id	sid	tid	token	lemma	pos
fbem-2300	1	1	frontiers	frontier	NOUN
fbem-2300	1	2	in	in	ADP
fbem-2300	1	3	business	business	NOUN
fbem-2300	1	4	,	,	PUNCT
fbem-2300	1	5	economics	economic	NOUN
fbem-2300	1	6	and	and	CCONJ
fbem-2300	1	7	management	management	NOUN
fbem-2300	1	8	issn	issn	PROPN
fbem-2300	1	9	:	:	PUNCT
fbem-2300	1	10	2766	2766	NUM
fbem-2300	1	11	-	-	PUNCT
fbem-2300	1	12	824x	824x	NUM
fbem-2300	1	13	|	|	ADJ
fbem-2300	1	14	vol	vol	NOUN
fbem-2300	1	15	.	.	PROPN
fbem-2300	2	1	6	6	NUM
fbem-2300	2	2	,	,	PUNCT
fbem-2300	2	3	no	no	INTJ
fbem-2300	2	4	.	.	NOUN
fbem-2300	2	5	1	1	NUM
fbem-2300	2	6	,	,	PUNCT
fbem-2300	2	7	2022	2022	NUM
fbem-2300	2	8	134	134	NUM
fbem-2300	2	9	research	research	NOUN
fbem-2300	2	10	on	on	ADP
fbem-2300	2	11	investment	investment	NOUN
fbem-2300	2	12	strategy	strategy	NOUN
fbem-2300	2	13	and	and	CCONJ
fbem-2300	2	14	benefit	benefit	NOUN
fbem-2300	2	15	of	of	ADP
fbem-2300	2	16	a‐share	a‐share	PUNCT
fbem-2300	2	17	traditional	traditional	ADJ
fbem-2300	2	18	chinese	chinese	ADJ
fbem-2300	2	19	medicine	medicine	NOUN
fbem-2300	2	20	industry	industry	NOUN
fbem-2300	2	21	value	value	NOUN
fbem-2300	2	22	quantification	quantification	NOUN
fbem-2300	2	23	based	base	VERB
fbem-2300	2	24	on	on	ADP
fbem-2300	2	25	machine	machine	NOUN
fbem-2300	2	26	learning	learn	VERB
fbem-2300	2	27	jiatong	jiatong	PROPN
fbem-2300	2	28	hu	hu	PROPN
fbem-2300	2	29	shanghai	shanghai	PROPN
fbem-2300	2	30	university	university	PROPN
fbem-2300	2	31	of	of	ADP
fbem-2300	2	32	finance	finance	NOUN
fbem-2300	2	33	and	and	CCONJ
fbem-2300	2	34	economics	economic	NOUN
fbem-2300	2	35	,	,	PUNCT
fbem-2300	2	36	shanghai	shanghai	PROPN
fbem-2300	2	37	,	,	PUNCT
fbem-2300	2	38	china	china	PROPN
fbem-2300	2	39	abstract	abstract	PROPN
fbem-2300	2	40	:	:	PUNCT
fbem-2300	2	41	before	before	ADP
fbem-2300	2	42	the	the	DET
fbem-2300	2	43	development	development	NOUN
fbem-2300	2	44	of	of	ADP
fbem-2300	2	45	quantitative	quantitative	ADJ
fbem-2300	2	46	investment	investment	NOUN
fbem-2300	2	47	,	,	PUNCT
fbem-2300	2	48	investors	investor	NOUN
fbem-2300	2	49	only	only	ADV
fbem-2300	2	50	used	use	VERB
fbem-2300	2	51	qualitative	qualitative	ADJ
fbem-2300	2	52	investment	investment	NOUN
fbem-2300	2	53	to	to	PART
fbem-2300	2	54	participate	participate	VERB
fbem-2300	2	55	in	in	ADP
fbem-2300	2	56	the	the	DET
fbem-2300	2	57	market	market	NOUN
fbem-2300	2	58	.	.	PUNCT
fbem-2300	3	1	with	with	ADP
fbem-2300	3	2	the	the	DET
fbem-2300	3	3	great	great	ADJ
fbem-2300	3	4	development	development	NOUN
fbem-2300	3	5	of	of	ADP
fbem-2300	3	6	information	information	NOUN
fbem-2300	3	7	technology	technology	NOUN
fbem-2300	3	8	and	and	CCONJ
fbem-2300	3	9	computer	computer	NOUN
fbem-2300	3	10	technology	technology	NOUN
fbem-2300	3	11	,	,	PUNCT
fbem-2300	3	12	investment	investment	NOUN
fbem-2300	3	13	institutions	institution	NOUN
fbem-2300	3	14	can	can	AUX
fbem-2300	3	15	use	use	VERB
fbem-2300	3	16	emerging	emerge	VERB
fbem-2300	3	17	technologies	technology	NOUN
fbem-2300	3	18	to	to	PART
fbem-2300	3	19	analyze	analyze	VERB
fbem-2300	3	20	and	and	CCONJ
fbem-2300	3	21	process	process	NOUN
fbem-2300	3	22	data	datum	NOUN
fbem-2300	3	23	,	,	PUNCT
fbem-2300	3	24	apply	apply	VERB
fbem-2300	3	25	mathematical	mathematical	ADJ
fbem-2300	3	26	models	model	NOUN
fbem-2300	3	27	to	to	ADP
fbem-2300	3	28	the	the	DET
fbem-2300	3	29	market	market	NOUN
fbem-2300	3	30	,	,	PUNCT
fbem-2300	3	31	and	and	CCONJ
fbem-2300	3	32	execute	execute	VERB
fbem-2300	3	33	them	they	PRON
fbem-2300	3	34	by	by	ADP
fbem-2300	3	35	computer	computer	NOUN
fbem-2300	3	36	instructions	instruction	NOUN
fbem-2300	3	37	.	.	PUNCT
fbem-2300	4	1	this	this	DET
fbem-2300	4	2	paper	paper	NOUN
fbem-2300	4	3	summarizes	summarize	VERB
fbem-2300	4	4	the	the	DET
fbem-2300	4	5	research	research	NOUN
fbem-2300	4	6	progress	progress	NOUN
fbem-2300	4	7	of	of	ADP
fbem-2300	4	8	applying	apply	VERB
fbem-2300	4	9	machine	machine	NOUN
fbem-2300	4	10	learning	learn	VERB
fbem-2300	4	11	technology	technology	NOUN
fbem-2300	4	12	to	to	ADP
fbem-2300	4	13	quantitative	quantitative	ADJ
fbem-2300	4	14	strategy	strategy	NOUN
fbem-2300	4	15	,	,	PUNCT
fbem-2300	4	16	especially	especially	ADV
fbem-2300	4	17	the	the	DET
fbem-2300	4	18	influence	influence	NOUN
fbem-2300	4	19	of	of	ADP
fbem-2300	4	20	bp	bp	PROPN
fbem-2300	4	21	neural	neural	ADJ
fbem-2300	4	22	network	network	NOUN
fbem-2300	4	23	on	on	ADP
fbem-2300	4	24	quantitative	quantitative	ADJ
fbem-2300	4	25	investment	investment	NOUN
fbem-2300	4	26	after	after	ADP
fbem-2300	4	27	stock	stock	NOUN
fbem-2300	4	28	selection	selection	NOUN
fbem-2300	4	29	.	.	PUNCT
fbem-2300	5	1	keywords	keyword	NOUN
fbem-2300	5	2	:	:	PUNCT
fbem-2300	5	3	machine	machine	NOUN
fbem-2300	5	4	learning	learning	NOUN
fbem-2300	5	5	,	,	PUNCT
fbem-2300	5	6	quantitative	quantitative	ADJ
fbem-2300	5	7	investment	investment	NOUN
fbem-2300	5	8	,	,	PUNCT
fbem-2300	5	9	bp	bp	PROPN
fbem-2300	5	10	neural	neural	ADJ
fbem-2300	5	11	network	network	NOUN
fbem-2300	5	12	,	,	PUNCT
fbem-2300	5	13	deep	deep	ADJ
fbem-2300	5	14	learning	learning	NOUN
fbem-2300	5	15	.	.	PUNCT
fbem-2300	6	1	1	1	X
fbem-2300	6	2	.	.	X
fbem-2300	6	3	introduction	introduction	NOUN
fbem-2300	6	4	in	in	ADP
fbem-2300	6	5	recent	recent	ADJ
fbem-2300	6	6	years	year	NOUN
fbem-2300	6	7	,	,	PUNCT
fbem-2300	6	8	the	the	DET
fbem-2300	6	9	artificial	artificial	ADJ
fbem-2300	6	10	neural	neural	ADJ
fbem-2300	6	11	network	network	NOUN
fbem-2300	6	12	,	,	PUNCT
fbem-2300	6	13	(	(	PUNCT
fbem-2300	6	14	ann	ann	PROPN
fbem-2300	6	15	)	)	PUNCT
fbem-2300	6	16	model	model	NOUN
fbem-2300	6	17	has	have	AUX
fbem-2300	6	18	made	make	VERB
fbem-2300	6	19	great	great	ADJ
fbem-2300	6	20	achievements	achievement	NOUN
fbem-2300	6	21	in	in	ADP
fbem-2300	6	22	natural	natural	ADJ
fbem-2300	6	23	language	language	NOUN
fbem-2300	6	24	processing	processing	NOUN
fbem-2300	6	25	,	,	PUNCT
fbem-2300	6	26	image	image	NOUN
fbem-2300	6	27	recognition	recognition	NOUN
fbem-2300	6	28	and	and	CCONJ
fbem-2300	6	29	other	other	ADJ
fbem-2300	6	30	fields[1	fields[1	PROPN
fbem-2300	6	31	]	]	PUNCT
fbem-2300	6	32	.	.	PUNCT
fbem-2300	7	1	with	with	ADP
fbem-2300	7	2	the	the	DET
fbem-2300	7	3	development	development	NOUN
fbem-2300	7	4	of	of	ADP
fbem-2300	7	5	gpu	gpu	PROPN
fbem-2300	7	6	technology	technology	NOUN
fbem-2300	7	7	,	,	PUNCT
fbem-2300	7	8	the	the	DET
fbem-2300	7	9	improvement	improvement	NOUN
fbem-2300	7	10	of	of	ADP
fbem-2300	7	11	computer	computer	NOUN
fbem-2300	7	12	computing	computing	NOUN
fbem-2300	7	13	power	power	NOUN
fbem-2300	7	14	and	and	CCONJ
fbem-2300	7	15	the	the	DET
fbem-2300	7	16	proposal	proposal	NOUN
fbem-2300	7	17	of	of	ADP
fbem-2300	7	18	neural	neural	ADJ
fbem-2300	7	19	network	network	NOUN
fbem-2300	7	20	optimization	optimization	NOUN
fbem-2300	7	21	algorithms	algorithm	NOUN
fbem-2300	7	22	,	,	PUNCT
fbem-2300	7	23	such	such	ADJ
fbem-2300	7	24	as	as	ADP
fbem-2300	7	25	backpropagation	backpropagation	NOUN
fbem-2300	7	26	,	,	PUNCT
fbem-2300	7	27	bp	bp	PROPN
fbem-2300	7	28	)	)	PUNCT
fbem-2300	7	29	,	,	PUNCT
fbem-2300	7	30	the	the	DET
fbem-2300	7	31	problem	problem	NOUN
fbem-2300	7	32	of	of	ADP
fbem-2300	7	33	model	model	NOUN
fbem-2300	7	34	training	training	NOUN
fbem-2300	7	35	speed	speed	NOUN
fbem-2300	7	36	that	that	PRON
fbem-2300	7	37	has	have	AUX
fbem-2300	7	38	long	long	ADV
fbem-2300	7	39	plagued	plague	VERB
fbem-2300	7	40	the	the	DET
fbem-2300	7	41	development	development	NOUN
fbem-2300	7	42	of	of	ADP
fbem-2300	7	43	deep	deep	ADJ
fbem-2300	7	44	learning	learning	NOUN
fbem-2300	7	45	has	have	AUX
fbem-2300	7	46	been	be	AUX
fbem-2300	7	47	solved[2	solved[2	ADV
fbem-2300	7	48	]	]	X
fbem-2300	7	49	.	.	PUNCT
fbem-2300	8	1	the	the	DET
fbem-2300	8	2	application	application	NOUN
fbem-2300	8	3	of	of	ADP
fbem-2300	8	4	neural	neural	ADJ
fbem-2300	8	5	network	network	NOUN
fbem-2300	8	6	in	in	ADP
fbem-2300	8	7	financial	financial	ADJ
fbem-2300	8	8	field	field	NOUN
fbem-2300	8	9	has	have	VERB
fbem-2300	8	10	a	a	DET
fbem-2300	8	11	long	long	ADJ
fbem-2300	8	12	history[3	history[3	NOUN
fbem-2300	8	13	]	]	PUNCT
fbem-2300	8	14	.	.	PUNCT
fbem-2300	9	1	at	at	ADP
fbem-2300	9	2	present	present	ADJ
fbem-2300	9	3	,	,	PUNCT
fbem-2300	9	4	an	an	DET
fbem-2300	9	5	important	important	ADJ
fbem-2300	9	6	application	application	NOUN
fbem-2300	9	7	of	of	ADP
fbem-2300	9	8	neural	neural	ADJ
fbem-2300	9	9	network	network	NOUN
fbem-2300	9	10	and	and	CCONJ
fbem-2300	9	11	deep	deep	ADJ
fbem-2300	9	12	learning	learning	NOUN
fbem-2300	9	13	algorithm	algorithm	NOUN
fbem-2300	9	14	in	in	ADP
fbem-2300	9	15	financial	financial	ADJ
fbem-2300	9	16	field	field	NOUN
fbem-2300	9	17	is	be	AUX
fbem-2300	9	18	quantitative	quantitative	ADJ
fbem-2300	9	19	investment	investment	NOUN
fbem-2300	9	20	.	.	PUNCT
fbem-2300	10	1	quantitative	quantitative	ADJ
fbem-2300	10	2	investment	investment	NOUN
fbem-2300	10	3	refers	refer	VERB
fbem-2300	10	4	to	to	ADP
fbem-2300	10	5	the	the	DET
fbem-2300	10	6	realization	realization	NOUN
fbem-2300	10	7	of	of	ADP
fbem-2300	10	8	securities	security	NOUN
fbem-2300	10	9	analysis	analysis	NOUN
fbem-2300	10	10	and	and	CCONJ
fbem-2300	10	11	prediction	prediction	NOUN
fbem-2300	10	12	with	with	ADP
fbem-2300	10	13	the	the	DET
fbem-2300	10	14	help	help	NOUN
fbem-2300	10	15	of	of	ADP
fbem-2300	10	16	computers	computer	NOUN
fbem-2300	10	17	,	,	PUNCT
fbem-2300	10	18	and	and	CCONJ
fbem-2300	10	19	then	then	ADV
fbem-2300	10	20	the	the	DET
fbem-2300	10	21	formulation	formulation	NOUN
fbem-2300	10	22	of	of	ADP
fbem-2300	10	23	feasible	feasible	ADJ
fbem-2300	10	24	quantitative	quantitative	ADJ
fbem-2300	10	25	strategies	strategy	NOUN
fbem-2300	10	26	for	for	ADP
fbem-2300	10	27	trading	trading	NOUN
fbem-2300	10	28	in	in	ADP
fbem-2300	10	29	the	the	DET
fbem-2300	10	30	securities	security	NOUN
fbem-2300	10	31	market	market	NOUN
fbem-2300	10	32	.	.	PUNCT
fbem-2300	11	1	the	the	DET
fbem-2300	11	2	traditional	traditional	ADJ
fbem-2300	11	3	quantitative	quantitative	ADJ
fbem-2300	11	4	investment	investment	NOUN
fbem-2300	11	5	strategy	strategy	NOUN
fbem-2300	11	6	is	be	AUX
fbem-2300	11	7	mainly	mainly	ADV
fbem-2300	11	8	based	base	VERB
fbem-2300	11	9	on	on	ADP
fbem-2300	11	10	statistical	statistical	ADJ
fbem-2300	11	11	learning	learning	NOUN
fbem-2300	11	12	,	,	PUNCT
fbem-2300	11	13	but	but	CCONJ
fbem-2300	11	14	the	the	DET
fbem-2300	11	15	traditional	traditional	ADJ
fbem-2300	11	16	statistical	statistical	ADJ
fbem-2300	11	17	learning	learning	NOUN
fbem-2300	11	18	method	method	NOUN
fbem-2300	11	19	has	have	VERB
fbem-2300	11	20	great	great	ADJ
fbem-2300	11	21	limitations	limitation	NOUN
fbem-2300	11	22	in	in	ADP
fbem-2300	11	23	model	model	NOUN
fbem-2300	11	24	fitting	fitting	ADJ
fbem-2300	11	25	and	and	CCONJ
fbem-2300	11	26	price	price	NOUN
fbem-2300	11	27	prediction[4	prediction[4	NOUN
fbem-2300	11	28	]	]	PUNCT
fbem-2300	11	29	.	.	PUNCT
fbem-2300	12	1	in	in	ADP
fbem-2300	12	2	recent	recent	ADJ
fbem-2300	12	3	years	year	NOUN
fbem-2300	12	4	,	,	PUNCT
fbem-2300	12	5	machine	machine	NOUN
fbem-2300	12	6	learning	learning	NOUN
fbem-2300	12	7	algorithms	algorithm	NOUN
fbem-2300	12	8	,	,	PUNCT
fbem-2300	12	9	which	which	PRON
fbem-2300	12	10	are	be	AUX
fbem-2300	12	11	developing	develop	VERB
fbem-2300	12	12	rapidly	rapidly	ADV
fbem-2300	12	13	,	,	PUNCT
fbem-2300	12	14	are	be	AUX
fbem-2300	12	15	different	different	ADJ
fbem-2300	12	16	from	from	ADP
fbem-2300	12	17	statistical	statistical	ADJ
fbem-2300	12	18	learning	learning	NOUN
fbem-2300	12	19	methods	method	NOUN
fbem-2300	12	20	.	.	PUNCT
fbem-2300	13	1	they	they	PRON
