	3	11b	11b	NOUN
ejpam-462	424	4	.	.	PUNCT
ejpam-462	425	1	jai	jai	PROPN
ejpam-462	425	2	press	press	PROPN
ejpam-462	425	3	,	,	PUNCT
ejpam-462	425	4	conneticut	conneticut	PROPN
ejpam-462	425	5	,	,	PUNCT
ejpam-462	425	6	usa	usa	PROPN
ejpam-462	425	7	,	,	PUNCT
ejpam-462	425	8	1993	1993	NUM
ejpam-462	425	9	.	.	PUNCT
ejpam-462	426	1	[	[	X
ejpam-462	426	2	3	3	X
ejpam-462	426	3	]	]	X
ejpam-462	426	4	p	p	X
ejpam-462	426	5	bearse	bearse	NOUN
ejpam-462	426	6	and	and	CCONJ
ejpam-462	426	7	h	h	NOUN
ejpam-462	426	8	bozdogan	bozdogan	NOUN
ejpam-462	426	9	.	.	PUNCT
ejpam-462	427	1	subset	subset	ADJ
ejpam-462	427	2	selection	selection	NOUN
ejpam-462	427	3	in	in	ADP
ejpam-462	427	4	vector	vector	NOUN
ejpam-462	427	5	autoregressive	autoregressive	ADJ
ejpam-462	427	6	models	model	NOUN
ejpam-462	427	7	using	use	VERB
ejpam-462	427	8	the	the	DET
ejpam-462	427	9	genetic	genetic	ADJ
ejpam-462	427	10	algorithm	algorithm	NOUN
ejpam-462	427	11	with	with	ADP
ejpam-462	427	12	informational	informational	ADJ
ejpam-462	427	13	complexity	complexity	NOUN
ejpam-462	427	14	as	as	ADP
ejpam-462	427	15	the	the	DET
ejpam-462	427	16	fitness	fitness	NOUN
ejpam-462	427	17	function	function	NOUN
ejpam-462	427	18	.	.	PUNCT
ejpam-462	428	1	systems	system	NOUN
ejpam-462	428	2	analysis	analysis	NOUN
ejpam-462	428	3	modelling	model	VERB
ejpam-462	428	4	simulation	simulation	NOUN
ejpam-462	428	5	,	,	PUNCT
ejpam-462	428	6	31:61–91	31:61–91	NUM
ejpam-462	428	7	,	,	PUNCT
ejpam-462	428	8	1998	1998	NUM
ejpam-462	428	9	.	.	PUNCT
ejpam-462	429	1	[	[	X
ejpam-462	429	2	4	4	X
ejpam-462	429	3	]	]	X
ejpam-462	429	4	p	p	NOUN
ejpam-462	429	5	bearse	bearse	NOUN
ejpam-462	429	6	,	,	PUNCT
ejpam-462	429	7	h	h	NOUN
ejpam-462	429	8	bozdogan	bozdogan	NOUN
ejpam-462	429	9	,	,	PUNCT
ejpam-462	429	10	and	and	CCONJ
ejpam-462	429	11	a	a	DET
ejpam-462	429	12	scholottman	scholottman	NOUN
ejpam-462	429	13	.	.	PUNCT
ejpam-462	430	1	empirical	empirical	ADJ
ejpam-462	430	2	econometric	econometric	ADJ
ejpam-462	430	3	modelling	modelling	NOUN
ejpam-462	430	4	of	of	ADP
ejpam-462	430	5	food	food	NOUN
ejpam-462	430	6	consumption	consumption	NOUN
ejpam-462	430	7	using	use	VERB
ejpam-462	430	8	a	a	DET
ejpam-462	430	9	new	new	ADJ
ejpam-462	430	10	informational	informational	ADJ
ejpam-462	430	11	complexity	complexity	NOUN
ejpam-462	430	12	approach	approach	NOUN
ejpam-462	430	13	.	.	PUNCT
ejpam-462	431	1	journal	journal	NOUN
ejpam-462	431	2	of	of	ADP
ejpam-462	431	3	applied	apply	VERB
ejpam-462	431	4	econometrics	econometric	NOUN
ejpam-462	431	5	,	,	PUNCT
ejpam-462	431	6	12:563–592	12:563–592	NUM
ejpam-462	431	7	,	,	PUNCT
ejpam-462	431	8	1997	1997	NUM
