An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model

Yuming Li; Pin Ni; Victor Chang

doi:10.5220/0007722000520058

An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model

Yuming Li, Pin Ni, Victor Chang

Centre for Digital Innovation

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The stock market plays a major role in the entire financial market. How to obtain effective trading signals in the stock market is a topic that stock market has long been discussing. This paper first reviews the Deep Reinforcement Learning theory and model, validates the validity of the model through empirical data, and compares the benefits of the three classical Deep Reinforcement Learning models. From the perspective of the automated stock market investment transaction decision-making mechanism, Deep Reinforcement Learning model has made a useful reference for the construction of investor automation investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of investor strategy yield.

Original language	English
Title of host publication	COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk
Editors	Farshad Firouzi, Ernesto Estrada, Victor Mendez Munoz, Victor Chang
Publisher	SciTePress
Pages	52-58
Number of pages	7
ISBN (Electronic)	9789897583667
DOIs	https://doi.org/10.5220/0007722000520058
Publication status	Published - 1 Jan 2019
Event	4th International Conference on Complexity, Future Information Systems and Risk - Heraklion, Crete, Greece Duration: 2 May 2019 → 4 May 2019 Conference number: 4

Publication series

Name	COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk

Conference

Conference	4th International Conference on Complexity, Future Information Systems and Risk
Abbreviated title	COMPLEXIS 2019
Country/Territory	Greece
City	Heraklion, Crete
Period	2/05/19 → 4/05/19

Access to Document

10.5220/0007722000520058

Cite this

Li, Y., Ni, P., & Chang, V. (2019). An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model. In F. Firouzi, E. Estrada, V. M. Munoz, & V. Chang (Eds.), COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk (pp. 52-58). (COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk). SciTePress. https://doi.org/10.5220/0007722000520058

Li, Yuming ; Ni, Pin ; Chang, Victor. / An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model. COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk. editor / Farshad Firouzi ; Ernesto Estrada ; Victor Mendez Munoz ; Victor Chang. SciTePress, 2019. pp. 52-58 (COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk).

@inproceedings{390eea48c95e4e52a0b6b4d1bcb023f6,

title = "An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model",

abstract = "The stock market plays a major role in the entire financial market. How to obtain effective trading signals in the stock market is a topic that stock market has long been discussing. This paper first reviews the Deep Reinforcement Learning theory and model, validates the validity of the model through empirical data, and compares the benefits of the three classical Deep Reinforcement Learning models. From the perspective of the automated stock market investment transaction decision-making mechanism, Deep Reinforcement Learning model has made a useful reference for the construction of investor automation investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of investor strategy yield.",

author = "Yuming Li and Pin Ni and Victor Chang",

year = "2019",

month = jan,

day = "1",

doi = "10.5220/0007722000520058",

language = "English",

series = "COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk",

publisher = "SciTePress",

pages = "52--58",

editor = "Farshad Firouzi and Ernesto Estrada and Munoz, {Victor Mendez} and Victor Chang",

booktitle = "COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk",

note = "4th International Conference on Complexity, Future Information Systems and Risk, COMPLEXIS 2019 ; Conference date: 02-05-2019 Through 04-05-2019",

}

Li, Y, Ni, P & Chang, V 2019, An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model. in F Firouzi, E Estrada, VM Munoz & V Chang (eds), COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk. COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk, SciTePress, pp. 52-58, 4th International Conference on Complexity, Future Information Systems and Risk, Heraklion, Crete, Greece, 2/05/19. https://doi.org/10.5220/0007722000520058

An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model. / Li, Yuming; Ni, Pin; Chang, Victor.
COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk. ed. / Farshad Firouzi; Ernesto Estrada; Victor Mendez Munoz; Victor Chang. SciTePress, 2019. p. 52-58 (COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model

AU - Li, Yuming

AU - Ni, Pin

AU - Chang, Victor

N1 - Conference code: 4

PY - 2019/1/1

Y1 - 2019/1/1

N2 - The stock market plays a major role in the entire financial market. How to obtain effective trading signals in the stock market is a topic that stock market has long been discussing. This paper first reviews the Deep Reinforcement Learning theory and model, validates the validity of the model through empirical data, and compares the benefits of the three classical Deep Reinforcement Learning models. From the perspective of the automated stock market investment transaction decision-making mechanism, Deep Reinforcement Learning model has made a useful reference for the construction of investor automation investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of investor strategy yield.

AB - The stock market plays a major role in the entire financial market. How to obtain effective trading signals in the stock market is a topic that stock market has long been discussing. This paper first reviews the Deep Reinforcement Learning theory and model, validates the validity of the model through empirical data, and compares the benefits of the three classical Deep Reinforcement Learning models. From the perspective of the automated stock market investment transaction decision-making mechanism, Deep Reinforcement Learning model has made a useful reference for the construction of investor automation investment model, the construction of stock market investment strategy, the application of artificial intelligence in the field of financial investment and the improvement of investor strategy yield.

UR - http://www.scopus.com/inward/record.url?scp=85067524270&partnerID=8YFLogxK

U2 - 10.5220/0007722000520058

DO - 10.5220/0007722000520058

M3 - Conference contribution

AN - SCOPUS:85067524270

T3 - COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk

SP - 52

EP - 58

BT - COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk

A2 - Firouzi, Farshad

A2 - Estrada, Ernesto

A2 - Munoz, Victor Mendez

A2 - Chang, Victor

PB - SciTePress

T2 - 4th International Conference on Complexity, Future Information Systems and Risk

Y2 - 2 May 2019 through 4 May 2019

ER -

Li Y, Ni P, Chang V. An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model. In Firouzi F, Estrada E, Munoz VM, Chang V, editors, COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk. SciTePress. 2019. p. 52-58. (COMPLEXIS 2019 - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk). doi: 10.5220/0007722000520058

An Empirical Research on the Investment Strategy of Stock Market based on Deep Reinforcement Learning model

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this