fbem-2300	13	2	have	have	VERB
fbem-2300	13	3	no	no	DET
fbem-2300	13	4	assumption	assumption	NOUN
fbem-2300	13	5	of	of	ADP
fbem-2300	13	6	distribution	distribution	NOUN
fbem-2300	13	7	for	for	ADP
fbem-2300	13	8	input	input	NOUN
fbem-2300	13	9	data	datum	NOUN
fbem-2300	13	10	,	,	PUNCT
fbem-2300	13	11	and	and	CCONJ
fbem-2300	13	12	can	can	AUX
fbem-2300	13	13	fit	fit	VERB
fbem-2300	13	14	a	a	DET
fbem-2300	13	15	variety	variety	NOUN
fbem-2300	13	16	of	of	ADP
fbem-2300	13	17	relationships[5	relationships[5	NOUN
fbem-2300	13	18	]	]	PUNCT
fbem-2300	13	19	.	.	PUNCT
fbem-2300	14	1	using	use	VERB
fbem-2300	14	2	machine	machine	NOUN
fbem-2300	14	3	learning	learn	VERB
fbem-2300	14	4	algorithms	algorithm	NOUN
fbem-2300	14	5	including	include	VERB
fbem-2300	14	6	neural	neural	ADJ
fbem-2300	14	7	network	network	NOUN
fbem-2300	14	8	models	model	NOUN
fbem-2300	14	9	to	to	PART
fbem-2300	14	10	formulate	formulate	VERB
fbem-2300	14	11	quantitative	quantitative	ADJ
fbem-2300	14	12	investment	investment	NOUN
fbem-2300	14	13	timing	timing	NOUN
fbem-2300	14	14	strategies	strategy	NOUN
fbem-2300	14	15	is	be	AUX
fbem-2300	14	16	a	a	DET
fbem-2300	14	17	very	very	ADV
fbem-2300	14	18	popular	popular	ADJ
fbem-2300	14	19	direction	direction	NOUN
fbem-2300	14	20	in	in	ADP
fbem-2300	14	21	quantitative	quantitative	ADJ
fbem-2300	14	22	investment	investment	NOUN
fbem-2300	14	23	strategy	strategy	NOUN
fbem-2300	14	24	research	research	NOUN
fbem-2300	14	25	in	in	ADP
fbem-2300	14	26	recent	recent	ADJ
fbem-2300	14	27	years	year	NOUN
fbem-2300	14	28	,	,	PUNCT
fbem-2300	14	29	and	and	CCONJ
fbem-2300	14	30	is	be	AUX
fbem-2300	14	31	also	also	ADV
fbem-2300	14	32	the	the	DET
fbem-2300	14	33	main	main	ADJ
fbem-2300	14	34	application	application	NOUN
fbem-2300	14	35	field	field	NOUN
fbem-2300	14	36	in	in	ADP
fbem-2300	14	37	the	the	DET
fbem-2300	14	38	field	field	NOUN
fbem-2300	14	39	of	of	ADP
fbem-2300	14	40	quantitative	quantitative	ADJ
fbem-2300	14	41	investment[6].it	investment[6].it	NOUN
fbem-2300	14	42	can	can	AUX
fbem-2300	14	43	be	be	AUX
fbem-2300	14	44	predicted	predict	VERB
fbem-2300	14	45	that	that	SCONJ
fbem-2300	14	46	more	more	ADJ
fbem-2300	14	47	machine	machine	NOUN
fbem-2300	14	48	learning	learning	NOUN
fbem-2300	14	49	methods	method	NOUN
fbem-2300	14	50	will	will	AUX
fbem-2300	14	51	be	be	AUX
fbem-2300	14	52	used	use	VERB
fbem-2300	14	53	in	in	ADP
fbem-2300	14	54	the	the	DET
fbem-2300	14	55	future	future	ADJ
fbem-2300	14	56	financial	financial	ADJ
fbem-2300	14	57	quantitative	quantitative	ADJ
fbem-2300	14	58	research	research	NOUN
fbem-2300	14	59	,	,	PUNCT
fbem-2300	14	60	and	and	CCONJ
fbem-2300	14	61	how	how	SCONJ
fbem-2300	14	62	to	to	PART
fbem-2300	14	63	find	find	VERB
fbem-2300	14	64	a	a	DET
fbem-2300	14	65	suitable	suitable	ADJ
fbem-2300	14	66	application	application	NOUN
fbem-2300	14	67	mode	mode	NOUN
fbem-2300	14	68	of	of	ADP
fbem-2300	14	69	machine	machine	NOUN
fbem-2300	14	70	learning	learning	NOUN
fbem-2300	14	71	has	have	AUX
fbem-2300	14	72	become	become	VERB
fbem-2300	14	73	one	one	NUM
fbem-2300	14	74	of	of	ADP
fbem-2300	14	75	the	the	DET
fbem-2300	14	76	most	most	ADV
fbem-2300	14	77	promising	promising	ADJ
fbem-2300	14	78	research	research	NOUN
fbem-2300	14	79	directions	direction	NOUN
fbem-2300	14	80	in	in	ADP
fbem-2300	14	81	the	the	DET
fbem-2300	14	82	current	current	ADJ
fbem-2300	14	83	quantitative	quantitative	ADJ
fbem-2300	14	84	research	research	NOUN
fbem-2300	14	85	field[7	field[7	PROPN
fbem-2300	14	86	]	]	PUNCT
fbem-2300	14	87	.	.	PUNCT
fbem-2300	15	1	at	at	ADP
fbem-2300	15	2	present	present	ADJ
fbem-2300	15	3	,	,	PUNCT
fbem-2300	15	4	china	china	PROPN
fbem-2300	15	5	's	's	PART
fbem-2300	15	6	research	research	NOUN
fbem-2300	15	7	in	in	ADP
fbem-2300	15	8	the	the	DET
fbem-2300	15	9	field	field	NOUN
fbem-2300	15	10	of	of	ADP
fbem-2300	15	11	quantitative	quantitative	ADJ
fbem-2300	15	12	investment	investment	NOUN
fbem-2300	15	13	is	be	AUX
fbem-2300	15	14	still	still	ADV
fbem-2300	15	15	in	in	ADP
fbem-2300	15	16	the	the	DET
fbem-2300	15	17	exploratory	exploratory	ADJ
fbem-2300	15	18	stage	stage	NOUN
fbem-2300	15	19	,	,	PUNCT
fbem-2300	15	20	so	so	CCONJ
fbem-2300	15	21	promoting	promote	VERB
fbem-2300	15	22	the	the	DET
fbem-2300	15	23	vigorous	vigorous	ADJ
fbem-2300	15	24	development	development	NOUN
fbem-2300	15	25	of	of	ADP
fbem-2300	15	26	china	china	PROPN
fbem-2300	15	27	's	's	PART
fbem-2300	15	28	quantitative	quantitative	ADJ
fbem-2300	15	29	investment	investment	NOUN
fbem-2300	15	30	is	be	AUX
fbem-2300	15	31	the	the	DET
fbem-2300	15	32	requirement	requirement	NOUN
fbem-2300	15	33	of	of	ADP
fbem-2300	15	34	the	the	DET
fbem-2300	15	35	times	time	NOUN
fbem-2300	15	36	under	under	ADP
fbem-2300	15	37	the	the	DET
fbem-2300	15	38	current	current	ADJ
fbem-2300	15	39	international	international	ADJ
fbem-2300	15	40	environment	environment	NOUN
fbem-2300	15	41	,	,	PUNCT
fbem-2300	15	42	and	and	CCONJ
fbem-2300	15	43	is	be	AUX
fbem-2300	15	44	also	also	ADV
fbem-2300	15	45	the	the	DET
fbem-2300	15	46	significance	significance	NOUN
fbem-2300	15	47	of	of	ADP
fbem-2300	15	48	this	this	DET
fbem-2300	15	49	study	study	NOUN
fbem-2300	15	50	.	.	PUNCT
fbem-2300	16	1	2	2	X
fbem-2300	16	2	.	.	X
fbem-2300	16	3	overview	overview	NOUN
fbem-2300	16	4	of	of	ADP
fbem-2300	16	5	mass	mass	ADJ
fbem-2300	16	6	production	production	NOUN
fbem-2300	16	7	investment	investment	NOUN
fbem-2300	16	8	and	and	CCONJ
fbem-2300	16	9	machine	machine	NOUN
fbem-2300	16	10	learning	learning	NOUN
fbem-2300	16	11	and	and	CCONJ
fbem-2300	16	12	related	related	ADJ
fbem-2300	16	13	theories	theory	NOUN
fbem-2300	16	14	2.1	2.1	NUM
fbem-2300	16	15	.	.	PUNCT
fbem-2300	17	1	overview	overview	NOUN
fbem-2300	17	2	of	of	ADP
fbem-2300	17	3	mass	mass	ADJ
fbem-2300	17	4	production	production	NOUN
fbem-2300	17	5	investment	investment	NOUN
fbem-2300	17	6	and	and	CCONJ
fbem-2300	17	7	machine	machine	NOUN
fbem-2300	17	8	learning	learning	NOUN
fbem-2300	17	9	theory	theory	NOUN
fbem-2300	17	10	the	the	DET
fbem-2300	17	11	so	so	ADV
fbem-2300	17	12	-	-	PUNCT
fbem-2300	17	13	called	call	VERB
fbem-2300	17	14	machine	machine	NOUN
fbem-2300	17	15	learning	learning	NOUN
fbem-2300	17	16	,	,	PUNCT
fbem-2300	17	17	in	in	ADP
fbem-2300	17	18	fact	fact	NOUN
fbem-2300	17	19	,	,	PUNCT
fbem-2300	17	20	is	be	AUX
fbem-2300	17	21	to	to	PART
fbem-2300	17	22	use	use	VERB
fbem-2300	17	23	computers	computer	NOUN
fbem-2300	17	24	to	to	PART
fbem-2300	17	25	simulate	simulate	VERB
fbem-2300	17	26	and	and	CCONJ
fbem-2300	17	27	realize	realize	VERB
fbem-2300	17	28	the	the	DET
fbem-2300	17	29	thinking	thinking	NOUN
fbem-2300	17	30	of	of	ADP
fbem-2300	17	31	human	human	ADJ
fbem-2300	17	32	brain	brain	NOUN
fbem-2300	17	33	;	;	PUNCT
fbem-2300	17	34	the	the	DET
fbem-2300	17	35	socalled	socalled	ADJ
fbem-2300	17	36	quantitative	quantitative	ADJ
fbem-2300	17	37	investment	investment	NOUN
fbem-2300	17	38	is	be	AUX
fbem-2300	17	39	actually	actually	ADV
fbem-2300	17	40	the	the	DET
fbem-2300	17	41	method	method	NOUN
fbem-2300	17	42	of	of	ADP
fbem-2300	17	43	using	use	VERB
fbem-2300	17	44	computer	computer	NOUN
fbem-2300	17	45	to	to	PART
fbem-2300	17	46	realize	realize	VERB
fbem-2300	17	47	the	the	DET
fbem-2300	17	48	choice	choice	NOUN
fbem-2300	17	49	of	of	ADP
fbem-2300	17	50	investment	investment	NOUN
fbem-2300	17	51	targets	target	NOUN
fbem-2300	17	52	,	,	PUNCT
fbem-2300	17	53	that	that	ADV
fbem-2300	17	54	is	is	ADV
fbem-2300	17	55	,	,	PUNCT
fbem-2300	17	56	analyzing	analyze	VERB
fbem-2300	17	57	the	the	DET
fbem-2300	17	58	investment	investment	NOUN
fbem-2300	17	59	objects	object	NOUN
fbem-2300	17	60	,	,	PUNCT
fbem-2300	17	61	extracting	extract	VERB
fbem-2300	17	62	transaction	transaction	NOUN
fbem-2300	17	63	information	information	NOUN
fbem-2300	17	64	and	and	CCONJ
fbem-2300	17	65	making	make	VERB
fbem-2300	17	66	a	a	DET
fbem-2300	17	67	reasonable	reasonable	ADJ
fbem-2300	17	68	investment	investment	NOUN
fbem-2300	17	69	plan[8	plan[8	NOUN
fbem-2300	17	70	]	]	X
fbem-2300	17	71	.	.	PUNCT
fbem-2300	18	1	quantitative	quantitative	ADJ
fbem-2300	18	2	investment	investment	NOUN
fbem-2300	18	3	emerged	emerge	VERB
fbem-2300	18	4	in	in	ADP
fbem-2300	18	5	1970s	1970s	NUM
fbem-2300	18	6	,	,	PUNCT
fbem-2300	18	7	and	and	CCONJ
fbem-2300	18	8	in	in	ADP
fbem-2300	18	9	the	the	DET
fbem-2300	18	10	following	follow	VERB
fbem-2300	18	11	decades	decade	NOUN
fbem-2300	18	12	,	,	PUNCT
fbem-2300	18	13	this	this	DET
fbem-2300	18	14	quantitative	quantitative	ADJ
fbem-2300	18	15	investment	investment	NOUN
fbem-2300	18	16	method	method	NOUN
fbem-2300	18	17	has	have	AUX
fbem-2300	18	18	been	be	AUX
fbem-2300	18	19	developed	develop	VERB
fbem-2300	18	20	by	by	ADP
fbem-2300	18	21	leaps	leap	NOUN
fbem-2300	18	22	and	and	CCONJ
fbem-2300	18	23	bounds	bound	NOUN
fbem-2300	18	24	,	,	PUNCT
fbem-2300	18	25	and	and	CCONJ
fbem-2300	18	26	quantitative	quantitative	ADJ
fbem-2300	18	27	investment	investment	NOUN
fbem-2300	18	28	has	have	AUX
fbem-2300	18	29	gradually	gradually	ADV
fbem-2300	18	30	been	be	AUX
fbem-2300	18	31	widely	widely	ADV
fbem-2300	18	32	studied	study	VERB
fbem-2300	18	33	and	and	CCONJ
fbem-2300	18	34	used[9].with	used[9].with	ADP
fbem-2300	18	35	the	the	DET
fbem-2300	18	36	great	great	ADJ
fbem-2300	18	37	development	development	NOUN
fbem-2300	18	38	of	of	ADP
fbem-2300	18	39	information	information	NOUN
fbem-2300	18	40	technology	technology	NOUN
fbem-2300	18	41	and	and	CCONJ
fbem-2300	18	42	computer	computer	NOUN
fbem-2300	18	43	technology	technology	NOUN
fbem-2300	18	44	,	,	PUNCT
fbem-2300	18	45	investment	investment	NOUN
fbem-2300	18	46	institutions	institution	NOUN
fbem-2300	18	47	can	can	AUX
fbem-2300	18	48	use	use	VERB
fbem-2300	18	49	emerging	emerge	VERB
fbem-2300	18	50	technologies	technology	NOUN
fbem-2300	18	51	to	to	PART
fbem-2300	18	52	analyze	analyze	VERB
fbem-2300	18	53	and	and	CCONJ
fbem-2300	18	54	process	process	NOUN
fbem-2300	18	55	data	datum	NOUN
fbem-2300	18	56	,	,	PUNCT
fbem-2300	18	57	apply	apply	VERB
fbem-2300	18	58	mathematical	mathematical	ADJ
fbem-2300	18	59	models	model	NOUN
fbem-2300	18	60	to	to	ADP
fbem-2300	18	61	the	the	DET
fbem-2300	18	62	market	market	NOUN
fbem-2300	18	63	,	,	PUNCT
fbem-2300	18	64	and	and	CCONJ
fbem-2300	18	65	execute	execute	VERB
fbem-2300	18	66	computer	computer	NOUN
fbem-2300	18	67	instructions	instruction	NOUN
fbem-2300	18	68	programmatically[10	programmatically[10	X
fbem-2300	18	69	]	]	X
fbem-2300	18	70	.	.	PUNCT
fbem-2300	19	1	different	different	ADJ
fbem-2300	19	2	from	from	ADP
fbem-2300	19	3	traditional	traditional	ADJ
fbem-2300	19	4	qualitative	qualitative	ADJ
fbem-2300	19	5	investment	investment	NOUN
fbem-2300	19	6	,	,	PUNCT
fbem-2300	19	7	quantitative	quantitative	ADJ
fbem-2300	19	8	investment	investment	NOUN
fbem-2300	19	9	uses	use	VERB
fbem-2300	19	10	a	a	DET
fbem-2300	19	11	set	set	ADJ
fbem-2300	19	12	computer	computer	NOUN
fbem-2300	19	13	model	model	NOUN
fbem-2300	19	14	and	and	CCONJ
fbem-2300	19	15	completes	complete	VERB
fbem-2300	19	16	market	market	NOUN
fbem-2300	19	17	transactions	transaction	NOUN
fbem-2300	19	18	according	accord	VERB
fbem-2300	19	19	to	to	ADP
fbem-2300	19	20	certain	certain	ADJ
fbem-2300	19	21	rules[11	rules[11	NOUN
fbem-2300	19	22	]	]	PUNCT
fbem-2300	19	23	.	.	PUNCT
fbem-2300	20	1	in	in	ADP
fbem-2300	20	2	fact	fact	NOUN
fbem-2300	20	3	,	,	PUNCT
fbem-2300	20	4	it	it	PRON
fbem-2300	20	5	is	be	AUX
fbem-2300	20	6	a	a	DET
fbem-2300	20	7	practical	practical	ADJ
fbem-2300	20	8	application	application	NOUN
fbem-2300	20	9	of	of	ADP
fbem-2300	20	10	methodology	methodology	NOUN