ejpam-462	431	9	.	.	PUNCT
ejpam-462	432	1	[	[	X
ejpam-462	432	2	5	5	NUM
ejpam-462	432	3	]	]	PUNCT
ejpam-462	432	4	h	h	NOUN
ejpam-462	432	5	bozdogan	bozdogan	NOUN
ejpam-462	432	6	.	.	PUNCT
ejpam-462	433	1	icomp	icomp	PROPN
ejpam-462	433	2	:	:	PUNCT
ejpam-462	433	3	a	a	DET
ejpam-462	433	4	new	new	ADJ
ejpam-462	433	5	model	model	ADJ
ejpam-462	433	6	-	-	PUNCT
ejpam-462	433	7	selection	selection	NOUN
ejpam-462	433	8	criteria	criterion	NOUN
ejpam-462	433	9	.	.	PUNCT
ejpam-462	434	1	in	in	ADP
ejpam-462	434	2	h.h	h.h	PROPN
ejpam-462	434	3	bock	bock	NOUN
ejpam-462	434	4	,	,	PUNCT
ejpam-462	434	5	editor	editor	NOUN
ejpam-462	434	6	,	,	PUNCT
ejpam-462	434	7	classification	classification	NOUN
ejpam-462	434	8	and	and	CCONJ
ejpam-462	434	9	related	related	ADJ
ejpam-462	434	10	methods	method	NOUN
ejpam-462	434	11	of	of	ADP
ejpam-462	434	12	data	datum	NOUN
ejpam-462	434	13	analysis	analysis	NOUN
ejpam-462	434	14	.	.	PUNCT
ejpam-462	435	1	north	north	NOUN
ejpam-462	435	2	-	-	PUNCT
ejpam-462	435	3	holland	holland	PROPN
ejpam-462	435	4	,	,	PUNCT
ejpam-462	435	5	1988	1988	NUM
ejpam-462	435	6	.	.	PUNCT
ejpam-462	436	1	[	[	X
ejpam-462	436	2	6	6	NUM
ejpam-462	436	3	]	]	PUNCT
ejpam-462	436	4	h	h	NOUN
ejpam-462	436	5	bozdogan	bozdogan	NOUN
ejpam-462	436	6	and	and	CCONJ
ejpam-462	436	7	d	d	PROPN
ejpam-462	436	8	haughton	haughton	PROPN
ejpam-462	436	9	.	.	PUNCT
ejpam-462	437	1	informational	informational	ADJ
ejpam-462	437	2	complexity	complexity	NOUN
ejpam-462	437	3	criteria	criterion	NOUN
ejpam-462	437	4	for	for	ADP
ejpam-462	437	5	regression	regression	NOUN
ejpam-462	437	6	models	model	NOUN
ejpam-462	437	7	.	.	PUNCT
ejpam-462	438	1	computational	computational	ADJ
ejpam-462	438	2	statistics	statistic	NOUN
ejpam-462	438	3	and	and	CCONJ
ejpam-462	438	4	data	datum	NOUN
ejpam-462	438	5	analysis	analysis	NOUN
ejpam-462	438	6	,	,	PUNCT
ejpam-462	438	7	28:51–76	28:51–76	NUM
ejpam-462	438	8	,	,	PUNCT
ejpam-462	438	9	1998	1998	NUM
ejpam-462	438	10	.	.	PUNCT
ejpam-462	439	1	[	[	X
ejpam-462	439	2	7	7	X
ejpam-462	439	3	]	]	X
ejpam-462	439	4	m	m	VERB
ejpam-462	439	5	chen	chen	PROPN
ejpam-462	439	6	.	.	PUNCT
ejpam-462	440	1	estimation	estimation	NOUN
ejpam-462	440	2	of	of	ADP
ejpam-462	440	3	covariance	covariance	NOUN
ejpam-462	440	4	matrices	matrix	NOUN
ejpam-462	440	5	under	under	ADP
ejpam-462	440	6	a	a	DET
ejpam-462	440	7	quadratic	quadratic	ADJ
ejpam-462	440	8	loss	loss	NOUN
ejpam-462	440	9	function	function	NOUN
ejpam-462	440	10	.	.	PUNCT
ejpam-462	441	1	research	research	NOUN
ejpam-462	441	2	report	report	PROPN
ejpam-462	441	3	s-46	s-46	PROPN
ejpam-462	441	4	,	,	PUNCT
ejpam-462	441	5	department	department	NOUN
ejpam-462	441	6	of	of	ADP
ejpam-462	441	7	mathematics	mathematics	PROPN
ejpam-462	441	8	,	,	PUNCT
ejpam-462	441	9	suny	suny	PROPN
ejpam-462	441	10	at	at	ADP
ejpam-462	441	11	albany	albany	PROPN
ejpam-462	441	12	,	,	PUNCT
ejpam-462	441	13	1976	1976	NUM
ejpam-462	441	14	.	.	PUNCT
ejpam-462	442	1	[	[	X
ejpam-462	442	2	8	8	NUM
ejpam-462	442	3	]	]	X
ejpam-462	442	4	r	r	NOUN
ejpam-462	442	5	engle	engle	NOUN
ejpam-462	442	6	and	and	CCONJ
ejpam-462	442	7	c	c	PROPN
ejpam-462	442	8	granger	granger	PROPN
ejpam-462	442	9	.	.	PUNCT
ejpam-462	443	1	cointegraion	cointegraion	NOUN
ejpam-462	443	2	and	and	CCONJ
ejpam-462	443	3	error	error	NOUN
ejpam-462	443	4	-	-	PUNCT
ejpam-462	443	5	correction	correction	NOUN
ejpam-462	443	6	:	:	PUNCT
ejpam-462	443	7	representation	representation	NOUN
ejpam-462	443	8	,	,	PUNCT
ejpam-462	443	9	estimation	estimation	NOUN
ejpam-462	443	10	and	and	CCONJ
ejpam-462	443	11	testing	testing	NOUN
ejpam-462	443	12	.	.	PUNCT
ejpam-462	444	1	econometrica	econometrica	PROPN
ejpam-462	444	2	,	,	PUNCT
ejpam-462	444	3	55:251–276	55:251–276	PROPN
ejpam-462	444	4	,	,	PUNCT
ejpam-462	444	5	1987	1987	NUM
ejpam-462	444	6	.	.	PUNCT
ejpam-462	445	1	[	[	X
ejpam-462	445	2	9	9	NUM
ejpam-462	445	3	]	]	X
ejpam-462	445	4	c	c	PROPN
ejpam-462	445	5	granger	granger	PROPN
ejpam-462	445	6	.	.	PUNCT
ejpam-462	446	1	investigating	investigate	VERB
ejpam-462	446	2	causal	causal	ADJ
ejpam-462	446	3	relations	relation	NOUN
ejpam-462	446	4	by	by	ADP
ejpam-462	446	5	econometric	econometric	ADJ
ejpam-462	446	6	models	model	NOUN
ejpam-462	446	7	and	and	CCONJ
ejpam-462	446	8	cross	cross	ADJ
ejpam-462	446	9	-	-	ADJ
ejpam-462	446	10	spectral	spectral	ADJ
ejpam-462	446	11	methods	method	NOUN
ejpam-462	446	12	.	.	PUNCT
ejpam-462	447	1	econometric	econometric	PROPN
ejpam-462	447	2	,	,	PUNCT
ejpam-462	447	3	37:424–438	37:424–438	PROPN
ejpam-462	447	4	,	,	PUNCT
ejpam-462	447	5	1969	1969	NUM
ejpam-462	447	6	.	.	PUNCT
ejpam-462	448	1	[	[	X
ejpam-462	448	2	10	10	NUM
ejpam-462	448	3	]	]	X
ejpam-462	448	4	j	j	PROPN
ejpam-462	448	5	holland	holland	PROPN
ejpam-462	448	6	.	.	PUNCT
ejpam-462	449	1	adaptation	adaptation	NOUN
ejpam-462	449	2	in	in	ADP
ejpam-462	449	3	natural	natural	ADJ
ejpam-462	449	4	and	and	CCONJ
ejpam-462	449	5	artificial	artificial	ADJ
ejpam-462	449	6	systems	system	NOUN
ejpam-462	449	7	.	.	PUNCT
ejpam-462	450	1	university	university	NOUN
ejpam-462	450	2	of	of	ADP
ejpam-462	450	3	michigan	michigan	PROPN
ejpam-462	450	4	press	press	PROPN
ejpam-462	450	5	,	,	PUNCT
ejpam-462	450	6	ann	ann	PROPN
ejpam-462	450	7	arbor	arbor	PROPN
ejpam-462	450	8	,	,	PUNCT
ejpam-462	450	9	michigan	michigan	PROPN