fbem-2300	20	11	.	.	PUNCT
fbem-2300	21	1	the	the	DET
fbem-2300	21	2	application	application	NOUN
fbem-2300	21	3	process	process	NOUN
fbem-2300	21	4	is	be	AUX
fbem-2300	21	5	more	more	ADV
fbem-2300	21	6	combined	combine	VERB
fbem-2300	21	7	with	with	ADP
fbem-2300	21	8	mathematics	mathematic	NOUN
fbem-2300	21	9	,	,	PUNCT
fbem-2300	21	10	statistics	statistic	NOUN
fbem-2300	21	11	,	,	PUNCT
fbem-2300	21	12	information	information	NOUN
fbem-2300	21	13	technology	technology	NOUN
fbem-2300	21	14	and	and	CCONJ
fbem-2300	21	15	other	other	ADJ
fbem-2300	21	16	disciplines	discipline	NOUN
fbem-2300	21	17	.	.	PUNCT
fbem-2300	22	1	in	in	ADP
fbem-2300	22	2	recent	recent	ADJ
fbem-2300	22	3	years	year	NOUN
fbem-2300	22	4	,	,	PUNCT
fbem-2300	22	5	it	it	PRON
fbem-2300	22	6	has	have	AUX
fbem-2300	22	7	incorporated	incorporate	VERB
fbem-2300	22	8	many	many	ADJ
fbem-2300	22	9	emerging	emerge	VERB
fbem-2300	22	10	computer	computer	NOUN
fbem-2300	22	11	technologies	technology	NOUN
fbem-2300	22	12	such	such	ADJ
fbem-2300	22	13	as	as	ADP
fbem-2300	22	14	machine	machine	NOUN
fbem-2300	22	15	learning	learning	NOUN
fbem-2300	22	16	,	,	PUNCT
fbem-2300	22	17	artificial	artificial	ADJ
fbem-2300	22	18	intelligence	intelligence	NOUN
fbem-2300	22	19	,	,	PUNCT
fbem-2300	22	20	and	and	CCONJ
fbem-2300	22	21	combined	combine	VERB
fbem-2300	22	22	with	with	ADP
fbem-2300	22	23	classical	classical	ADJ
fbem-2300	22	24	statistical	statistical	ADJ
fbem-2300	22	25	theory	theory	NOUN
fbem-2300	22	26	to	to	PART
fbem-2300	22	27	complete	complete	VERB
fbem-2300	22	28	data	datum	NOUN
fbem-2300	22	29	prediction	prediction	NOUN
fbem-2300	22	30	and	and	CCONJ
fbem-2300	22	31	estimation	estimation	NOUN
fbem-2300	22	32	,	,	PUNCT
fbem-2300	22	33	the	the	DET
fbem-2300	22	34	emergence	emergence	NOUN
fbem-2300	22	35	and	and	CCONJ
fbem-2300	22	36	development	development	NOUN
fbem-2300	22	37	of	of	ADP
fbem-2300	22	38	quantitative	quantitative	ADJ
fbem-2300	22	39	investment	investment	NOUN
fbem-2300	22	40	has	have	AUX
fbem-2300	22	41	expanded	expand	VERB
fbem-2300	22	42	the	the	DET
fbem-2300	22	43	asset	asset	NOUN
fbem-2300	22	44	allocation	allocation	NOUN
fbem-2300	22	45	method	method	NOUN
fbem-2300	22	46	and	and	CCONJ
fbem-2300	22	47	promoted	promote	VERB
fbem-2300	22	48	the	the	DET
fbem-2300	22	49	development	development	NOUN
fbem-2300	22	50	and	and	CCONJ
fbem-2300	22	51	perfection	perfection	NOUN
fbem-2300	22	52	of	of	ADP
fbem-2300	22	53	asset	asset	NOUN
fbem-2300	22	54	allocation	allocation	NOUN
fbem-2300	22	55	theory	theory	NOUN
fbem-2300	22	56	.	.	PUNCT
fbem-2300	23	1	in	in	ADP
fbem-2300	23	2	the	the	DET
fbem-2300	23	3	stock	stock	NOUN
fbem-2300	23	4	market	market	NOUN
fbem-2300	23	5	,	,	PUNCT
fbem-2300	23	6	the	the	DET
fbem-2300	23	7	application	application	NOUN
fbem-2300	23	8	of	of	ADP
fbem-2300	23	9	quantitative	quantitative	ADJ
fbem-2300	23	10	investment	investment	NOUN
fbem-2300	23	11	is	be	AUX
fbem-2300	23	12	the	the	DET
fbem-2300	23	13	quantitative	quantitative	ADJ
fbem-2300	23	14	stock	stock	NOUN
fbem-2300	23	15	selection	selection	NOUN
fbem-2300	23	16	,	,	PUNCT
fbem-2300	23	17	among	among	ADP
fbem-2300	23	18	which	which	PRON
fbem-2300	23	19	the	the	DET
fbem-2300	23	20	multi	multi	ADJ
fbem-2300	23	21	-	-	ADJ
fbem-2300	23	22	factor	factor	ADJ
fbem-2300	23	23	quantitative	quantitative	ADJ
fbem-2300	23	24	stock	stock	NOUN
fbem-2300	23	25	selection	selection	NOUN
fbem-2300	23	26	strategy	strategy	NOUN
fbem-2300	23	27	is	be	AUX
fbem-2300	23	28	one	one	NUM
fbem-2300	23	29	of	of	ADP
fbem-2300	23	30	the	the	DET
fbem-2300	23	31	stock	stock	NOUN
fbem-2300	23	32	selection	selection	NOUN
fbem-2300	23	33	strategies	strategy	NOUN
fbem-2300	23	34	which	which	PRON
fbem-2300	23	35	is	be	AUX
fbem-2300	23	36	widely	widely	ADV
fbem-2300	23	37	used	use	VERB
fbem-2300	23	38	and	and	CCONJ
fbem-2300	23	39	highly	highly	ADV
fbem-2300	23	40	accepted	accept	VERB
fbem-2300	23	41	by	by	ADP
fbem-2300	23	42	the	the	DET
fbem-2300	23	43	market	market	NOUN
fbem-2300	23	44	.	.	PUNCT
fbem-2300	24	1	the	the	DET
fbem-2300	24	2	factors	factor	NOUN
fbem-2300	24	3	used	use	VERB
fbem-2300	24	4	in	in	ADP
fbem-2300	24	5	this	this	DET
fbem-2300	24	6	strategy	strategy	NOUN
fbem-2300	24	7	mostly	mostly	ADV
fbem-2300	24	8	come	come	VERB
fbem-2300	24	9	from	from	ADP
fbem-2300	24	10	the	the	DET
fbem-2300	24	11	fundamental	fundamental	ADJ
fbem-2300	24	12	data	datum	NOUN
fbem-2300	24	13	of	of	ADP
fbem-2300	24	14	enterprises	enterprise	NOUN
fbem-2300	24	15	and	and	CCONJ
fbem-2300	24	16	market	market	NOUN
fbem-2300	24	17	transaction	transaction	NOUN
fbem-2300	24	18	data	datum	NOUN
fbem-2300	24	19	,	,	PUNCT
fbem-2300	24	20	and	and	CCONJ
fbem-2300	24	21	the	the	DET
fbem-2300	24	22	stock	stock	NOUN
fbem-2300	24	23	selection	selection	NOUN
fbem-2300	24	24	in	in	ADP
fbem-2300	24	25	the	the	DET
fbem-2300	24	26	strategy	strategy	NOUN
fbem-2300	24	27	135	135	NUM
fbem-2300	24	28	also	also	ADV
fbem-2300	24	29	has	have	VERB
fbem-2300	24	30	a	a	DET
fbem-2300	24	31	strong	strong	ADJ
fbem-2300	24	32	logical	logical	ADJ
fbem-2300	24	33	support	support	NOUN
fbem-2300	24	34	.	.	PUNCT
fbem-2300	25	1	good	good	ADJ
fbem-2300	25	2	factors	factor	NOUN
fbem-2300	25	3	mean	mean	VERB
fbem-2300	25	4	longterm	longterm	VERB
fbem-2300	25	5	stable	stable	ADJ
fbem-2300	25	6	income	income	NOUN
fbem-2300	25	7	,	,	PUNCT
fbem-2300	25	8	and	and	CCONJ
fbem-2300	25	9	more	more	ADJ
fbem-2300	25	10	and	and	CCONJ
fbem-2300	25	11	more	more	ADJ
fbem-2300	25	12	investors	investor	NOUN
fbem-2300	25	13	realize	realize	VERB
fbem-2300	25	14	multi	multi	ADJ
fbem-2300	25	15	-	-	ADJ
fbem-2300	25	16	factor	factor	NOUN
fbem-2300	25	17	strategies	strategy	NOUN
fbem-2300	25	18	through	through	ADP
fbem-2300	25	19	different	different	ADJ
fbem-2300	25	20	channels	channel	NOUN
fbem-2300	25	21	and	and	CCONJ
fbem-2300	25	22	ways	way	NOUN
fbem-2300	25	23	in	in	ADP
fbem-2300	25	24	order	order	NOUN
fbem-2300	25	25	to	to	PART
fbem-2300	25	26	obtain	obtain	VERB
fbem-2300	25	27	excess	excess	ADJ
fbem-2300	25	28	returns	return	NOUN
fbem-2300	25	29	from	from	ADP
fbem-2300	25	30	the	the	DET
fbem-2300	25	31	market	market	NOUN
fbem-2300	25	32	.	.	PUNCT
fbem-2300	26	1	therefore	therefore	ADV
fbem-2300	26	2	,	,	PUNCT
fbem-2300	26	3	the	the	DET
fbem-2300	26	4	nonlinear	nonlinear	ADJ
fbem-2300	26	5	dimension	dimension	NOUN
fbem-2300	26	6	can	can	AUX
fbem-2300	26	7	be	be	AUX
fbem-2300	26	8	considered	consider	VERB
fbem-2300	26	9	when	when	SCONJ
fbem-2300	26	10	constructing	construct	VERB
fbem-2300	26	11	the	the	DET
fbem-2300	26	12	stock	stock	NOUN
fbem-2300	26	13	return	return	NOUN
fbem-2300	26	14	prediction	prediction	NOUN
fbem-2300	26	15	model	model	NOUN
fbem-2300	26	16	.	.	PUNCT
fbem-2300	27	1	various	various	ADJ
fbem-2300	27	2	algorithms	algorithm	NOUN
fbem-2300	27	3	in	in	ADP
fbem-2300	27	4	machine	machine	NOUN
fbem-2300	27	5	learning	learning	NOUN
fbem-2300	27	6	can	can	AUX
fbem-2300	27	7	simulate	simulate	VERB
fbem-2300	27	8	nonlinear	nonlinear	ADJ
fbem-2300	27	9	relations	relation	NOUN
fbem-2300	27	10	well	well	ADV
fbem-2300	27	11	,	,	PUNCT
fbem-2300	27	12	among	among	ADP
fbem-2300	27	13	which	which	PRON
fbem-2300	27	14	neural	neural	ADJ
fbem-2300	27	15	network	network	NOUN
fbem-2300	27	16	can	can	AUX
fbem-2300	27	17	simulate	simulate	VERB
fbem-2300	27	18	any	any	DET
fbem-2300	27	19	function	function	NOUN
fbem-2300	27	20	in	in	ADP
fbem-2300	27	21	theory	theory	NOUN
fbem-2300	27	22	.	.	PUNCT
fbem-2300	28	1	the	the	DET
fbem-2300	28	2	machine	machine	NOUN
fbem-2300	28	3	learning	learn	VERB
fbem-2300	28	4	methods	method	NOUN
fbem-2300	28	5	represented	represent	VERB
fbem-2300	28	6	by	by	ADP
fbem-2300	28	7	neural	neural	ADJ
fbem-2300	28	8	network	network	NOUN
fbem-2300	28	9	have	have	VERB
fbem-2300	28	10	strong	strong	ADJ
fbem-2300	28	11	self	self	NOUN
fbem-2300	28	12	-	-	PUNCT
fbem-2300	28	13	learning	learn	VERB
fbem-2300	28	14	ability	ability	NOUN
fbem-2300	28	15	,	,	PUNCT
fbem-2300	28	16	and	and	CCONJ
fbem-2300	28	17	certain	certain	ADJ
fbem-2300	28	18	robustness	robustness	NOUN
fbem-2300	28	19	and	and	CCONJ
fbem-2300	28	20	fault	fault	VERB
fbem-2300	28	21	tolerance	tolerance	NOUN
fbem-2300	28	22	.	.	PUNCT
fbem-2300	29	1	2.2	2.2	NUM
fbem-2300	29	2	.	.	PUNCT
fbem-2300	30	1	the	the	DET
fbem-2300	30	2	impact	impact	NOUN
fbem-2300	30	3	of	of	ADP
fbem-2300	30	4	machine	machine	NOUN
fbem-2300	30	5	learning	learn	VERB
fbem-2300	30	6	on	on	ADP
fbem-2300	30	7	quantitative	quantitative	ADJ
fbem-2300	30	8	investment	investment	NOUN
fbem-2300	30	9	machine	machine	NOUN
fbem-2300	30	10	learning	learn	VERB
fbem-2300	30	11	algorithm	algorithm	NOUN
fbem-2300	30	12	is	be	AUX
fbem-2300	30	13	a	a	DET
fbem-2300	30	14	kind	kind	NOUN
fbem-2300	30	15	of	of	ADP
fbem-2300	30	16	data	datum	NOUN
fbem-2300	30	17	analysis	analysis	NOUN
fbem-2300	30	18	method	method	NOUN
fbem-2300	30	19	that	that	PRON
fbem-2300	30	20	can	can	AUX
fbem-2300	30	21	learn	learn	VERB
fbem-2300	30	22	from	from	ADP
fbem-2300	30	23	historical	historical	ADJ
fbem-2300	30	24	data	datum	NOUN
fbem-2300	30	25	.	.	PUNCT
fbem-2300	31	1	it	it	PRON
fbem-2300	31	2	learns	learn	VERB
fbem-2300	31	3	and	and	CCONJ
fbem-2300	31	4	perfects	perfect	VERB
fbem-2300	31	5	existing	exist	VERB
fbem-2300	31	6	patterns	pattern	NOUN
fbem-2300	31	7	from	from	ADP
fbem-2300	31	8	feature	feature	NOUN
fbem-2300	31	9	data	datum	NOUN
fbem-2300	31	10	sets	set	NOUN
fbem-2300	31	11	,	,	PUNCT
fbem-2300	31	12	and	and	CCONJ
fbem-2300	31	13	is	be	AUX
fbem-2300	31	14	used	use	VERB
fbem-2300	31	15	to	to	PART
fbem-2300	31	16	accomplish	accomplish	VERB
fbem-2300	31	17	common	common	ADJ
fbem-2300	31	18	tasks	task	NOUN
fbem-2300	31	19	such	such	ADJ
fbem-2300	31	20	as	as	ADP
fbem-2300	31	21	data	datum	NOUN
fbem-2300	31	22	classification	classification	NOUN
fbem-2300	31	23	,	,	PUNCT
fbem-2300	31	24	regression	regression	NOUN
fbem-2300	31	25	and	and	CCONJ
fbem-2300	31	26	unsupervised	unsupervised	ADJ
fbem-2300	31	27	fitting	fitting	ADJ
fbem-2300	31	28	.	.	PUNCT
fbem-2300	32	1	the	the	DET
fbem-2300	32	2	general	general	ADJ
fbem-2300	32	3	flow	flow	NOUN
fbem-2300	32	4	chart	chart	NOUN
fbem-2300	32	5	of	of	ADP
fbem-2300	32	6	machine	machine	NOUN
fbem-2300	32	7	learning	learning	NOUN
fbem-2300	32	8	is	be	AUX
fbem-2300	32	9	shown	show	VERB
fbem-2300	32	10	in	in	ADP
fbem-2300	32	11	figure	figure	NOUN
fbem-2300	32	12	1	1	NUM
fbem-2300	32	13	.	.	PUNCT
fbem-2300	33	1	figure	figure	NOUN
fbem-2300	33	2	1	1	NUM
fbem-2300	33	3	.	.	PUNCT
fbem-2300	33	4	machine	machine	NOUN
fbem-2300	33	5	learning	learning	NOUN
fbem-2300	33	6	flow	flow	NOUN
fbem-2300	33	7	chart	chart	NOUN
fbem-2300	33	8	learning	learning	NOUN
fbem-2300	33	9	is	be	AUX
fbem-2300	33	10	a	a	DET
fbem-2300	33	11	branch	branch	NOUN
fbem-2300	33	12	of	of	ADP
fbem-2300	33	13	artificial	artificial	ADJ
fbem-2300	33	14	intelligence	intelligence	NOUN
fbem-2300	33	15	,	,	PUNCT
fbem-2300	33	16	and	and	CCONJ
fbem-2300	33	17	its	its	PRON
fbem-2300	33	18	core	core	NOUN
fbem-2300	33	19	advantage	advantage	NOUN
fbem-2300	33	20	is	be	AUX
fbem-2300	33	21	learning	learn	VERB
fbem-2300	33	22	ability	ability	NOUN
fbem-2300	33	23	,	,	PUNCT
fbem-2300	33	24	which	which	PRON
fbem-2300	33	25	is	be	AUX
fbem-2300	33	26	also	also	ADV
fbem-2300	33	27	the	the	DET
fbem-2300	33	28	difference	difference	NOUN
fbem-2300	33	29	between	between	ADP
fbem-2300	33	30	it	it	PRON
fbem-2300	33	31	and	and	CCONJ
fbem-2300	33	32	traditional	traditional	ADJ
fbem-2300	33	33	algorithms	algorithm	NOUN
fbem-2300	33	34	.	.	PUNCT
fbem-2300	34	1	the	the	DET