ejpam-462	450	10	,	,	PUNCT
ejpam-462	450	11	1975	1975	NUM
ejpam-462	450	12	.	.	PUNCT
ejpam-462	451	1	[	[	X
ejpam-462	451	2	11	11	NUM
ejpam-462	451	3	]	]	X
ejpam-462	451	4	j	j	PROPN
ejpam-462	451	5	holland	holland	PROPN
ejpam-462	451	6	.	.	PUNCT
ejpam-462	452	1	genetic	genetic	ADJ
ejpam-462	452	2	algorithms	algorithm	NOUN
ejpam-462	452	3	.	.	PUNCT
ejpam-462	453	1	scientific	scientific	ADJ
ejpam-462	453	2	american	american	PROPN
ejpam-462	453	3	,	,	PUNCT
ejpam-462	453	4	pages	page	NOUN
ejpam-462	453	5	66–72	66–72	NUM
ejpam-462	453	6	,	,	PUNCT
ejpam-462	453	7	1992	1992	NUM
ejpam-462	453	8	.	.	PUNCT
ejpam-462	454	1	[	[	X
ejpam-462	454	2	12	12	NUM
ejpam-462	454	3	]	]	X
ejpam-462	454	4	o	o	X
ejpam-462	454	5	ledoit	ledoit	NOUN
ejpam-462	454	6	and	and	CCONJ
ejpam-462	454	7	m	m	PROPN
ejpam-462	454	8	wolf	wolf	NOUN
ejpam-462	454	9	.	.	PUNCT
ejpam-462	455	1	honey	honey	NOUN
ejpam-462	455	2	,	,	PUNCT
ejpam-462	455	3	i	i	PRON
ejpam-462	455	4	shrunk	shrink	VERB
ejpam-462	455	5	the	the	DET
ejpam-462	455	6	sample	sample	NOUN
ejpam-462	455	7	covariance	covariance	NOUN
ejpam-462	455	8	matrix	matrix	NOUN
ejpam-462	455	9	.	.	PUNCT
ejpam-462	456	1	technical	technical	ADJ
ejpam-462	456	2	report	report	PROPN
ejpam-462	456	3	,	,	PUNCT
ejpam-462	456	4	universitat	universitat	ADJ
ejpam-462	456	5	pompeu	pompeu	NOUN
ejpam-462	456	6	fabra	fabra	NOUN
ejpam-462	456	7	,	,	PUNCT
ejpam-462	456	8	2003	2003	NUM
ejpam-462	456	9	.	.	PUNCT
ejpam-462	457	1	[	[	X
ejpam-462	457	2	13	13	NUM
ejpam-462	457	3	]	]	X
ejpam-462	457	4	r	r	NOUN
ejpam-462	457	5	litterman	litterman	NOUN
ejpam-462	457	6	.	.	PUNCT
ejpam-462	458	1	forecasting	forecast	VERB
ejpam-462	458	2	with	with	ADP
ejpam-462	458	3	bayesian	bayesian	NOUN
ejpam-462	458	4	vector	vector	NOUN
ejpam-462	458	5	autoregressions	autoregression	NOUN
ejpam-462	458	6	five	five	NUM
ejpam-462	458	7	years	year	NOUN
ejpam-462	458	8	of	of	ADP
ejpam-462	458	9	experience	experience	NOUN
ejpam-462	458	10	.	.	PUNCT
ejpam-462	459	1	journal	journal	NOUN
ejpam-462	459	2	of	of	ADP
ejpam-462	459	3	business	business	NOUN
ejpam-462	459	4	and	and	CCONJ
ejpam-462	459	5	economic	economic	ADJ
ejpam-462	459	6	statistics	statistic	NOUN
ejpam-462	459	7	,	,	PUNCT
ejpam-462	459	8	4:25–38	4:25–38	NUM
ejpam-462	459	9	,	,	PUNCT
ejpam-462	459	10	1986	1986	NUM
ejpam-462	459	11	.	.	PUNCT
ejpam-462	460	1	references	reference	NOUN
ejpam-462	460	2	405	405	NUM
ejpam-462	460	3	[	[	X
ejpam-462	460	4	14	14	NUM
ejpam-462	460	5	]	]	X
ejpam-462	460	6	h	h	NOUN
ejpam-462	460	7	lütkepohl	lütkepohl	NOUN
ejpam-462	460	8	.	.	PUNCT
ejpam-462	461	1	introduction	introduction	NOUN
ejpam-462	461	2	to	to	ADP
ejpam-462	461	3	multiple	multiple	ADJ