fbem-2300	34	2	machine	machine	NOUN
fbem-2300	34	3	can	can	AUX
fbem-2300	34	4	learn	learn	VERB
fbem-2300	34	5	historical	historical	ADJ
fbem-2300	34	6	data	datum	NOUN
fbem-2300	34	7	and	and	CCONJ
fbem-2300	34	8	find	find	VERB
fbem-2300	34	9	its	its	PRON
fbem-2300	34	10	own	own	ADJ
fbem-2300	34	11	rules	rule	NOUN
fbem-2300	34	12	.	.	PUNCT
fbem-2300	35	1	secondly	secondly	ADV
fbem-2300	35	2	,	,	PUNCT
fbem-2300	35	3	compared	compare	VERB
fbem-2300	35	4	with	with	ADP
fbem-2300	35	5	traditional	traditional	ADJ
fbem-2300	35	6	programming	programming	NOUN
fbem-2300	35	7	methods	method	NOUN
fbem-2300	35	8	,	,	PUNCT
fbem-2300	35	9	machine	machine	NOUN
fbem-2300	35	10	learning	learning	NOUN
fbem-2300	35	11	has	have	VERB
fbem-2300	35	12	the	the	DET
fbem-2300	35	13	advantages	advantage	NOUN
fbem-2300	35	14	that	that	SCONJ
fbem-2300	35	15	firstly	firstly	ADV
fbem-2300	35	16	,	,	PUNCT
fbem-2300	35	17	it	it	PRON
fbem-2300	35	18	can	can	AUX
fbem-2300	35	19	simplify	simplify	VERB
fbem-2300	35	20	the	the	DET
fbem-2300	35	21	code	code	NOUN
fbem-2300	35	22	and	and	CCONJ
fbem-2300	35	23	improve	improve	VERB
fbem-2300	35	24	the	the	DET
fbem-2300	35	25	execution	execution	NOUN
fbem-2300	35	26	ability	ability	NOUN
fbem-2300	35	27	of	of	ADP
fbem-2300	35	28	the	the	DET
fbem-2300	35	29	code	code	NOUN
fbem-2300	35	30	through	through	ADP
fbem-2300	35	31	machine	machine	NOUN
fbem-2300	35	32	learning	learning	NOUN
fbem-2300	35	33	algorithms	algorithm	NOUN
fbem-2300	35	34	;	;	PUNCT
fbem-2300	35	35	secondly	secondly	ADV
fbem-2300	35	36	,	,	PUNCT
fbem-2300	35	37	it	it	PRON
fbem-2300	35	38	can	can	AUX
fbem-2300	35	39	find	find	VERB
fbem-2300	35	40	a	a	DET
fbem-2300	35	41	solution	solution	NOUN
fbem-2300	35	42	to	to	ADP
fbem-2300	35	43	the	the	DET
fbem-2300	35	44	problems	problem	NOUN
fbem-2300	35	45	that	that	PRON
fbem-2300	35	46	can	can	AUX
fbem-2300	35	47	not	not	PART
fbem-2300	35	48	be	be	AUX
fbem-2300	35	49	solved	solve	VERB
fbem-2300	35	50	by	by	ADP
fbem-2300	35	51	traditional	traditional	ADJ
fbem-2300	35	52	methods	method	NOUN
fbem-2300	35	53	through	through	ADP
fbem-2300	35	54	machine	machine	NOUN
fbem-2300	35	55	learning	learn	VERB
fbem-2300	35	56	technology	technology	NOUN
fbem-2300	35	57	.	.	PUNCT
fbem-2300	36	1	furthermore	furthermore	ADV
fbem-2300	36	2	,	,	PUNCT
fbem-2300	36	3	machine	machine	NOUN
fbem-2300	36	4	learning	learning	NOUN
fbem-2300	36	5	can	can	AUX
fbem-2300	36	6	adapt	adapt	VERB
fbem-2300	36	7	to	to	ADP
fbem-2300	36	8	the	the	DET
fbem-2300	36	9	changes	change	NOUN
fbem-2300	36	10	of	of	ADP
fbem-2300	36	11	new	new	ADJ
fbem-2300	36	12	data	datum	NOUN
fbem-2300	36	13	and	and	CCONJ
fbem-2300	36	14	realize	realize	VERB
fbem-2300	36	15	system	system	NOUN
fbem-2300	36	16	personalization	personalization	NOUN
fbem-2300	36	17	according	accord	VERB
fbem-2300	36	18	to	to	ADP
fbem-2300	36	19	different	different	ADJ
fbem-2300	36	20	environments	environment	NOUN
fbem-2300	36	21	.	.	PUNCT
fbem-2300	37	1	learn	learn	VERB
fbem-2300	37	2	the	the	DET
fbem-2300	37	3	historical	historical	ADJ
fbem-2300	37	4	data	datum	NOUN
fbem-2300	37	5	of	of	ADP
fbem-2300	37	6	the	the	DET
fbem-2300	37	7	machine	machine	NOUN
fbem-2300	37	8	,	,	PUNCT
fbem-2300	37	9	and	and	CCONJ
fbem-2300	37	10	self	self	NOUN
fbem-2300	37	11	-	-	PUNCT
fbem-2300	37	12	explore	explore	VERB
fbem-2300	37	13	the	the	DET
fbem-2300	37	14	rules	rule	NOUN
fbem-2300	37	15	.	.	PUNCT
fbem-2300	38	1	secondly	secondly	ADV
fbem-2300	38	2	,	,	PUNCT
fbem-2300	38	3	compared	compare	VERB
fbem-2300	38	4	with	with	ADP
fbem-2300	38	5	traditional	traditional	ADJ
fbem-2300	38	6	programming	programming	NOUN
fbem-2300	38	7	methods	method	NOUN
fbem-2300	38	8	,	,	PUNCT
fbem-2300	38	9	machine	machine	NOUN
fbem-2300	38	10	learning	learning	NOUN
fbem-2300	38	11	has	have	VERB
fbem-2300	38	12	the	the	DET
fbem-2300	38	13	advantages	advantage	NOUN
fbem-2300	38	14	that	that	SCONJ
fbem-2300	38	15	firstly	firstly	ADV
fbem-2300	38	16	,	,	PUNCT
fbem-2300	38	17	it	it	PRON
fbem-2300	38	18	can	can	AUX
fbem-2300	38	19	simplify	simplify	VERB
fbem-2300	38	20	the	the	DET
fbem-2300	38	21	code	code	NOUN
fbem-2300	38	22	and	and	CCONJ
fbem-2300	38	23	improve	improve	VERB
fbem-2300	38	24	the	the	DET
fbem-2300	38	25	execution	execution	NOUN
fbem-2300	38	26	ability	ability	NOUN
fbem-2300	38	27	of	of	ADP
fbem-2300	38	28	the	the	DET
fbem-2300	38	29	code	code	NOUN
fbem-2300	38	30	through	through	ADP
fbem-2300	38	31	machine	machine	NOUN
fbem-2300	38	32	learning	learning	NOUN
fbem-2300	38	33	algorithms	algorithm	NOUN
fbem-2300	38	34	;	;	PUNCT
fbem-2300	38	35	secondly	secondly	ADV
fbem-2300	38	36	,	,	PUNCT
fbem-2300	38	37	it	it	PRON
fbem-2300	38	38	can	can	AUX
fbem-2300	38	39	find	find	VERB
fbem-2300	38	40	a	a	DET
fbem-2300	38	41	solution	solution	NOUN
fbem-2300	38	42	to	to	ADP
fbem-2300	38	43	the	the	DET
fbem-2300	38	44	problems	problem	NOUN
fbem-2300	38	45	that	that	PRON
fbem-2300	38	46	can	can	AUX
fbem-2300	38	47	not	not	PART
fbem-2300	38	48	be	be	AUX
fbem-2300	38	49	solved	solve	VERB
fbem-2300	38	50	by	by	ADP
fbem-2300	38	51	traditional	traditional	ADJ
fbem-2300	38	52	methods	method	NOUN
fbem-2300	38	53	through	through	ADP
fbem-2300	38	54	machine	machine	NOUN
fbem-2300	38	55	learning	learn	VERB
fbem-2300	38	56	technology	technology	NOUN
fbem-2300	38	57	.	.	PUNCT
fbem-2300	39	1	furthermore	furthermore	ADV
fbem-2300	39	2	,	,	PUNCT
fbem-2300	39	3	machine	machine	NOUN
fbem-2300	39	4	learning	learning	NOUN
fbem-2300	39	5	can	can	AUX
fbem-2300	39	6	adapt	adapt	VERB
fbem-2300	39	7	to	to	ADP
fbem-2300	39	8	the	the	DET
fbem-2300	39	9	changes	change	NOUN
fbem-2300	39	10	of	of	ADP
fbem-2300	39	11	new	new	ADJ
fbem-2300	39	12	data	datum	NOUN
fbem-2300	39	13	and	and	CCONJ
fbem-2300	39	14	realize	realize	VERB
fbem-2300	39	15	system	system	NOUN
fbem-2300	39	16	personalization	personalization	NOUN
fbem-2300	39	17	according	accord	VERB
fbem-2300	39	18	to	to	ADP
fbem-2300	39	19	different	different	ADJ
fbem-2300	39	20	environments	environment	NOUN
fbem-2300	39	21	.	.	PUNCT
fbem-2300	40	1	applying	apply	VERB
fbem-2300	40	2	machine	machine	NOUN
fbem-2300	40	3	learning	learning	NOUN
fbem-2300	40	4	to	to	ADP
fbem-2300	40	5	the	the	DET
fbem-2300	40	6	field	field	NOUN
fbem-2300	40	7	of	of	ADP
fbem-2300	40	8	financial	financial	ADJ
fbem-2300	40	9	quantification	quantification	NOUN
fbem-2300	40	10	can	can	AUX
fbem-2300	40	11	help	help	VERB
fbem-2300	40	12	investors	investor	NOUN
fbem-2300	40	13	find	find	VERB
fbem-2300	40	14	the	the	DET
fbem-2300	40	15	laws	law	NOUN
fbem-2300	40	16	between	between	ADP
fbem-2300	40	17	financial	financial	ADJ
fbem-2300	40	18	data	datum	NOUN
fbem-2300	40	19	that	that	PRON
fbem-2300	40	20	can	can	AUX
fbem-2300	40	21	not	not	PART
fbem-2300	40	22	be	be	AUX
fbem-2300	40	23	found	find	VERB
fbem-2300	40	24	by	by	ADP
fbem-2300	40	25	manpower	manpower	NOUN
fbem-2300	40	26	and	and	CCONJ
fbem-2300	40	27	reproduce	reproduce	VERB
fbem-2300	40	28	them	they	PRON
fbem-2300	40	29	.	.	PUNCT
fbem-2300	41	1	this	this	PRON
fbem-2300	41	2	is	be	AUX
fbem-2300	41	3	based	base	VERB
fbem-2300	41	4	on	on	ADP
fbem-2300	41	5	machine	machine	NOUN
fbem-2300	41	6	learning	learning	NOUN
fbem-2300	41	7	,	,	PUNCT
fbem-2300	41	8	which	which	PRON
fbem-2300	41	9	can	can	AUX
fbem-2300	41	10	analyze	analyze	VERB
fbem-2300	41	11	massive	massive	ADJ
fbem-2300	41	12	and	and	CCONJ
fbem-2300	41	13	high	high	ADJ
fbem-2300	41	14	-	-	PUNCT
fbem-2300	41	15	dimensional	dimensional	ADJ
fbem-2300	41	16	transaction	transaction	NOUN
fbem-2300	41	17	data	datum	NOUN
fbem-2300	41	18	,	,	PUNCT
fbem-2300	41	19	synthesize	synthesize	VERB
fbem-2300	41	20	various	various	ADJ
fbem-2300	41	21	information	information	NOUN
fbem-2300	41	22	,	,	PUNCT
fbem-2300	41	23	and	and	CCONJ
fbem-2300	41	24	discover	discover	VERB
fbem-2300	41	25	potential	potential	ADJ
fbem-2300	41	26	correlation	correlation	NOUN
fbem-2300	41	27	factors	factor	NOUN
fbem-2300	41	28	among	among	ADP
fbem-2300	41	29	financial	financial	ADJ
fbem-2300	41	30	data	datum	NOUN
fbem-2300	41	31	.	.	PUNCT
fbem-2300	42	1	moreover	moreover	ADV
fbem-2300	42	2	,	,	PUNCT
fbem-2300	42	3	its	its	PRON
fbem-2300	42	4	distributed	distribute	VERB
fbem-2300	42	5	operation	operation	NOUN
fbem-2300	42	6	can	can	AUX
fbem-2300	42	7	greatly	greatly	ADV
fbem-2300	42	8	shorten	shorten	VERB
fbem-2300	42	9	the	the	DET
fbem-2300	42	10	operation	operation	NOUN
fbem-2300	42	11	time	time	NOUN
fbem-2300	42	12	and	and	CCONJ
fbem-2300	42	13	reduce	reduce	VERB
fbem-2300	42	14	the	the	DET
fbem-2300	42	15	transaction	transaction	NOUN
fbem-2300	42	16	timeliness	timeliness	NOUN
fbem-2300	42	17	risk	risk	NOUN
fbem-2300	42	18	.	.	PUNCT
fbem-2300	43	1	if	if	SCONJ
fbem-2300	43	2	you	you	PRON
fbem-2300	43	3	want	want	VERB
fbem-2300	43	4	to	to	PART
fbem-2300	43	5	build	build	VERB
fbem-2300	43	6	a	a	DET
fbem-2300	43	7	successful	successful	ADJ
fbem-2300	43	8	quantitative	quantitative	ADJ
fbem-2300	43	9	investment	investment	NOUN
fbem-2300	43	10	model	model	NOUN
fbem-2300	43	11	based	base	VERB
fbem-2300	43	12	on	on	ADP
fbem-2300	43	13	machine	machine	NOUN
fbem-2300	43	14	learning	learning	NOUN
fbem-2300	43	15	,	,	PUNCT
fbem-2300	43	16	you	you	PRON
fbem-2300	43	17	need	need	VERB
fbem-2300	43	18	to	to	PART
fbem-2300	43	19	carefully	carefully	ADV
fbem-2300	43	20	select	select	VERB
fbem-2300	43	21	samples	sample	NOUN
fbem-2300	43	22	and	and	CCONJ
fbem-2300	43	23	preprocess	preprocess	NOUN
fbem-2300	43	24	data	datum	NOUN
fbem-2300	43	25	;	;	PUNCT
fbem-2300	43	26	the	the	DET
fbem-2300	43	27	selection	selection	NOUN
fbem-2300	43	28	of	of	ADP
fbem-2300	43	29	machine	machine	NOUN
fbem-2300	43	30	learning	learning	NOUN
fbem-2300	43	31	model	model	NOUN
fbem-2300	43	32	,	,	PUNCT
fbem-2300	43	33	the	the	DET
fbem-2300	43	34	selection	selection	NOUN
fbem-2300	43	35	of	of	ADP
fbem-2300	43	36	model	model	NOUN
fbem-2300	43	37	algorithm	algorithm	NOUN
fbem-2300	43	38	and	and	CCONJ
fbem-2300	43	39	the	the	DET
fbem-2300	43	40	setting	setting	NOUN
fbem-2300	43	41	of	of	ADP
fbem-2300	43	42	parameters	parameter	NOUN
fbem-2300	43	43	are	be	AUX
fbem-2300	43	44	all	all	ADV
fbem-2300	43	45	complicated	complicated	ADJ
fbem-2300	43	46	preparatory	preparatory	ADJ
fbem-2300	43	47	work	work	NOUN
fbem-2300	43	48	;	;	PUNCT
fbem-2300	43	49	after	after	ADP
fbem-2300	43	50	running	run	VERB
fbem-2300	43	51	the	the	DET
fbem-2300	43	52	machine	machine	NOUN
fbem-2300	43	53	learning	learning	NOUN
fbem-2300	43	54	model	model	NOUN
fbem-2300	43	55	,	,	PUNCT
fbem-2300	43	56	it	it	PRON
fbem-2300	43	57	is	be	AUX
fbem-2300	43	58	necessary	necessary	ADJ
fbem-2300	43	59	to	to	PART
fbem-2300	43	60	modify	modify	VERB
fbem-2300	43	61	the	the	DET
fbem-2300	43	62	parameters	parameter	NOUN
fbem-2300	43	63	repeatedly	repeatedly	ADV
fbem-2300	43	64	according	accord	VERB
fbem-2300	43	65	to	to	ADP
fbem-2300	43	66	the	the	DET
fbem-2300	43	67	results	result	NOUN
fbem-2300	43	68	,	,	PUNCT
fbem-2300	43	69	test	test	VERB
fbem-2300	43	70	the	the	DET
fbem-2300	43	71	model	model	NOUN
fbem-2300	43	72	again	again	ADV
fbem-2300	43	73	and	and	CCONJ
fbem-2300	43	74	again	again	ADV
fbem-2300	43	75	,	,	PUNCT
fbem-2300	43	76	and	and	CCONJ
fbem-2300	43	77	optimize	optimize	VERB
fbem-2300	43	78	the	the	DET
fbem-2300	43	79	model	model	NOUN
fbem-2300	43	80	several	several	ADJ
fbem-2300	43	81	times	time	NOUN
fbem-2300	43	82	to	to	PART
fbem-2300	43	83	obtain	obtain	VERB
fbem-2300	43	84	an	an	DET
fbem-2300	43	85	optimal	optimal	ADJ
fbem-2300	43	86	learning	learning	NOUN
fbem-2300	43	87	result	result	NOUN
fbem-2300	43	88	.	.	PUNCT
fbem-2300	44	1	3	3	X
fbem-2300	44	2	.	.	X
fbem-2300	44	3	make	make	VERB
fbem-2300	44	4	quantitative	quantitative	ADJ
fbem-2300	44	5	investment	investment	NOUN
fbem-2300	44	6	through	through	ADP
fbem-2300	44	7	machine	machine	NOUN
fbem-2300	44	8	learning	learn	VERB
fbem-2300	44	9	stock	stock	NOUN
fbem-2300	44	10	selection	selection	NOUN
fbem-2300	44	11	3.1	3.1	NUM
fbem-2300	44	12	.	.	PUNCT
fbem-2300	44	13	machine	machine	NOUN
fbem-2300	44	14	learning	learning	NOUN
fbem-2300	44	15	and	and	CCONJ
fbem-2300	44	16	quantitative	quantitative	ADJ
fbem-2300	44	17	investment	investment	NOUN
fbem-2300	44	18	the	the	DET
fbem-2300	44	19	ultimate	ultimate	ADJ
fbem-2300	44	20	goal	goal	NOUN
fbem-2300	44	21	of	of	ADP
fbem-2300	44	22	quantitative	quantitative	ADJ
fbem-2300	44	23	research	research	NOUN
fbem-2300	44	24	is	be	AUX
fbem-2300	44	25	to	to	PART
fbem-2300	44	26	predict	predict	VERB
fbem-2300	44	27	the	the	DET
fbem-2300	44	28	future	future	ADJ
fbem-2300	44	29	trend	trend	NOUN
fbem-2300	44	30	of	of	ADP
fbem-2300	44	31	securities	security	NOUN
fbem-2300	44	32	,	,	PUNCT
fbem-2300	44	33	and	and	CCONJ
fbem-2300	44	34	to	to	PART
fbem-2300	44	35	make	make	VERB
fbem-2300	44	36	a	a	DET
fbem-2300	44	37	profit	profit	NOUN
fbem-2300	44	38	by	by	ADP
fbem-2300	44	39	"	"	PUNCT
fbem-2300	44	40	buying	buy	VERB
fbem-2300	44	41	low	low	ADJ
fbem-2300	44	42	and	and	CCONJ
fbem-2300	44	43	selling	sell	VERB
fbem-2300	44	44	high	high	ADJ
fbem-2300	44	45	"	"	PUNCT
fbem-2300	44	46	according	accord	VERB
fbem-2300	44	47	to	to	ADP
fbem-2300	44	48	the	the	DET
fbem-2300	44	49	prediction	prediction	NOUN
fbem-2300	44	50	.	.	PUNCT
fbem-2300	45	1	quantitative	quantitative	ADJ
fbem-2300	45	2	timing	timing	NOUN
fbem-2300	45	3	research	research	NOUN
fbem-2300	45	4	is	be	AUX
fbem-2300	45	5	to	to	PART
fbem-2300	45	6	judge	judge	VERB
fbem-2300	45	7	whether	whether	SCONJ
fbem-2300	45	8	the	the	DET
fbem-2300	45	9	current	current	ADJ
fbem-2300	45	10	time	time	NOUN
fbem-2300	45	11	point	point	NOUN
fbem-2300	45	12	is	be	AUX
fbem-2300	45	13	the	the	DET
fbem-2300	45	14	low	low	ADJ
fbem-2300	45	15	point	point	NOUN
fbem-2300	45	16	or	or	CCONJ
fbem-2300	45	17	the	the	DET
fbem-2300	45	18	high	high	ADJ
fbem-2300	45	19	point	point	NOUN
fbem-2300	45	20	of	of	ADP
fbem-2300	45	21	the	the	DET
fbem-2300	45	22	price	price	NOUN
fbem-2300	45	23	only	only	ADV
fbem-2300	45	24	by	by	ADP
fbem-2300	45	25	judging	judge	VERB
fbem-2300	45	26	the	the	DET
fbem-2300	45	27	price	price	NOUN
fbem-2300	45	28	trend	trend	NOUN
fbem-2300	45	29	of	of	ADP
fbem-2300	45	30	a	a	DET
fbem-2300	45	31	security	security	NOUN
fbem-2300	45	32	,	,	PUNCT
fbem-2300	45	33	and	and	CCONJ
fbem-2300	45	34	to	to	PART
fbem-2300	45	35	buy	buy	VERB
fbem-2300	45	36	at	at	ADP
fbem-2300	45	37	the	the	DET
fbem-2300	45	38	low	low	ADJ
fbem-2300	45	39	point	point	NOUN
fbem-2300	45	40	of	of	ADP
fbem-2300	45	41	the	the	DET
fbem-2300	45	42	price	price	NOUN
fbem-2300	45	43	and	and	CCONJ
fbem-2300	45	44	sell	sell	VERB
fbem-2300	45	45	at	at	ADP
fbem-2300	45	46	the	the	DET
fbem-2300	45	47	high	high	ADJ
fbem-2300	45	48	point	point	NOUN
fbem-2300	45	49	to	to	PART
fbem-2300	45	50	realize	realize	VERB
fbem-2300	45	51	the	the	DET
fbem-2300	45	52	profit	profit	NOUN
fbem-2300	45	53	.	.	PUNCT
fbem-2300	46	1	the	the	DET
fbem-2300	46	2	data	datum	NOUN
fbem-2300	46	3	processing	processing	NOUN
fbem-2300	46	4	flow	flow	NOUN
fbem-2300	46	5	of	of	ADP
fbem-2300	46	6	this	this	DET
fbem-2300	46	7	paper	paper	NOUN
fbem-2300	46	8	is	be	AUX
fbem-2300	46	9	shown	show	VERB
fbem-2300	46	10	in	in	ADP
fbem-2300	46	11	figure	figure	NOUN
fbem-2300	46	12	2	2	NUM
fbem-2300	46	13	,	,	PUNCT
fbem-2300	46	14	which	which	PRON
fbem-2300	46	15	is	be	AUX
fbem-2300	46	16	mainly	mainly	ADV
fbem-2300	46	17	divided	divide	VERB
fbem-2300	46	18	into	into	ADP
fbem-2300	46	19	three	three	NUM
fbem-2300	46	20	parts	part	NOUN
fbem-2300	46	21	:	:	PUNCT
fbem-2300	46	22	data	datum	NOUN
fbem-2300	46	23	preprocessing	preprocessing	NOUN
fbem-2300	46	24	,	,	PUNCT
fbem-2300	46	25	model	model	NOUN
fbem-2300	46	26	calculation	calculation	NOUN
fbem-2300	46	27	and	and	CCONJ
fbem-2300	46	28	simulated	simulated	ADJ
fbem-2300	46	29	income	income	NOUN
fbem-2300	46	30	.	.	PUNCT
fbem-2300	47	1	what	what	PRON
fbem-2300	47	2	needs	need	VERB
fbem-2300	47	3	to	to	PART
fbem-2300	47	4	be	be	AUX
fbem-2300	47	5	noted	note	VERB
fbem-2300	47	6	here	here	ADV
fbem-2300	47	7	is	be	AUX
fbem-2300	47	8	that	that	SCONJ
fbem-2300	47	9	in	in	ADP
fbem-2300	47	10	the	the	DET
fbem-2300	47	11	data	data	NOUN
fbem-2300	47	12	preprocessing	preprocessing	NOUN
fbem-2300	47	13	stage	stage	NOUN
fbem-2300	47	14	,	,	PUNCT
fbem-2300	47	15	the	the	DET
fbem-2300	47	16	article	article	NOUN
fbem-2300	47	17	takes	take	VERB
fbem-2300	47	18	the	the	DET
fbem-2300	47	19	market	market	NOUN
fbem-2300	47	20	open	open	ADJ
fbem-2300	47	21	data	datum	NOUN
fbem-2300	47	22	source	source	NOUN
fbem-2300	47	23	-the	-the	DET
fbem-2300	47	24	price	price	NOUN
fbem-2300	47	25	and	and	CCONJ
fbem-2300	47	26	trading	trading	NOUN
fbem-2300	47	27	volume	volume	NOUN
fbem-2300	47	28	data	datum	NOUN
fbem-2300	47	29	of	of	ADP
fbem-2300	47	30	historical	historical	ADJ
fbem-2300	47	31	stock	stock	NOUN
fbem-2300	47	32	transactions	transaction	NOUN
fbem-2300	47	33	-as	-as	ADP
fbem-2300	47	34	the	the	DET
fbem-2300	47	35	original	original	ADJ
fbem-2300	47	36	input	input	NOUN
fbem-2300	47	37	,	,	PUNCT
fbem-2300	47	38	and	and	CCONJ
fbem-2300	47	39	obtains	obtain	VERB
fbem-2300	47	40	the	the	DET
fbem-2300	47	41	input	input	NOUN
fbem-2300	47	42	indicators	indicator	NOUN
fbem-2300	47	43	and	and	CCONJ
fbem-2300	47	44	output	output	NOUN
fbem-2300	47	45	indicators	indicator	NOUN
fbem-2300	47	46	of	of	ADP
fbem-2300	47	47	the	the	DET
fbem-2300	47	48	model	model	NOUN
fbem-2300	47	49	respectively	respectively	ADV
fbem-2300	47	50	.	.	PUNCT
fbem-2300	48	1	the	the	DET
fbem-2300	48	2	"	"	PUNCT
fbem-2300	48	3	future	future	ADJ
fbem-2300	48	4	"	"	PUNCT
fbem-2300	48	5	data	datum	NOUN
fbem-2300	48	6	is	be	AUX
fbem-2300	48	7	used	use	VERB
fbem-2300	48	8	in	in	ADP
fbem-2300	48	9	the	the	DET
fbem-2300	48	10	calculation	calculation	NOUN
fbem-2300	48	11	of	of	ADP
fbem-2300	48	12	output	output	NOUN
fbem-2300	48	13	indicators	indicator	NOUN
fbem-2300	48	14	,	,	PUNCT
fbem-2300	48	15	so	so	SCONJ
fbem-2300	48	16	it	it	PRON
fbem-2300	48	17	can	can	AUX
fbem-2300	48	18	be	be	AUX
fbem-2300	48	19	obtained	obtain	VERB
fbem-2300	48	20	in	in	ADP
fbem-2300	48	21	the	the	DET
fbem-2300	48	22	model	model	NOUN
fbem-2300	48	23	training	training	NOUN
fbem-2300	48	24	and	and	CCONJ
fbem-2300	48	25	optimization	optimization	NOUN
fbem-2300	48	26	stage	stage	NOUN
fbem-2300	48	27	,	,	PUNCT
fbem-2300	48	28	but	but	CCONJ
fbem-2300	48	29	in	in	ADP
fbem-2300	48	30	the	the	DET
fbem-2300	48	31	use	use	NOUN
fbem-2300	48	32	stage	stage	NOUN
fbem-2300	48	33	of	of	ADP
fbem-2300	48	34	the	the	DET
fbem-2300	48	35	model	model	NOUN
fbem-2300	48	36	,	,	PUNCT
fbem-2300	48	37	the	the	DET
fbem-2300	48	38	output	output	NOUN
fbem-2300	48	39	indicators	indicator	NOUN
fbem-2300	48	40	should	should	AUX
fbem-2300	48	41	be	be	AUX
fbem-2300	48	42	given	give	VERB
fbem-2300	48	43	by	by	ADP
fbem-2300	48	44	model	model	NOUN
fbem-2300	48	45	prediction	prediction	NOUN
fbem-2300	48	46	,	,	PUNCT
fbem-2300	48	47	as	as	SCONJ
fbem-2300	48	48	shown	show	VERB
fbem-2300	48	49	in	in	ADP
fbem-2300	48	50	figure	figure	NOUN
fbem-2300	48	51	2	2	NUM
fbem-2300	48	52	.	.	NOUN
fbem-2300	48	53	136	136	NUM
fbem-2300	48	54	figure	figure	NOUN
fbem-2300	48	55	2	2	NUM
fbem-2300	48	56	.	.	PUNCT
fbem-2300	48	57	quantification	quantification	NOUN
fbem-2300	48	58	based	base	VERB
fbem-2300	48	59	on	on	ADP
fbem-2300	48	60	historical	historical	ADJ
fbem-2300	48	61	data	datum	NOUN
fbem-2300	48	62	is	be	AUX
fbem-2300	48	63	the	the	DET
fbem-2300	48	64	strategy	strategy	NOUN
fbem-2300	48	65	research	research	NOUN
fbem-2300	48	66	framework	framework	NOUN
fbem-2300	48	67	in	in	ADP
fbem-2300	48	68	the	the	DET
fbem-2300	48	69	work	work	NOUN
fbem-2300	48	70	of	of	ADP
fbem-2300	48	71	the	the	DET
fbem-2300	48	72	paper	paper	NOUN
fbem-2300	48	73	,	,	PUNCT
fbem-2300	48	74	we	we	PRON
fbem-2300	48	75	use	use	VERB
fbem-2300	48	76	the	the	DET
fbem-2300	48	77	model	model	NOUN
fbem-2300	48	78	with	with	ADP
fbem-2300	48	79	artificial	artificial	ADJ
fbem-2300	48	80	features	feature	NOUN
fbem-2300	48	81	as	as	ADP
fbem-2300	48	82	input	input	NOUN
fbem-2300	48	83	,	,	PUNCT
fbem-2300	48	84	which	which	PRON
fbem-2300	48	85	has	have	VERB
fbem-2300	48	86	better	well	ADJ
fbem-2300	48	87	effect	effect	NOUN
fbem-2300	48	88	in	in	ADP
fbem-2300	48	89	the	the	DET
fbem-2300	48	90	case	case	NOUN
fbem-2300	48	91	of	of	ADP
fbem-2300	48	92	less	less	ADJ
fbem-2300	48	93	data	datum	NOUN
fbem-2300	48	94	.	.	PUNCT
fbem-2300	49	1	the	the	DET
fbem-2300	49	2	work	work	NOUN
fbem-2300	49	3	of	of	ADP
fbem-2300	49	4	this	this	DET
fbem-2300	49	5	paper	paper	NOUN
fbem-2300	49	6	explores	explore	VERB
fbem-2300	49	7	the	the	DET
fbem-2300	49	8	possibility	possibility	NOUN
fbem-2300	49	9	of	of	ADP
fbem-2300	49	10	combining	combine	VERB
fbem-2300	49	11	neural	neural	ADJ
fbem-2300	49	12	network	network	NOUN
fbem-2300	49	13	and	and	CCONJ
fbem-2300	49	14	machine	machine	NOUN
fbem-2300	49	15	learning	learn	VERB
fbem-2300	49	16	model	model	NOUN
fbem-2300	49	17	to	to	PART
fbem-2300	49	18	predict	predict	VERB
fbem-2300	49	19	the	the	DET
fbem-2300	49	20	stock	stock	NOUN
fbem-2300	49	21	market	market	NOUN
fbem-2300	49	22	and	and	CCONJ
fbem-2300	49	23	make	make	VERB
fbem-2300	49	24	profits	profit	NOUN
fbem-2300	49	25	from	from	ADP
fbem-2300	49	26	it	it	PRON
fbem-2300	49	27	with	with	ADP
fbem-2300	49	28	the	the	DET
fbem-2300	49	29	manually	manually	ADV
fbem-2300	49	30	extracted	extract	VERB
fbem-2300	49	31	features	feature	NOUN
fbem-2300	49	32	as	as	ADP
fbem-2300	49	33	input	input	NOUN
fbem-2300	49	34	.	.	PUNCT
fbem-2300	50	1	it	it	PRON
fbem-2300	50	2	is	be	AUX
fbem-2300	50	3	hoped	hope	VERB
fbem-2300	50	4	that	that	SCONJ
fbem-2300	50	5	the	the	DET
fbem-2300	50	6	process	process	NOUN
fbem-2300	50	7	of	of	ADP
fbem-2300	50	8	extracting	extract	VERB
fbem-2300	50	9	features	feature	NOUN
fbem-2300	50	10	using	use	VERB
fbem-2300	50	11	models	model	NOUN
fbem-2300	50	12	can	can	AUX
fbem-2300	50	13	be	be	AUX
fbem-2300	50	14	replaced	replace	VERB
fbem-2300	50	15	by	by	ADP
fbem-2300	50	16	manually	manually	ADV
fbem-2300	50	17	extracted	extract	VERB
fbem-2300	50	18	features	feature	NOUN
fbem-2300	50	19	,	,	PUNCT
fbem-2300	50	20	so	so	SCONJ
fbem-2300	50	21	as	as	SCONJ
fbem-2300	50	22	to	to	PART
fbem-2300	50	23	achieve	achieve	VERB
fbem-2300	50	24	better	well	ADJ
fbem-2300	50	25	prediction	prediction	NOUN
fbem-2300	50	26	results	result	NOUN
fbem-2300	50	27	using	use	VERB
fbem-2300	50	28	simpler	simple	ADJ
fbem-2300	50	29	neural	neural	ADJ
fbem-2300	50	30	networks	network	NOUN
fbem-2300	50	31	or	or	CCONJ
fbem-2300	50	32	machine	machine	NOUN
fbem-2300	50	33	learning	learning	NOUN
fbem-2300	50	34	models	model	NOUN
fbem-2300	50	35	.	.	PUNCT
fbem-2300	51	1	in	in	ADP
fbem-2300	51	2	order	order	NOUN
fbem-2300	51	3	to	to	PART
fbem-2300	51	4	obtain	obtain	VERB
fbem-2300	51	5	a	a	DET
fbem-2300	51	6	better	well	ADJ
fbem-2300	51	7	quantitative	quantitative	ADJ
fbem-2300	51	8	investment	investment	NOUN
fbem-2300	51	9	effect	effect	NOUN
fbem-2300	51	10	of	of	ADP
fbem-2300	51	11	large	large	ADJ
fbem-2300	51	12	-	-	PUNCT
fbem-2300	51	13	scale	scale	NOUN
fbem-2300	51	14	assets	asset	NOUN
fbem-2300	51	15	,	,	PUNCT
fbem-2300	51	16	this	this	DET
fbem-2300	51	17	paper	paper	NOUN