ejpam-462	461	4	time	time	NOUN
ejpam-462	461	5	series	series	PROPN
ejpam-462	461	6	analysis	analysis	NOUN
ejpam-462	461	7	.	.	PUNCT
ejpam-462	462	1	springer	springer	NOUN
ejpam-462	462	2	-	-	PUNCT
ejpam-462	462	3	verlag	verlag	PROPN
ejpam-462	462	4	,	,	PUNCT
ejpam-462	462	5	1993	1993	NUM
ejpam-462	462	6	.	.	PUNCT
ejpam-462	463	1	[	[	X
ejpam-462	463	2	15	15	NUM
ejpam-462	463	3	]	]	X
ejpam-462	463	4	j	j	PROPN
ejpam-462	463	5	magnus	magnus	PROPN
ejpam-462	463	6	and	and	CCONJ
ejpam-462	463	7	h	h	PROPN
ejpam-462	463	8	neudecker	neudecker	PROPN
ejpam-462	463	9	.	.	PUNCT
ejpam-462	464	1	matrix	matrix	NOUN
ejpam-462	464	2	differential	differential	NOUN
ejpam-462	464	3	calculus	calculus	NOUN
ejpam-462	464	4	with	with	ADP
ejpam-462	464	5	applications	application	NOUN
ejpam-462	464	6	in	in	ADP
ejpam-462	464	7	statistis	statistis	NOUN
ejpam-462	464	8	and	and	CCONJ
ejpam-462	464	9	econometrics	econometric	NOUN
ejpam-462	464	10	.	.	PUNCT
ejpam-462	465	1	wiley	wiley	PROPN
ejpam-462	465	2	,	,	PUNCT
ejpam-462	465	3	1988	1988	NUM
ejpam-462	465	4	.	.	PUNCT
ejpam-462	466	1	[	[	X
ejpam-462	466	2	16	16	NUM
ejpam-462	466	3	]	]	X
ejpam-462	466	4	k	k	PROPN
ejpam-462	466	5	mardia	mardia	PROPN
ejpam-462	466	6	.	.	PUNCT
ejpam-462	467	1	applications	application	NOUN
ejpam-462	467	2	of	of	ADP
ejpam-462	467	3	some	some	DET
ejpam-462	467	4	measures	measure	NOUN
ejpam-462	467	5	of	of	ADP
ejpam-462	467	6	multivariate	multivariate	NOUN
ejpam-462	467	7	skewness	skewness	NOUN
ejpam-462	467	8	and	and	CCONJ
ejpam-462	467	9	kurtosis	kurtosis	NOUN
ejpam-462	467	10	in	in	ADP
ejpam-462	467	11	testing	testing	NOUN
ejpam-462	467	12	normality	normality	NOUN
ejpam-462	467	13	and	and	CCONJ
ejpam-462	467	14	robustness	robustness	NOUN
ejpam-462	467	15	studies	study	NOUN
ejpam-462	467	16	.	.	PUNCT
ejpam-462	468	1	sankhya	sankhya	PROPN
ejpam-462	468	2	,	,	PUNCT
ejpam-462	468	3	b36:115–128	b36:115–128	NOUN
ejpam-462	468	4	,	,	PUNCT
ejpam-462	468	5	1974	1974	NUM
ejpam-462	468	6	.	.	PUNCT
ejpam-462	469	1	[	[	X
ejpam-462	469	2	17	17	NUM
ejpam-462	469	3	]	]	X
ejpam-462	469	4	c	c	PROPN
ejpam-462	469	5	neely	neely	PROPN
ejpam-462	469	6	,	,	PUNCT
ejpam-462	469	7	p	p	NOUN
ejpam-462	469	8	weller	weller	NOUN
ejpam-462	469	9	,	,	PUNCT
ejpam-462	469	10	and	and	CCONJ
ejpam-462	469	11	r	r	NOUN
ejpam-462	469	12	dittmar	dittmar	NOUN
ejpam-462	469	13	.	.	PUNCT
ejpam-462	470	1	is	be	AUX
ejpam-462	470	2	technical	technical	ADJ
ejpam-462	470	3	analysis	analysis	NOUN
ejpam-462	470	4	in	in	ADP
ejpam-462	470	5	the	the	DET
ejpam-462	470	6	foreighn	foreighn	ADJ
ejpam-462	470	7	exchange	exchange	NOUN
ejpam-462	470	8	market	market	NOUN