fbem-2300	51	18	systematically	systematically	ADV
fbem-2300	51	19	selects	select	VERB
fbem-2300	51	20	six	six	NUM
fbem-2300	51	21	machine	machine	NOUN
fbem-2300	51	22	learning	learning	NOUN
fbem-2300	51	23	models	model	NOUN
fbem-2300	51	24	with	with	ADP
fbem-2300	51	25	strong	strong	ADJ
fbem-2300	51	26	classification	classification	NOUN
fbem-2300	51	27	and	and	CCONJ
fbem-2300	51	28	prediction	prediction	NOUN
fbem-2300	51	29	ability	ability	NOUN
fbem-2300	51	30	to	to	PART
fbem-2300	51	31	predict	predict	VERB
fbem-2300	51	32	the	the	DET
fbem-2300	51	33	income	income	NOUN
fbem-2300	51	34	direction	direction	NOUN
fbem-2300	51	35	of	of	ADP
fbem-2300	51	36	largescale	largescale	ADJ
fbem-2300	51	37	assets	asset	NOUN
fbem-2300	51	38	,	,	PUNCT
fbem-2300	51	39	which	which	PRON
fbem-2300	51	40	plays	play	VERB
fbem-2300	51	41	a	a	DET
fbem-2300	51	42	role	role	NOUN
fbem-2300	51	43	in	in	ADP
fbem-2300	51	44	screening	screen	VERB
fbem-2300	51	45	superior	superior	ADJ
fbem-2300	51	46	assets	asset	NOUN
fbem-2300	51	47	to	to	PART
fbem-2300	51	48	assist	assist	VERB
fbem-2300	51	49	the	the	DET
fbem-2300	51	50	subsequent	subsequent	ADJ
fbem-2300	51	51	asset	asset	NOUN
fbem-2300	51	52	allocation	allocation	NOUN
fbem-2300	51	53	.	.	PUNCT
fbem-2300	52	1	the	the	DET
fbem-2300	52	2	six	six	NUM
fbem-2300	52	3	selected	select	VERB
fbem-2300	52	4	machine	machine	NOUN
fbem-2300	52	5	learning	learning	NOUN
fbem-2300	52	6	models	model	NOUN
fbem-2300	52	7	include	include	VERB
fbem-2300	52	8	support	support	NOUN
fbem-2300	52	9	vector	vector	NOUN
fbem-2300	52	10	machine	machine	NOUN
fbem-2300	52	11	,	,	PUNCT
fbem-2300	52	12	xgboost	xgboost	ADV
fbem-2300	52	13	,	,	PUNCT
fbem-2300	52	14	random	random	ADJ
fbem-2300	52	15	forest	forest	NOUN
fbem-2300	52	16	,	,	PUNCT
fbem-2300	52	17	gbdt	gbdt	PROPN
fbem-2300	52	18	,	,	PUNCT
fbem-2300	52	19	bp	bp	PROPN
fbem-2300	52	20	neural	neural	ADJ
fbem-2300	52	21	network	network	NOUN
fbem-2300	52	22	and	and	CCONJ
fbem-2300	52	23	lstm	lstm	NOUN
fbem-2300	52	24	.	.	PUNCT
fbem-2300	53	1	here	here	ADV
fbem-2300	53	2	,	,	PUNCT
fbem-2300	53	3	the	the	DET
fbem-2300	53	4	theoretical	theoretical	ADJ
fbem-2300	53	5	method	method	NOUN
fbem-2300	53	6	of	of	ADP
fbem-2300	53	7	one	one	NUM
fbem-2300	53	8	of	of	ADP
fbem-2300	53	9	the	the	DET
fbem-2300	53	10	models	model	NOUN
fbem-2300	53	11	,	,	PUNCT
fbem-2300	53	12	namely	namely	ADV
fbem-2300	53	13	bp	bp	PROPN
fbem-2300	53	14	neural	neural	ADJ
fbem-2300	53	15	model	model	NOUN
fbem-2300	53	16	,	,	PUNCT
fbem-2300	53	17	and	and	CCONJ
fbem-2300	53	18	the	the	DET
fbem-2300	53	19	basic	basic	ADJ
fbem-2300	53	20	idea	idea	NOUN
fbem-2300	53	21	of	of	ADP
fbem-2300	53	22	its	its	PRON
fbem-2300	53	23	classification	classification	NOUN
fbem-2300	53	24	algorithm	algorithm	NOUN
fbem-2300	53	25	are	be	AUX
fbem-2300	53	26	introduced	introduce	VERB
fbem-2300	53	27	.	.	PUNCT
fbem-2300	54	1	3.2	3.2	NUM
fbem-2300	54	2	.	.	PUNCT
fbem-2300	55	1	use	use	VERB
fbem-2300	55	2	bp	bp	PROPN
fbem-2300	55	3	algorithm	algorithm	NOUN
fbem-2300	55	4	for	for	ADP
fbem-2300	55	5	stock	stock	NOUN
fbem-2300	55	6	selection	selection	NOUN
fbem-2300	55	7	the	the	DET
fbem-2300	55	8	learning	learning	NOUN
fbem-2300	55	9	ability	ability	NOUN
fbem-2300	55	10	of	of	ADP
fbem-2300	55	11	multi	multi	ADJ
fbem-2300	55	12	-	-	ADJ
fbem-2300	55	13	layer	layer	ADJ
fbem-2300	55	14	neural	neural	ADJ
fbem-2300	55	15	network	network	NOUN
fbem-2300	55	16	is	be	AUX
fbem-2300	55	17	far	far	ADV
fbem-2300	55	18	stronger	strong	ADJ
fbem-2300	55	19	than	than	ADP
fbem-2300	55	20	that	that	PRON
fbem-2300	55	21	of	of	ADP
fbem-2300	55	22	single	single	ADJ
fbem-2300	55	23	-	-	PUNCT
fbem-2300	55	24	layer	layer	NOUN
fbem-2300	55	25	neural	neural	ADJ
fbem-2300	55	26	network	network	NOUN
fbem-2300	55	27	,	,	PUNCT
fbem-2300	55	28	and	and	CCONJ
fbem-2300	55	29	it	it	PRON
fbem-2300	55	30	trains	train	VERB
fbem-2300	55	31	multi	multi	ADJ
fbem-2300	55	32	-	-	ADJ
fbem-2300	55	33	layer	layer	ADJ
fbem-2300	55	34	neural	neural	ADJ
fbem-2300	55	35	network	network	NOUN
fbem-2300	55	36	through	through	ADP
fbem-2300	55	37	more	more	ADV
fbem-2300	55	38	powerful	powerful	ADJ
fbem-2300	55	39	algorithms	algorithm	NOUN
fbem-2300	55	40	.	.	PUNCT
fbem-2300	56	1	the	the	DET
fbem-2300	56	2	bp	bp	PROPN
fbem-2300	56	3	neural	neural	PROPN
fbem-2300	56	4	network	network	NOUN
fbem-2300	56	5	model	model	NOUN
fbem-2300	56	6	used	use	VERB
fbem-2300	56	7	in	in	ADP
fbem-2300	56	8	this	this	DET
fbem-2300	56	9	paper	paper	NOUN
fbem-2300	56	10	is	be	AUX
fbem-2300	56	11	a	a	DET
fbem-2300	56	12	neural	neural	ADJ
fbem-2300	56	13	network	network	NOUN
fbem-2300	56	14	model	model	NOUN
fbem-2300	56	15	based	base	VERB
fbem-2300	56	16	on	on	ADP
fbem-2300	56	17	error	error	NOUN
fbem-2300	56	18	back	back	NOUN
fbem-2300	56	19	propagation	propagation	NOUN
fbem-2300	56	20	algorithm	algorithm	NOUN
fbem-2300	56	21	(	(	PUNCT
fbem-2300	56	22	abbreviated	abbreviate	VERB
fbem-2300	56	23	as	as	ADP
fbem-2300	56	24	bp	bp	PROPN
fbem-2300	56	25	algorithm	algorithm	PROPN
fbem-2300	56	26	)	)	PUNCT
fbem-2300	56	27	.	.	PUNCT
fbem-2300	57	1	bp	bp	PROPN
fbem-2300	57	2	algorithm	algorithm	PROPN
fbem-2300	57	3	is	be	AUX
fbem-2300	57	4	a	a	DET
fbem-2300	57	5	widely	widely	ADV
fbem-2300	57	6	used	use	VERB
fbem-2300	57	7	neural	neural	ADJ
fbem-2300	57	8	network	network	NOUN
fbem-2300	57	9	algorithm	algorithm	NOUN
fbem-2300	57	10	,	,	PUNCT
fbem-2300	57	11	which	which	PRON
fbem-2300	57	12	can	can	AUX
fbem-2300	57	13	be	be	AUX
fbem-2300	57	14	used	use	VERB
fbem-2300	57	15	to	to	PART
fbem-2300	57	16	train	train	VERB
fbem-2300	57	17	not	not	PART
fbem-2300	57	18	only	only	ADV
fbem-2300	57	19	multilayer	multilayer	ADJ
fbem-2300	57	20	feedforward	feedforward	NOUN
fbem-2300	57	21	neural	neural	ADJ
fbem-2300	57	22	networks	network	NOUN
fbem-2300	57	23	,	,	PUNCT
fbem-2300	57	24	but	but	CCONJ
fbem-2300	57	25	also	also	ADV
fbem-2300	57	26	other	other	ADJ
fbem-2300	57	27	neural	neural	ADJ
fbem-2300	57	28	networks	network	NOUN
fbem-2300	57	29	.	.	PUNCT
fbem-2300	58	1	the	the	DET
fbem-2300	58	2	specific	specific	ADJ
fbem-2300	58	3	bp	bp	PROPN
fbem-2300	58	4	algorithm	algorithm	NOUN
fbem-2300	58	5	workflow	workflow	NOUN
fbem-2300	58	6	is	be	AUX
fbem-2300	58	7	as	as	SCONJ
fbem-2300	58	8	follows	follow	VERB
fbem-2300	58	9	:	:	PUNCT
fbem-2300	58	10	(	(	PUNCT
fbem-2300	58	11	1	1	X
fbem-2300	58	12	)	)	PUNCT
fbem-2300	58	13	input	input	NOUN
fbem-2300	58	14	training	training	NOUN
fbem-2300	58	15	set	set	VERB
fbem-2300	58	16			NOUN
fbem-2300	58	17			ADJ
fbem-2300	58	18	m	m	PROPN
fbem-2300	58	19	kkk	kkk	NOUN
fbem-2300	58	20	yxd	yxd	NOUN
fbem-2300	58	21	1	1	NUM
fbem-2300	58	22	,	,	PUNCT
fbem-2300	58	23			PROPN
fbem-2300	58	24	and	and	CCONJ
fbem-2300	58	25	determine	determine	VERB
fbem-2300	58	26	learning	learn	VERB
fbem-2300	58	27	rate	rate	PRON
fbem-2300	58	28	.	.	PUNCT
fbem-2300	59	1	(	(	PUNCT
fbem-2300	59	2	2	2	X
fbem-2300	59	3	)	)	PUNCT
fbem-2300	59	4	according	accord	VERB
fbem-2300	59	5	to	to	ADP
fbem-2300	59	6	the	the	DET
fbem-2300	59	7	input	input	NOUN
fbem-2300	59	8	training	training	NOUN
fbem-2300	59	9	set	set	NOUN
fbem-2300	59	10	and	and	CCONJ
fbem-2300	59	11	learning	learning	NOUN
fbem-2300	59	12	rate	rate	NOUN
fbem-2300	59	13	,	,	PUNCT
fbem-2300	59	14	randomly	randomly	ADV
fbem-2300	59	15	initialize	initialize	VERB
fbem-2300	59	16	the	the	DET
fbem-2300	59	17	connection	connection	NOUN
fbem-2300	59	18	and	and	CCONJ
fbem-2300	59	19	threshold	threshold	NOUN
fbem-2300	59	20	of	of	ADP
fbem-2300	59	21	the	the	DET
fbem-2300	59	22	neural	neural	ADJ
fbem-2300	59	23	network	network	NOUN
fbem-2300	59	24	between	between	ADP
fbem-2300	59	25	(	(	PUNCT
fbem-2300	59	26	0,1	0,1	NUM
fbem-2300	59	27	)	)	PUNCT
fbem-2300	59	28	(	(	PUNCT
fbem-2300	59	29	3	3	X
fbem-2300	59	30	)	)	PUNCT
fbem-2300	59	31	according	accord	VERB
fbem-2300	59	32	to	to	ADP
fbem-2300	59	33	the	the	DET
fbem-2300	59	34	set	set	NOUN
fbem-2300	59	35	parameters	parameter	NOUN
fbem-2300	59	36	and	and	CCONJ
fbem-2300	59	37	formula	formula	VERB
fbem-2300	59	38			PROPN
fbem-2300	59	39	jjkj	jjkj	PROPN
fbem-2300	59	40	fy	fy	PROPN
fbem-2300	59	41			PROPN
fbem-2300	59	42	ˆ	ˆ	PROPN
fbem-2300	59	43	,	,	PUNCT
fbem-2300	59	44	the	the	DET
fbem-2300	59	45	output	output	NOUN
fbem-2300	59	46	value	value	NOUN
fbem-2300	59	47	kjŷ	kjŷ	PROPN
fbem-2300	59	48	of	of	ADP
fbem-2300	59	49	the	the	DET
fbem-2300	59	50	training	training	NOUN
fbem-2300	59	51	sample	sample	NOUN
fbem-2300	59	52	is	be	AUX
fbem-2300	59	53	obtained	obtain	VERB
fbem-2300	59	54	.	.	PUNCT
fbem-2300	60	1	(	(	PUNCT
fbem-2300	60	2	4	4	NUM
fbem-2300	60	3	)	)	PUNCT
fbem-2300	60	4	according	accord	VERB
fbem-2300	60	5	to	to	ADP
fbem-2300	60	6	the	the	DET
fbem-2300	60	7	formula	formula	NOUN
fbem-2300	60	8			NOUN
fbem-2300	60	9			NOUN
fbem-2300	61	1	kjkjkjkjj	kjkjkjkjj	PRON
fbem-2300	61	2	yyyyg	yyyyg	NOUN
fbem-2300	61	3			PUNCT
fbem-2300	61	4	1ˆ	1ˆ	NOUN
fbem-2300	61	5	,	,	PUNCT
fbem-2300	61	6	the	the	DET
fbem-2300	61	7	gradient	gradient	ADJ
fbem-2300	61	8	term	term	NOUN
fbem-2300	61	9	jg	jg	PROPN
fbem-2300	61	10	of	of	ADP
fbem-2300	61	11	the	the	DET
fbem-2300	61	12	output	output	NOUN
fbem-2300	61	13	neuron	neuron	NOUN
fbem-2300	61	14	is	be	AUX
fbem-2300	61	15	obtained	obtain	VERB
fbem-2300	61	16	.	.	PUNCT
fbem-2300	62	1	(	(	PUNCT
fbem-2300	62	2	5	5	NUM
fbem-2300	62	3	)	)	PUNCT
fbem-2300	62	4	according	accord	VERB
fbem-2300	62	5	to	to	ADP
fbem-2300	62	6	the	the	DET
fbem-2300	62	7	formula	formula	NOUN
fbem-2300	62	8	hh	hh	VERB
fbem-2300	62	9	e	e	NOUN
fbem-2300	62	10			PROPN
fbem-2300	62	11	,	,	PUNCT
fbem-2300	62	12	the	the	DET
fbem-2300	62	13	gradient	gradient	ADJ
fbem-2300	62	14	term	term	NOUN
fbem-2300	62	15	he	he	PRON
fbem-2300	62	16	of	of	ADP
fbem-2300	62	17	hidden	hide	VERB
fbem-2300	62	18	neurons	neuron	NOUN
fbem-2300	62	19	is	be	AUX
fbem-2300	62	20	obtained	obtain	VERB
fbem-2300	62	21	(	(	PUNCT
fbem-2300	62	22	6	6	NUM
fbem-2300	62	23	)	)	PUNCT
fbem-2300	62	24	according	accord	VERB
fbem-2300	62	25	to	to	ADP
fbem-2300	62	26	the	the	DET
fbem-2300	62	27	updated	update	VERB
fbem-2300	62	28	formula	formula	NOUN
fbem-2300	62	29	hjhj	hjhj	VERB
fbem-2300	62	30	bg	bg	ADJ
fbem-2300	62	31			NOUN
fbem-2300	62	32	,	,	PUNCT
fbem-2300	62	33	1i	1i	NUM
fbem-2300	62	34	,	,	PUNCT
fbem-2300	62	35	ihih	ihih	PROPN
fbem-2300	62	36	xev	xev	PROPN
fbem-2300	62	37			PROPN
fbem-2300	62	38	,	,	PUNCT
fbem-2300	62	39	he	he	PROPN
fbem-2300	62	40			PROPN
fbem-2300	62	41	,	,	PUNCT
fbem-2300	62	42	get	get	VERB
fbem-2300	62	43	the	the	DET
fbem-2300	62	44	updated	update	VERB
fbem-2300	62	45	connection	connection	NOUN
fbem-2300	62	46	weights	weight	VERB
fbem-2300	62	47	hj	hj	PROPN
fbem-2300	62	48	and	and	CCONJ
fbem-2300	62	49	ihv	ihv	VERB
fbem-2300	62	50	,	,	PUNCT
fbem-2300	62	51	and	and	CCONJ
fbem-2300	62	52	the	the	DET
fbem-2300	62	53	thresholds	threshold	NOUN
fbem-2300	62	54	j	j	PROPN
fbem-2300	62	55	and	and	CCONJ
fbem-2300	62	56	h	h	PROPN
fbem-2300	62	57	.	.	PUNCT
fbem-2300	63	1	(	(	PUNCT
fbem-2300	63	2	7	7	NUM
fbem-2300	63	3	)	)	PUNCT
fbem-2300	63	4	from	from	ADP
fbem-2300	63	5	this	this	DET
fbem-2300	63	6	cycle	cycle	NOUN
fbem-2300	63	7	,	,	PUNCT
fbem-2300	63	8	the	the	DET
fbem-2300	63	9	stopping	stop	VERB
fbem-2300	63	10	condition	condition	NOUN
fbem-2300	63	11	of	of	ADP
fbem-2300	63	12	the	the	DET
fbem-2300	63	13	neural	neural	ADJ
fbem-2300	63	14	network	network	NOUN
fbem-2300	63	15	is	be	AUX
fbem-2300	63	16	guided	guide	VERB
fbem-2300	63	17	,	,	PUNCT
fbem-2300	63	18	and	and	CCONJ
fbem-2300	63	19	finally	finally	ADV
fbem-2300	63	20	the	the	DET
fbem-2300	63	21	neural	neural	ADJ
fbem-2300	63	22	network	network	NOUN
fbem-2300	63	23	whose	whose	DET
fbem-2300	63	24	connection	connection	NOUN
fbem-2300	63	25	weight	weight	NOUN
fbem-2300	63	26	and	and	CCONJ
fbem-2300	63	27	threshold	threshold	NOUN
fbem-2300	63	28	are	be	AUX
fbem-2300	63	29	determined	determine	VERB
fbem-2300	63	30	is	be	AUX
fbem-2300	63	31	output	output	NOUN
fbem-2300	63	32	.	.	PUNCT
fbem-2300	64	1	in	in	ADP
fbem-2300	64	2	this	this	DET
fbem-2300	64	3	paper	paper	NOUN
fbem-2300	64	4	,	,	PUNCT
fbem-2300	64	5	the	the	DET
fbem-2300	64	6	financial	financial	ADJ
fbem-2300	64	7	statements	statement	NOUN
fbem-2300	64	8	of	of	ADP
fbem-2300	64	9	3000	3000	NUM
fbem-2300	64	10	chinese	chinese	ADJ
fbem-2300	64	11	medicine	medicine	NOUN
fbem-2300	64	12	listed	list	VERB
fbem-2300	64	13	companies	company	NOUN
fbem-2300	64	14	in	in	ADP
fbem-2300	64	15	a	a	DET
fbem-2300	64	16	stock	stock	NOUN
fbem-2300	64	17	market	market	NOUN
fbem-2300	64	18	from	from	ADP
fbem-2300	64	19	2017	2017	NUM
fbem-2300	64	20	to	to	ADP
fbem-2300	64	21	2021	2021	NUM
fbem-2300	64	22	are	be	AUX
fbem-2300	64	23	selected	select	VERB
fbem-2300	64	24	as	as	ADP
fbem-2300	64	25	samples	sample	NOUN
fbem-2300	64	26	.	.	PUNCT
fbem-2300	65	1	the	the	DET
fbem-2300	65	2	establishment	establishment	NOUN
fbem-2300	65	3	of	of	ADP
fbem-2300	65	4	stock	stock	NOUN
fbem-2300	65	5	selection	selection	NOUN
fbem-2300	65	6	model	model	NOUN
fbem-2300	65	7	consists	consist	VERB
fbem-2300	65	8	of	of	ADP
fbem-2300	65	9	two	two	NUM
fbem-2300	65	10	parts	part	NOUN
fbem-2300	65	11	:	:	PUNCT
fbem-2300	65	12	training	train	VERB
fbem-2300	65	13	samples	sample	NOUN
fbem-2300	65	14	and	and	CCONJ
fbem-2300	65	15	testing	testing	NOUN
fbem-2300	65	16	samples	sample	NOUN
fbem-2300	65	17	.	.	PUNCT
fbem-2300	66	1	to	to	PART
fbem-2300	66	2	determine	determine	VERB
fbem-2300	66	3	the	the	DET
fbem-2300	66	4	sample	sample	NOUN
fbem-2300	66	5	first	first	ADV
fbem-2300	66	6	,	,	PUNCT
fbem-2300	66	7	this	this	DET
fbem-2300	66	8	paper	paper	NOUN
fbem-2300	66	9	starts	start	VERB
fbem-2300	66	10	from	from	ADP
fbem-2300	66	11	700	700	NUM
fbem-2300	66	12	stocks	stock	NOUN
fbem-2300	66	13	from	from	ADP
fbem-2300	66	14	230	230	NUM
fbem-2300	66	15	stocks	stock	NOUN
fbem-2300	66	16	were	be	AUX
fbem-2300	66	17	selected	select	VERB
fbem-2300	66	18	as	as	ADP
fbem-2300	66	19	samples	sample	NOUN
fbem-2300	66	20	for	for	ADP
fbem-2300	66	21	training	training	NOUN
fbem-2300	66	22	test	test	NOUN
fbem-2300	66	23	.	.	PUNCT
fbem-2300	67	1	according	accord	VERB
fbem-2300	67	2	to	to	ADP
fbem-2300	67	3	the	the	DET
fbem-2300	67	4	following	follow	VERB
fbem-2300	67	5	criteria	criterion	NOUN
fbem-2300	67	6	,	,	PUNCT
fbem-2300	67	7	it	it	PRON
fbem-2300	67	8	is	be	AUX
fbem-2300	67	9	classified	classify	VERB
fbem-2300	67	10	as	as	ADP
fbem-2300	67	11	good	good	ADJ
fbem-2300	67	12	company	company	NOUN
fbem-2300	67	13	and	and	CCONJ
fbem-2300	67	14	bad	bad	ADJ
fbem-2300	67	15	company	company	NOUN
fbem-2300	67	16	:	:	PUNCT
fbem-2300	67	17	companies	company	NOUN
fbem-2300	67	18	with	with	ADP
fbem-2300	67	19	negative	negative	ADJ
fbem-2300	67	20	net	net	ADJ
fbem-2300	67	21	profit	profit	NOUN
fbem-2300	67	22	,	,	PUNCT
fbem-2300	67	23	negative	negative	ADJ
fbem-2300	67	24	main	main	ADJ
fbem-2300	67	25	business	business	NOUN
fbem-2300	67	26	income	income	NOUN
fbem-2300	67	27	and	and	CCONJ
fbem-2300	67	28	negative	negative	ADJ
fbem-2300	67	29	net	net	ADJ
fbem-2300	67	30	profit	profit	NOUN
fbem-2300	67	31	can	can	AUX
fbem-2300	67	32	be	be	AUX
fbem-2300	67	33	judged	judge	VERB
fbem-2300	67	34	as	as	ADP
fbem-2300	67	35	bad	bad	ADJ
fbem-2300	67	36	companies	company	NOUN
fbem-2300	67	37	.	.	PUNCT
fbem-2300	68	1	after	after	ADP
fbem-2300	68	2	a	a	DET
fbem-2300	68	3	series	series	NOUN
fbem-2300	68	4	of	of	ADP
fbem-2300	68	5	tests	test	NOUN
fbem-2300	68	6	,	,	PUNCT
fbem-2300	68	7	the	the	DET
fbem-2300	68	8	parameters	parameter	NOUN
fbem-2300	68	9	of	of	ADP
fbem-2300	68	10	the	the	DET
fbem-2300	68	11	bp	bp	PROPN
fbem-2300	68	12	neural	neural	PROPN
fbem-2300	68	13	network	network	PROPN
fbem-2300	68	14	stock	stock	NOUN
fbem-2300	68	15	selection	selection	NOUN
fbem-2300	68	16	model	model	NOUN
fbem-2300	68	17	are	be	AUX
fbem-2300	68	18	20	20	NUM
fbem-2300	68	19	neurons	neuron	NOUN
fbem-2300	68	20	in	in	ADP
fbem-2300	68	21	the	the	DET
fbem-2300	68	22	hidden	hide	VERB
fbem-2300	68	23	layer	layer	NOUN
fbem-2300	68	24	,	,	PUNCT
fbem-2300	68	25	the	the	DET
fbem-2300	68	26	threshold	threshold	NOUN
fbem-2300	68	27	is	be	AUX
fbem-2300	68	28	0.005	0.005	NUM
fbem-2300	68	29	,	,	PUNCT
fbem-2300	68	30	and	and	CCONJ
fbem-2300	68	31	the	the	DET
fbem-2300	68	32	learning	learning	NOUN
fbem-2300	68	33	rate	rate	NOUN
fbem-2300	68	34	is	be	AUX
fbem-2300	68	35	0.1	0.1	NUM
fbem-2300	68	36	.	.	PUNCT
fbem-2300	69	1	through	through	ADP
fbem-2300	69	2	bp	bp	PROPN
fbem-2300	69	3	neural	neural	ADJ
fbem-2300	69	4	network	network	NOUN
fbem-2300	69	5	,	,	PUNCT
fbem-2300	69	6	we	we	PRON
fbem-2300	69	7	can	can	AUX
fbem-2300	69	8	find	find	VERB
fbem-2300	69	9	out	out	ADP
fbem-2300	69	10	those	those	DET
fbem-2300	69	11	companies	company	NOUN
fbem-2300	69	12	with	with	ADP
fbem-2300	69	13	excellent	excellent	ADJ
fbem-2300	69	14	performance	performance	NOUN
fbem-2300	69	15	and	and	CCONJ
fbem-2300	69	16	good	good	ADJ
fbem-2300	69	17	growth	growth	NOUN
fbem-2300	69	18	in	in	ADP
fbem-2300	69	19	listed	list	VERB
fbem-2300	69	20	companies	company	NOUN
fbem-2300	69	21	and	and	CCONJ
fbem-2300	69	22	make	make	VERB
fbem-2300	69	23	quantitative	quantitative	ADJ
fbem-2300	69	24	investment	investment	NOUN
fbem-2300	69	25	.	.	PUNCT
fbem-2300	70	1	considering	consider	VERB
fbem-2300	70	2	the	the	DET
fbem-2300	70	3	factors	factor	NOUN
fbem-2300	70	4	of	of	ADP
fbem-2300	70	5	the	the	DET
fbem-2300	70	6	company	company	NOUN
fbem-2300	70	7	's	's	PART
fbem-2300	70	8	growth	growth	NOUN
fbem-2300	70	9	,	,	PUNCT
fbem-2300	70	10	bp	bp	PROPN
fbem-2300	70	11	neural	neural	ADJ
fbem-2300	70	12	network	network	NOUN
fbem-2300	70	13	is	be	AUX
fbem-2300	70	14	used	use	VERB
fbem-2300	70	15	to	to	PART
fbem-2300	70	16	establish	establish	VERB
fbem-2300	70	17	the	the	DET
fbem-2300	70	18	stock	stock	NOUN
fbem-2300	70	19	selection	selection	NOUN
fbem-2300	70	20	model	model	NOUN
fbem-2300	70	21	,	,	PUNCT
fbem-2300	70	22	and	and	CCONJ
fbem-2300	70	23	these	these	DET
fbem-2300	70	24	indexes	index	NOUN
fbem-2300	70	25	are	be	AUX
fbem-2300	70	26	trained	train	VERB
fbem-2300	70	27	and	and	CCONJ
fbem-2300	70	28	studied	study	VERB
fbem-2300	70	29	by	by	ADP
fbem-2300	70	30	bp	bp	PROPN
fbem-2300	70	31	neural	neural	ADJ
fbem-2300	70	32	network	network	NOUN
fbem-2300	70	33	,	,	PUNCT
fbem-2300	70	34	so	so	SCONJ
fbem-2300	70	35	as	as	SCONJ
fbem-2300	70	36	to	to	PART
fbem-2300	70	37	obtain	obtain	VERB
fbem-2300	70	38	a	a	DET
fbem-2300	70	39	stock	stock	NOUN
fbem-2300	70	40	value	value	NOUN
fbem-2300	70	41	feature	feature	NOUN
fbem-2300	70	42	set	set	VERB
fbem-2300	70	43	based	base	VERB
fbem-2300	70	44	on	on	ADP
fbem-2300	70	45	value	value	NOUN
fbem-2300	70	46	investment	investment	NOUN
fbem-2300	70	47	.	.	PUNCT
fbem-2300	71	1	through	through	ADP
fbem-2300	71	2	repeated	repeat	VERB
fbem-2300	71	3	training	training	NOUN
fbem-2300	71	4	and	and	CCONJ
fbem-2300	71	5	testing	testing	NOUN
fbem-2300	71	6	by	by	ADP
fbem-2300	71	7	cross	cross	NOUN
fbem-2300	71	8	-	-	NOUN
fbem-2300	71	9	validation	validation	ADJ
fbem-2300	71	10	,	,	PUNCT
fbem-2300	71	11	656	656	NUM
fbem-2300	71	12	stocks	stock	NOUN
fbem-2300	71	13	with	with	ADP
fbem-2300	71	14	investment	investment	NOUN
fbem-2300	71	15	value	value	NOUN
fbem-2300	71	16	are	be	AUX
fbem-2300	71	17	finally	finally	ADV
fbem-2300	71	18	selected	select	VERB
fbem-2300	71	19	.	.	PUNCT
fbem-2300	72	1	it	it	PRON
fbem-2300	72	2	can	can	AUX
fbem-2300	72	3	be	be	AUX
fbem-2300	72	4	seen	see	VERB
fbem-2300	72	5	that	that	SCONJ
fbem-2300	72	6	it	it	PRON
fbem-2300	72	7	is	be	AUX
fbem-2300	72	8	a	a	DET
fbem-2300	72	9	very	very	ADV
fbem-2300	72	10	prescient	prescient	ADJ
fbem-2300	72	11	and	and	CCONJ
fbem-2300	72	12	useful	useful	ADJ
fbem-2300	72	13	method	method	NOUN
fbem-2300	72	14	to	to	PART
fbem-2300	72	15	select	select	VERB
fbem-2300	72	16	stocks	stock	NOUN
fbem-2300	72	17	and	and	CCONJ
fbem-2300	72	18	invest	invest	VERB
fbem-2300	72	19	through	through	ADP
fbem-2300	72	20	bp	bp	PROPN
fbem-2300	72	21	neural	neural	ADJ
fbem-2300	72	22	network	network	NOUN
fbem-2300	72	23	.	.	PUNCT
fbem-2300	73	1	4	4	X
fbem-2300	73	2	.	.	X
fbem-2300	73	3	conclusion	conclusion	NOUN
fbem-2300	73	4	as	as	ADP
fbem-2300	73	5	a	a	DET
fbem-2300	73	6	computer	computer	NOUN
fbem-2300	73	7	language	language	NOUN
fbem-2300	73	8	,	,	PUNCT
fbem-2300	73	9	the	the	DET
fbem-2300	73	10	thinking	think	VERB
fbem-2300	73	11	mode	mode	NOUN
fbem-2300	73	12	of	of	ADP
fbem-2300	73	13	machine	machine	NOUN
fbem-2300	73	14	learning	learn	VERB
fbem-2300	73	15	algorithm	algorithm	NOUN
fbem-2300	73	16	is	be	AUX
fbem-2300	73	17	still	still	ADV
fbem-2300	73	18	fixed	fix	VERB
fbem-2300	73	19	and	and	CCONJ
fbem-2300	73	20	inflexible	inflexible	ADJ
fbem-2300	73	21	,	,	PUNCT
fbem-2300	73	22	and	and	CCONJ
fbem-2300	73	23	the	the	DET
fbem-2300	73	24	changes	change	NOUN
fbem-2300	73	25	brought	bring	VERB
fbem-2300	73	26	by	by	ADP
fbem-2300	73	27	unexpected	unexpected	ADJ
fbem-2300	73	28	events	event	NOUN
fbem-2300	73	29	in	in	ADP
fbem-2300	73	30	the	the	DET
fbem-2300	73	31	real	real	ADJ
fbem-2300	73	32	world	world	NOUN
fbem-2300	73	33	are	be	AUX
fbem-2300	73	34	still	still	ADV
fbem-2300	73	35	unpredictable	unpredictable	ADJ
fbem-2300	73	36	by	by	ADP
fbem-2300	73	37	computers	computer	NOUN
fbem-2300	73	38	.	.	PUNCT
fbem-2300	74	1	in	in	ADP
fbem-2300	74	2	the	the	DET
fbem-2300	74	3	future	future	NOUN
fbem-2300	74	4	,	,	PUNCT
fbem-2300	74	5	we	we	PRON
fbem-2300	74	6	need	need	VERB
fbem-2300	74	7	to	to	PART
fbem-2300	74	8	invest	invest	VERB
fbem-2300	74	9	more	more	ADJ
fbem-2300	74	10	efforts	effort	NOUN
fbem-2300	74	11	and	and	CCONJ
fbem-2300	74	12	energy	energy	NOUN
fbem-2300	74	13	to	to	PART
fbem-2300	74	14	contribute	contribute	VERB
fbem-2300	74	15	our	our	PRON
fbem-2300	74	16	own	own	ADJ
fbem-2300	74	17	strength	strength	NOUN
fbem-2300	74	18	to	to	ADP
fbem-2300	74	19	the	the	DET
fbem-2300	74	20	research	research	NOUN
fbem-2300	74	21	of	of	ADP
fbem-2300	74	22	quantitative	quantitative	ADJ
fbem-2300	74	23	investment	investment	NOUN
fbem-2300	74	24	.	.	PUNCT
fbem-2300	75	1	this	this	DET
fbem-2300	75	2	paper	paper	NOUN
fbem-2300	75	3	shows	show	VERB
fbem-2300	75	4	you	you	PRON
fbem-2300	75	5	the	the	DET
fbem-2300	75	6	research	research	NOUN
fbem-2300	75	7	on	on	ADP
fbem-2300	75	8	quantitative	quantitative	ADJ
fbem-2300	75	9	investment	investment	NOUN
fbem-2300	75	10	strategy	strategy	NOUN
fbem-2300	75	11	of	of	ADP
fbem-2300	75	12	ashare	ashare	NOUN
fbem-2300	75	13	market	market	NOUN
fbem-2300	75	14	based	base	VERB
fbem-2300	75	15	on	on	ADP
fbem-2300	75	16	machine	machine	NOUN
fbem-2300	75	17	learning	learning	NOUN
fbem-2300	75	18	,	,	PUNCT
fbem-2300	75	19	especially	especially	ADV
fbem-2300	75	20	the	the	DET
fbem-2300	75	21	model	model	NOUN
fbem-2300	75	22	137	137	NUM
fbem-2300	75	23	built	build	VERB
fbem-2300	75	24	by	by	ADP
fbem-2300	75	25	bp	bp	PROPN
fbem-2300	75	26	neural	neural	ADJ
fbem-2300	75	27	network	network	NOUN
fbem-2300	75	28	.	.	PUNCT
fbem-2300	76	1	the	the	DET
fbem-2300	76	2	experiment	experiment	NOUN
fbem-2300	76	3	proves	prove	VERB
fbem-2300	76	4	that	that	SCONJ
fbem-2300	76	5	it	it	PRON
fbem-2300	76	6	is	be	AUX