ejpam-462	470	9	profitable	profitable	ADJ
ejpam-462	470	10	?	?	PUNCT
ejpam-462	471	1	a	a	DET
ejpam-462	471	2	genetic	genetic	ADJ
ejpam-462	471	3	programming	programming	NOUN
ejpam-462	471	4	approach	approach	NOUN
ejpam-462	471	5	.	.	PUNCT
ejpam-462	472	1	journal	journal	NOUN
ejpam-462	472	2	of	of	ADP
ejpam-462	472	3	financial	financial	ADJ
ejpam-462	472	4	and	and	CCONJ
ejpam-462	472	5	quantitative	quantitative	ADJ
ejpam-462	472	6	analysis	analysis	NOUN
ejpam-462	472	7	,	,	PUNCT
ejpam-462	472	8	32(4):405–426	32(4):405–426	NUM
ejpam-462	472	9	,	,	PUNCT
ejpam-462	472	10	1997	1997	NUM
ejpam-462	472	11	.	.	PUNCT
ejpam-462	473	1	[	[	X
ejpam-462	473	2	18	18	NUM
ejpam-462	473	3	]	]	X
ejpam-462	473	4	j	j	PROPN
ejpam-462	473	5	penm	penm	NOUN
ejpam-462	473	6	and	and	CCONJ
ejpam-462	473	7	r	r	NOUN
ejpam-462	473	8	terrell	terrell	NOUN
ejpam-462	473	9	.	.	PUNCT
ejpam-462	474	1	on	on	ADP
ejpam-462	474	2	the	the	DET
ejpam-462	474	3	recursive	recursive	ADJ
ejpam-462	474	4	fitting	fitting	NOUN
ejpam-462	474	5	of	of	ADP
ejpam-462	474	6	subset	subset	ADJ
ejpam-462	474	7	autoregressions	autoregression	NOUN
ejpam-462	474	8	.	.	PUNCT
ejpam-462	475	1	journal	journal	NOUN
ejpam-462	475	2	of	of	ADP
ejpam-462	475	3	time	time	NOUN
ejpam-462	475	4	series	series	PROPN
ejpam-462	475	5	analysis	analysis	NOUN
ejpam-462	475	6	,	,	PUNCT
ejpam-462	475	7	3:43–59	3:43–59	NUM
ejpam-462	475	8	,	,	PUNCT
ejpam-462	475	9	1982	1982	NUM
ejpam-462	475	10	.	.	PUNCT
ejpam-462	476	1	[	[	X
ejpam-462	476	2	19	19	NUM
ejpam-462	476	3	]	]	PUNCT
ejpam-462	476	4	s	s	PART
ejpam-462	476	5	press	press	NOUN
ejpam-462	476	6	.	.	PUNCT
ejpam-462	477	1	estimation	estimation	NOUN
ejpam-462	477	2	of	of	ADP
ejpam-462	477	3	a	a	DET
ejpam-462	477	4	normal	normal	ADJ
ejpam-462	477	5	covariance	covariance	NOUN
ejpam-462	477	6	matrix	matrix	NOUN
ejpam-462	477	7	.	.	PUNCT
ejpam-462	478	1	technical	technical	ADJ
ejpam-462	478	2	report	report	PROPN
ejpam-462	478	3	,	,	PUNCT
ejpam-462	478	4	university	university	NOUN
ejpam-462	478	5	of	of	ADP
ejpam-462	478	6	british	british	PROPN
ejpam-462	478	7	columbia	columbia	PROPN
ejpam-462	478	8	,	,	PUNCT
ejpam-462	478	9	1975	1975	NUM
ejpam-462	478	10	.	.	PUNCT
ejpam-462	479	1	[	[	X
ejpam-462	479	2	20	20	NUM
ejpam-462	479	3	]	]	SYM
ejpam-462	479	4	b	b	X
ejpam-462	479	5	routledge	routledge	PROPN
ejpam-462	479	6	.	.	PUNCT
ejpam-462	480	1	adaptive	adaptive	ADJ
ejpam-462	480	2	learning	learn	VERB
ejpam-462	480	3	in	in	ADP
ejpam-462	480	4	financial	financial	ADJ
ejpam-462	480	5	markets	market	NOUN
ejpam-462	480	6	.	.	PUNCT
ejpam-462	481	1	in	in	ADP
ejpam-462	481	2	the	the	DET
ejpam-462	481	3	review	review	NOUN
ejpam-462	481	4	of	of	ADP
ejpam-462	481	5	financial	financial	ADJ
ejpam-462	481	6	studies	study	NOUN
ejpam-462	481	7	,	,	PUNCT
ejpam-462	481	8	volume	volume	NOUN
ejpam-462	481	9	12	12	NUM
ejpam-462	481	10	,	,	PUNCT
ejpam-462	481	11	pages	page	NOUN
ejpam-462	481	12	1165–1202	1165–1202	NUM
ejpam-462	481	13	.	.	PUNCT
ejpam-462	482	1	oxford	oxford	PROPN
ejpam-462	482	2	university	university	PROPN
ejpam-462	482	3	press	press	NOUN
ejpam-462	482	4	,	,	PUNCT
ejpam-462	482	5	1999	1999	NUM
ejpam-462	482	6	.	.	PUNCT
ejpam-462	483	1	[	[	X
ejpam-462	483	2	21	21	NUM
ejpam-462	483	3	]	]	X
ejpam-462	483	4	d	d	NOUN
ejpam-462	483	5	runkle	runkle	NOUN
ejpam-462	483	6	.	.	PUNCT
ejpam-462	484	1	vector	vector	NOUN
ejpam-462	484	2	autoregressions	autoregression	NOUN
ejpam-462	484	3	and	and	CCONJ
ejpam-462	484	4	reality	reality	NOUN
ejpam-462	484	5	.	.	PUNCT
ejpam-462	485	1	journal	journal	NOUN
ejpam-462	485	2	of	of	ADP
ejpam-462	485	3	business	business	NOUN
ejpam-462	485	4	and	and	CCONJ
ejpam-462	485	5	economic	economic	ADJ
ejpam-462	485	6	statistics	statistic	NOUN
ejpam-462	485	7	,	,	PUNCT
ejpam-462	485	8	5:437–442	5:437–442	NUM
ejpam-462	485	9	,	,	PUNCT
ejpam-462	485	10	1987	1987	NUM
ejpam-462	485	11	.	.	PUNCT
ejpam-462	486	1	[	[	X
ejpam-462	486	2	22	22	NUM
ejpam-462	486	3	]	]	PUNCT
ejpam-462	486	4	a	a	DET
ejpam-462	486	5	shurygin	shurygin	NOUN
ejpam-462	486	6	.	.	PUNCT
ejpam-462	487	1	the	the	DET
ejpam-462	487	2	linear	linear	ADJ
ejpam-462	487	3	combination	combination	NOUN
ejpam-462	487	4	of	of	ADP
ejpam-462	487	5	the	the	DET
ejpam-462	487	6	simplest	simple	ADJ
ejpam-462	487	7	discriminator	discriminator	NOUN
ejpam-462	487	8	and	and	CCONJ
ejpam-462	487	9	fisher	fisher	PROPN
ejpam-462	487	10	’s	’s	PART
ejpam-462	487	11	one	one	NUM
ejpam-462	487	12	.	.	PUNCT
ejpam-462	488	1	in	in	ADP
ejpam-462	488	2	nauka	nauka	PROPN
ejpam-462	488	3	,	,	PUNCT
ejpam-462	488	4	editor	editor	NOUN
ejpam-462	488	5	,	,	PUNCT
ejpam-462	488	6	applied	apply	VERB
ejpam-462	488	7	statistics	statistic	NOUN
ejpam-462	488	8	.	.	PUNCT
ejpam-462	489	1	moscow	moscow	PROPN
ejpam-462	489	2	,	,	PUNCT
ejpam-462	489	3	russia	russia	PROPN
ejpam-462	489	4	,	,	PUNCT
ejpam-462	489	5	1983	1983	NUM
ejpam-462	489	6	.	.	PUNCT
ejpam-462	490	1	[	[	X
ejpam-462	490	2	23	23	NUM
ejpam-462	490	3	]	]	PUNCT
ejpam-462	490	4	c	c	NOUN
ejpam-462	490	5	sims	sim	NOUN
ejpam-462	490	6	.	.	PUNCT
ejpam-462	491	1	income	income	NOUN
ejpam-462	491	2	and	and	CCONJ
ejpam-462	491	3	causality	causality	NOUN
ejpam-462	491	4	.	.	PUNCT
ejpam-462	492	1	american	american	PROPN
ejpam-462	492	2	economic	economic	PROPN
ejpam-462	492	3	review	review	PROPN
ejpam-462	492	4	.	.	PUNCT