fbem-2300	76	7	a	a	DET
fbem-2300	76	8	very	very	ADV
fbem-2300	76	9	prescient	prescient	ADJ
fbem-2300	76	10	and	and	CCONJ
fbem-2300	76	11	useful	useful	ADJ
fbem-2300	76	12	method	method	NOUN
fbem-2300	76	13	to	to	PART
fbem-2300	76	14	select	select	VERB
fbem-2300	76	15	stocks	stock	NOUN
fbem-2300	76	16	and	and	CCONJ
fbem-2300	76	17	invest	invest	VERB
fbem-2300	76	18	by	by	ADP
fbem-2300	76	19	bp	bp	PROPN
fbem-2300	76	20	neural	neural	ADJ
fbem-2300	76	21	network	network	NOUN
fbem-2300	76	22	.	.	PUNCT
fbem-2300	77	1	references	reference	NOUN
fbem-2300	77	2	[	[	X
fbem-2300	77	3	1	1	X
fbem-2300	77	4	]	]	X
fbem-2300	77	5	huang	huang	PROPN
fbem-2300	77	6	qing	qing	PROPN
fbem-2300	77	7	research	research	NOUN
fbem-2300	77	8	on	on	ADP
fbem-2300	77	9	the	the	DET
fbem-2300	77	10	application	application	NOUN
fbem-2300	77	11	of	of	ADP
fbem-2300	77	12	support	support	NOUN
fbem-2300	77	13	vector	vector	NOUN
fbem-2300	77	14	machine	machine	NOUN
fbem-2300	77	15	in	in	ADP
fbem-2300	77	16	china	china	PROPN
fbem-2300	77	17	's	's	PART
fbem-2300	77	18	a	a	DET
fbem-2300	77	19	-	-	PUNCT
fbem-2300	77	20	share	share	NOUN
fbem-2300	77	21	market	market	NOUN
fbem-2300	77	22	quantification	quantification	NOUN
fbem-2300	77	23	strategy	strategy	NOUN
fbem-2300	77	24	-	-	PUNCT
fbem-2300	77	25	based	base	VERB
fbem-2300	77	26	on	on	ADP
fbem-2300	77	27	fama	fama	PROPN
fbem-2300	77	28	french	french	ADJ
fbem-2300	77	29	three	three	NUM
fbem-2300	77	30	factor	factor	NOUN
fbem-2300	77	31	model	model	NOUN
fbem-2300	77	32	[	[	X
fbem-2300	77	33	j	j	X
fbem-2300	77	34	]	]	X
fbem-2300	77	35	times	times	PROPN
fbem-2300	77	36	finance	finance	NOUN
fbem-2300	77	37	,	,	PUNCT
fbem-2300	77	38	2017	2017	NUM
fbem-2300	77	39	(	(	PUNCT
fbem-2300	77	40	11	11	NUM
fbem-2300	77	41	):	):	PUNCT
fbem-2300	77	42	3	3	NUM
fbem-2300	77	43	.	.	PUNCT
fbem-2300	78	1	[	[	X
fbem-2300	78	2	2	2	NUM
fbem-2300	78	3	]	]	PUNCT
fbem-2300	78	4	chen	chen	PROPN
fbem-2300	78	5	siwen	siwen	PROPN
fbem-2300	78	6	stock	stock	NOUN
fbem-2300	78	7	investment	investment	NOUN
fbem-2300	78	8	and	and	CCONJ
fbem-2300	78	9	prediction	prediction	NOUN
fbem-2300	78	10	based	base	VERB
fbem-2300	78	11	on	on	ADP
fbem-2300	78	12	machine	machine	NOUN
fbem-2300	78	13	learning	learn	VERB
fbem-2300	78	14	[	[	X
fbem-2300	78	15	j	j	X
fbem-2300	78	16	]	]	X
fbem-2300	78	17	digital	digital	ADJ
fbem-2300	78	18	design	design	NOUN
fbem-2300	78	19	.	.	PUNCT
fbem-2300	79	1	cg	cg	NOUN
fbem-2300	79	2	world	world	NOUN
fbem-2300	79	3	,	,	PUNCT
fbem-2300	79	4	2020	2020	NUM
fbem-2300	79	5	,	,	PUNCT
fbem-2300	79	6	009	009	NUM
fbem-2300	79	7	(	(	PUNCT
fbem-2300	79	8	009	009	NUM
fbem-2300	79	9	):	):	PUNCT
fbem-2300	79	10	p.122	p.122	NOUN
fbem-2300	79	11	-	-	SYM
fbem-2300	79	12	123	123	NUM
fbem-2300	79	13	.	.	PUNCT
fbem-2300	80	1	[	[	X
fbem-2300	80	2	3	3	X
fbem-2300	80	3	]	]	X
fbem-2300	80	4	wei	wei	PROPN
fbem-2300	80	5	early	early	ADJ
fbem-2300	80	6	morning	morning	NOUN
fbem-2300	80	7	research	research	NOUN
fbem-2300	80	8	on	on	ADP
fbem-2300	80	9	the	the	DET
fbem-2300	80	10	application	application	NOUN
fbem-2300	80	11	of	of	ADP
fbem-2300	80	12	machine	machine	NOUN
fbem-2300	80	13	learning	learning	NOUN
fbem-2300	80	14	in	in	ADP
fbem-2300	80	15	the	the	DET
fbem-2300	80	16	analysis	analysis	NOUN
fbem-2300	80	17	of	of	ADP
fbem-2300	80	18	securities	security	NOUN
fbem-2300	80	19	investment	investment	NOUN
fbem-2300	81	1	[	[	X
fbem-2300	81	2	j	j	X
fbem-2300	81	3	]	]	X
fbem-2300	81	4	information	information	NOUN
fbem-2300	81	5	weekly	weekly	NOUN
fbem-2300	81	6	,	,	PUNCT
fbem-2300	81	7	2019	2019	NUM
fbem-2300	81	8	(	(	PUNCT
fbem-2300	81	9	52	52	NUM
fbem-2300	81	10	):	):	PUNCT
fbem-2300	81	11	1	1	NUM
fbem-2300	81	12	.	.	PUNCT
fbem-2300	82	1	[	[	X
fbem-2300	82	2	4	4	NUM
fbem-2300	82	3	]	]	PUNCT
fbem-2300	82	4	yuan	yuan	NOUN
fbem-2300	82	5	junfeng	junfeng	NOUN
fbem-2300	82	6	when	when	SCONJ
fbem-2300	82	7	machine	machine	NOUN
fbem-2300	82	8	learning	learning	NOUN
fbem-2300	82	9	is	be	AUX
fbem-2300	82	10	encountered	encounter	VERB
fbem-2300	82	11	in	in	ADP
fbem-2300	82	12	the	the	DET
fbem-2300	82	13	field	field	NOUN
fbem-2300	82	14	of	of	ADP
fbem-2300	82	15	financial	financial	ADJ
fbem-2300	82	16	investment	investment	NOUN
fbem-2300	83	1	[	[	X
fbem-2300	83	2	j	j	X
fbem-2300	83	3	]	]	X
fbem-2300	83	4	ai	ai	VERB
fbem-2300	83	5	,	,	PUNCT
fbem-2300	83	6	2018	2018	NUM
fbem-2300	83	7	(	(	PUNCT
fbem-2300	83	8	5	5	NUM
fbem-2300	83	9	):	):	PUNCT
fbem-2300	83	10	6	6	NUM
fbem-2300	83	11	.	.	PUNCT
fbem-2300	84	1	[	[	X
fbem-2300	84	2	5	5	X
fbem-2300	84	3	]	]	PUNCT
fbem-2300	84	4	huo	huo	PROPN
fbem-2300	84	5	yan	yan	PROPN
fbem-2300	84	6	empirical	empirical	ADJ
fbem-2300	84	7	research	research	NOUN
fbem-2300	84	8	on	on	ADP
fbem-2300	84	9	credit	credit	NOUN
fbem-2300	84	10	rating	rating	NOUN
fbem-2300	84	11	and	and	CCONJ
fbem-2300	84	12	credit	credit	NOUN
fbem-2300	84	13	debt	debt	NOUN
fbem-2300	84	14	default	default	NOUN
fbem-2300	84	15	-based	-base	VERB
fbem-2300	84	16	on	on	ADP
fbem-2300	84	17	machine	machine	NOUN
fbem-2300	84	18	learning	learn	VERB
fbem-2300	84	19	algorithm	algorithm	NOUN
fbem-2300	84	20	[	[	X
fbem-2300	84	21	j	j	X
fbem-2300	84	22	]	]	X
fbem-2300	84	23	financial	financial	ADJ
fbem-2300	84	24	regulation	regulation	NOUN
fbem-2300	84	25	research	research	NOUN
fbem-2300	84	26	,	,	PUNCT
fbem-2300	84	27	2022	2022	NUM
fbem-2300	84	28	(	(	PUNCT
fbem-2300	84	29	3	3	NUM
fbem-2300	84	30	):	):	PUNCT
fbem-2300	84	31	21	21	NUM
fbem-2300	84	32	[	[	SYM
fbem-2300	84	33	6	6	NUM
fbem-2300	84	34	]	]	SYM
fbem-2300	84	35	su	su	PROPN
fbem-2300	84	36	bingzhi	bingzhi	PROPN
fbem-2300	84	37	exploration	exploration	PROPN
fbem-2300	84	38	of	of	ADP
fbem-2300	84	39	portfolio	portfolio	NOUN
fbem-2300	84	40	investment	investment	NOUN
fbem-2300	84	41	based	base	VERB
fbem-2300	84	42	on	on	ADP
fbem-2300	84	43	machine	machine	NOUN
fbem-2300	84	44	learning	learn	VERB
fbem-2300	84	45	algorithm	algorithm	NOUN
fbem-2300	84	46	[	[	X
fbem-2300	84	47	j	j	X
fbem-2300	84	48	]	]	X
fbem-2300	84	49	knowledge	knowledge	NOUN
fbem-2300	84	50	base	base	NOUN
fbem-2300	84	51	,	,	PUNCT
fbem-2300	84	52	2017	2017	NUM
fbem-2300	84	53	(	(	PUNCT
fbem-2300	84	54	15	15	NUM
fbem-2300	84	55	):	):	PUNCT
fbem-2300	84	56	2	2	NUM
fbem-2300	84	57	.	.	PUNCT
fbem-2300	85	1	[	[	X
fbem-2300	85	2	7	7	NUM
fbem-2300	85	3	]	]	X
fbem-2300	85	4	li	li	PROPN
fbem-2300	85	5	bin	bin	PROPN
fbem-2300	85	6	,	,	PUNCT
fbem-2300	85	7	shao	shao	PROPN
fbem-2300	85	8	xinyue	xinyue	PROPN
fbem-2300	85	9	,	,	PUNCT
fbem-2300	85	10	li	li	PROPN
fbem-2300	85	11	yueyang	yueyang	PROPN
fbem-2300	85	12	research	research	PROPN
fbem-2300	85	13	on	on	ADP
fbem-2300	85	14	fundamentals	fundamental	NOUN
fbem-2300	85	15	quantitative	quantitative	ADJ
fbem-2300	85	16	investment	investment	NOUN
fbem-2300	85	17	driven	drive	VERB
fbem-2300	85	18	by	by	ADP
fbem-2300	85	19	machine	machine	NOUN
fbem-2300	85	20	learning	learn	VERB
fbem-2300	85	21	[	[	X
fbem-2300	85	22	j	j	X
fbem-2300	85	23	]	]	X
fbem-2300	85	24	china	china	PROPN
fbem-2300	85	25	industrial	industrial	ADJ
fbem-2300	85	26	economy	economy	NOUN
fbem-2300	85	27	,	,	PUNCT
fbem-2300	85	28	2019	2019	NUM
fbem-2300	85	29	(	(	PUNCT
fbem-2300	85	30	8)	8)	NUM
fbem-2300	85	31	:	:	SYM
fbem-2300	85	32	19	19	NUM
fbem-2300	85	33	.	.	PUNCT
fbem-2300	86	1	[	[	X
fbem-2300	86	2	8	8	NUM
fbem-2300	86	3	]	]	PUNCT
fbem-2300	86	4	wang	wang	PROPN
fbem-2300	86	5	yunkai	yunkai	PROPN
fbem-2300	86	6	,	,	PUNCT
fbem-2300	86	7	lan	lan	PROPN
fbem-2300	86	8	jinhui	jinhui	PROPN
fbem-2300	86	9	ml	ml	PROPN
fbem-2300	86	10	-	-	PUNCT
fbem-2300	86	11	ffa	ffa	NOUN
fbem-2300	86	12	:	:	PUNCT
fbem-2300	86	13	quantitative	quantitative	ADJ
fbem-2300	86	14	investment	investment	NOUN
fbem-2300	86	15	strategy	strategy	NOUN
fbem-2300	86	16	based	base	VERB
fbem-2300	86	17	on	on	ADP
fbem-2300	86	18	machine	machine	NOUN
fbem-2300	86	19	learning	learning	NOUN
fbem-2300	86	20	and	and	CCONJ
fbem-2300	86	21	fundamental	fundamental	ADJ
fbem-2300	86	22	factor	factor	NOUN
fbem-2300	86	23	analysis	analysis	NOUN
fbem-2300	86	24	[	[	X
fbem-2300	86	25	j	j	X
fbem-2300	86	26	]	]	X
fbem-2300	86	27	times	times	PROPN
fbem-2300	86	28	finance	finance	NOUN
fbem-2300	86	29	,	,	PUNCT
fbem-2300	86	30	2018	2018	NUM
fbem-2300	86	31	(	(	PUNCT
fbem-2300	86	32	32	32	NUM
fbem-2300	86	33	):	):	PUNCT
fbem-2300	86	34	3	3	NUM
fbem-2300	86	35	.	.	PUNCT
fbem-2300	87	1	[	[	X
fbem-2300	87	2	9	9	NUM
fbem-2300	87	3	]	]	PUNCT
fbem-2300	87	4	lin	lin	PROPN
fbem-2300	87	5	yaohu	yaohu	PROPN
fbem-2300	87	6	,	,	PUNCT
fbem-2300	87	7	liu	liu	PROPN
fbem-2300	87	8	shancun	shancun	PROPN
fbem-2300	87	9	,	,	PUNCT
fbem-2300	87	10	yang	yang	PROPN
fbem-2300	87	11	haijun	haijun	PROPN
fbem-2300	87	12	research	research	VERB
fbem-2300	87	13	on	on	ADP
fbem-2300	87	14	a	a	DET
fbem-2300	87	15	stock	stock	NOUN
fbem-2300	87	16	market	market	NOUN
fbem-2300	87	17	investment	investment	NOUN
fbem-2300	87	18	strategy	strategy	NOUN
fbem-2300	87	19	based	base	VERB
fbem-2300	87	20	on	on	ADP
fbem-2300	87	21	machine	machine	NOUN
fbem-2300	87	22	learning	learning	NOUN
fbem-2300	87	23	and	and	CCONJ
fbem-2300	87	24	candle	candle	NOUN
fbem-2300	87	25	chart	chart	NOUN
fbem-2300	88	1	[	[	X
fbem-2300	88	2	j	j	X
fbem-2300	88	3	]	]	X
fbem-2300	88	4	journal	journal	NOUN
fbem-2300	88	5	of	of	ADP
fbem-2300	88	6	econometrics	econometric	NOUN
fbem-2300	88	7	,	,	PUNCT
fbem-2300	88	8	2022	2022	NUM
fbem-2300	88	9	,	,	PUNCT
fbem-2300	88	10	2	2	NUM
fbem-2300	88	11	(	(	PUNCT
fbem-2300	88	12	1	1	NUM
fbem-2300	88	13	):	):	PUNCT
fbem-2300	88	14	15	15	NUM
fbem-2300	88	15	.	.	PUNCT
fbem-2300	89	1	[	[	X
fbem-2300	89	2	10	10	NUM
fbem-2300	89	3	]	]	X
fbem-2300	89	4	yin	yin	PROPN
fbem-2300	89	5	xingguang	xingguang	PROPN
fbem-2300	89	6	research	research	PROPN
fbem-2300	89	7	on	on	ADP
fbem-2300	89	8	portfolio	portfolio	NOUN
fbem-2300	89	9	selection	selection	NOUN
fbem-2300	89	10	based	base	VERB
fbem-2300	89	11	on	on	ADP
fbem-2300	89	12	machine	machine	NOUN
fbem-2300	89	13	learning	learn	VERB
fbem-2300	89	14	[	[	X
fbem-2300	89	15	j	j	X
fbem-2300	89	16	]	]	X
fbem-2300	89	17	information	information	NOUN
fbem-2300	89	18	system	system	NOUN
fbem-2300	89	19	engineering	engineering	NOUN
fbem-2300	89	20	,	,	PUNCT
fbem-2300	89	21	2021	2021	NUM
fbem-2300	89	22	(	(	PUNCT
fbem-2300	89	23	12	12	NUM
fbem-2300	89	24	):	):	PUNCT
fbem-2300	89	25	4	4	NUM
fbem-2300	89	26	.	.	PUNCT
fbem-2300	90	1	[	[	X
fbem-2300	90	2	11	11	NUM
fbem-2300	90	3	]	]	X
fbem-2300	90	4	bao	bao	PROPN
fbem-2300	90	5	junying	junying	PROPN
fbem-2300	90	6	,	,	PUNCT
fbem-2300	90	7	shi	shi	PROPN
fbem-2300	90	8	chengxiang	chengxiang	PROPN
fbem-2300	90	9	research	research	PROPN
fbem-2300	90	10	on	on	ADP
fbem-2300	90	11	the	the	DET
fbem-2300	90	12	application	application	NOUN
fbem-2300	90	13	of	of	ADP
fbem-2300	90	14	machine	machine	NOUN
fbem-2300	90	15	learning	learning	NOUN
fbem-2300	90	16	in	in	ADP
fbem-2300	90	17	china	china	PROPN
fbem-2300	90	18	's	's	PART
fbem-2300	90	19	high	high	ADJ
fbem-2300	90	20	yield	yield	NOUN
fbem-2300	90	21	debt	debt	NOUN
fbem-2300	90	22	investment	investment	NOUN
fbem-2300	90	23	[	[	X
fbem-2300	90	24	j	j	X
fbem-2300	90	25	]	]	X
fbem-2300	90	26	journal	journal	NOUN
fbem-2300	90	27	of	of	ADP
fbem-2300	90	28	chongqing	chongqe	VERB
fbem-2300	90	29	second	second	ADJ
fbem-2300	90	30	normal	normal	ADJ
fbem-2300	90	31	university	university	NOUN
fbem-2300	90	32	,	,	PUNCT
fbem-2300	90	33	2021	2021	NUM
fbem-2300	90	34	,	,	PUNCT
fbem-2300	90	35	34	34	NUM
fbem-2300	90	36	(	(	PUNCT
fbem-2300	90	37	3	3	NUM
fbem-2300	90	38	):	):	PUNCT
fbem-2300	90	39	7	7	NUM
fbem-2300	90	40	.	.	PUNCT