ejpam-462	492	5	,	,	PUNCT
ejpam-462	493	1	62:540–552	62:540–552	NOUN
ejpam-462	493	2	,	,	PUNCT
ejpam-462	493	3	1972	1972	NUM
ejpam-462	493	4	.	.	PUNCT
ejpam-462	494	1	[	[	X
ejpam-462	494	2	24	24	NUM
ejpam-462	494	3	]	]	SYM
ejpam-462	494	4	c	c	NOUN
ejpam-462	494	5	sims	sim	NOUN
ejpam-462	494	6	.	.	PUNCT
ejpam-462	495	1	macroeconomics	macroeconomic	NOUN
ejpam-462	495	2	and	and	CCONJ
ejpam-462	495	3	reality	reality	NOUN
ejpam-462	495	4	.	.	PUNCT
ejpam-462	496	1	econometrica	econometrica	PROPN
ejpam-462	496	2	,	,	PUNCT
ejpam-462	496	3	48:1–48	48:1–48	NUM
ejpam-462	496	4	,	,	PUNCT
ejpam-462	496	5	1980	1980	NUM
ejpam-462	496	6	.	.	PUNCT
ejpam-462	497	1	[	[	X
ejpam-462	497	2	25	25	NUM
ejpam-462	497	3	]	]	X
ejpam-462	497	4	c	c	PROPN
ejpam-462	497	5	thomaz	thomaz	PROPN
ejpam-462	497	6	.	.	PUNCT
ejpam-462	498	1	maximum	maximum	PROPN
ejpam-462	498	2	entropy	entropy	PROPN
ejpam-462	498	3	covariance	covariance	NOUN
ejpam-462	498	4	estimate	estimate	NOUN
ejpam-462	498	5	for	for	ADP
ejpam-462	498	6	statistical	statistical	ADJ
ejpam-462	498	7	pattern	pattern	NOUN
ejpam-462	498	8	recognition	recognition	NOUN
ejpam-462	498	9	.	.	PUNCT
ejpam-462	499	1	phd	phd	NOUN
ejpam-462	499	2	thesis	thesis	PROPN
ejpam-462	499	3	,	,	PUNCT
ejpam-462	499	4	university	university	NOUN
ejpam-462	499	5	of	of	ADP
ejpam-462	499	6	london	london	PROPN
ejpam-462	499	7	and	and	CCONJ
ejpam-462	499	8	for	for	ADP
ejpam-462	499	9	the	the	DET
ejpam-462	499	10	diploma	diploma	NOUN
ejpam-462	499	11	of	of	ADP
ejpam-462	499	12	the	the	DET
ejpam-462	499	13	imperial	imperial	ADJ
ejpam-462	499	14	college	college	PROPN
ejpam-462	499	15	(	(	PUNCT
ejpam-462	499	16	d.i.c	d.i.c	PROPN
ejpam-462	499	17	.	.	PUNCT
ejpam-462	499	18	)	)	PUNCT
ejpam-462	499	19	,	,	PUNCT
ejpam-462	499	20	2004	2004	NUM
ejpam-462	499	21	.	.	PUNCT
ejpam-462	500	1	[	[	X
ejpam-462	500	2	26	26	NUM
ejpam-462	500	3	]	]	X
ejpam-462	500	4	j	j	PROPN
ejpam-462	500	5	west	west	PROPN
ejpam-462	500	6	and	and	CCONJ
ejpam-462	500	7	linster	linster	PROPN
ejpam-462	500	8	.	.	PUNCT
ejpam-462	501	1	the	the	DET
ejpam-462	501	2	evolution	evolution	NOUN
ejpam-462	501	3	of	of	ADP
ejpam-462	501	4	fuzzy	fuzzy	ADJ
ejpam-462	501	5	rules	rule	NOUN
ejpam-462	501	6	in	in	ADP
ejpam-462	501	7	two	two	NUM
ejpam-462	501	8	-	-	PUNCT
ejpam-462	501	9	player	player	NOUN
ejpam-462	501	10	games	game	NOUN
ejpam-462	501	11	.	.	PUNCT
ejpam-462	502	1	southern	southern	ADJ
ejpam-462	502	2	economic	economic	ADJ
ejpam-462	502	3	journal	journal	NOUN
ejpam-462	502	4	,	,	PUNCT
ejpam-462	502	5	69(3):705–717	69(3):705–717	PROPN
ejpam-462	502	6	,	,	PUNCT
ejpam-462	502	7	2003	2003	NUM
ejpam-462	502	8	.	.	PUNCT