Capturing the Deep Trend of Stock Market for a Big Profit

Robin Qiu; Jeffrey Gong; Jason Qiu

doi:10.1007/978-3-030-75166-1_5

Capturing the Deep Trend of Stock Market for a Big Profit

Robin Qiu, Jeffrey Gong, Jason Qiu

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

Abstract

This paper explores a new and holistic trading paradigm for profit in the long run. We propose a trading strategy that combines a variety of social, economic, and trading technical indicators to substantially improve the performance of securities trading. Firstly, an enhanced moving average convergence divergence (MACD) trading algorithm is developed. Then, we apply deep learning towards further enhancing the proposed trading strategy, aimed at capturing the deep trend of stock market for a big profit. At last, by accounting for behavioral and social finance, we investigate systematically trading strategies to accommodate individuals’ irrational behavior and the restless social and economic dynamics. Promisingly, the proposed trading paradigm can be easily scaled and transformed over time.

Original language	English (US)
Title of host publication	AI and Analytics for Public Health - Proceedings of the 2020 INFORMS International Conference on Service Science
Editors	Hui Yang, Robin Qiu, Weiwei Chen
Publisher	Springer Science and Business Media B.V.
Pages	101-110
Number of pages	10
ISBN (Print)	9783030751654
DOIs	https://doi.org/10.1007/978-3-030-75166-1_5
State	Published - 2022
Event	INFORMS International Conference on Service Science, ICSS 2020 - Virtual, Online Duration: Dec 19 2020 → Dec 21 2020

Publication series

Name	Springer Proceedings in Business and Economics
ISSN (Print)	2198-7246
ISSN (Electronic)	2198-7254

Conference

Conference	INFORMS International Conference on Service Science, ICSS 2020
City	Virtual, Online
Period	12/19/20 → 12/21/20

All Science Journal Classification (ASJC) codes

General Economics, Econometrics and Finance
General Business, Management and Accounting

Access to Document

10.1007/978-3-030-75166-1_5

Cite this

Qiu, R., Gong, J., & Qiu, J. (2022). Capturing the Deep Trend of Stock Market for a Big Profit. In H. Yang, R. Qiu, & W. Chen (Eds.), AI and Analytics for Public Health - Proceedings of the 2020 INFORMS International Conference on Service Science (pp. 101-110). (Springer Proceedings in Business and Economics). Springer Science and Business Media B.V.. https://doi.org/10.1007/978-3-030-75166-1_5

Qiu, Robin ; Gong, Jeffrey ; Qiu, Jason. / Capturing the Deep Trend of Stock Market for a Big Profit. AI and Analytics for Public Health - Proceedings of the 2020 INFORMS International Conference on Service Science. editor / Hui Yang ; Robin Qiu ; Weiwei Chen. Springer Science and Business Media B.V., 2022. pp. 101-110 (Springer Proceedings in Business and Economics).

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title = "Capturing the Deep Trend of Stock Market for a Big Profit",

abstract = "This paper explores a new and holistic trading paradigm for profit in the long run. We propose a trading strategy that combines a variety of social, economic, and trading technical indicators to substantially improve the performance of securities trading. Firstly, an enhanced moving average convergence divergence (MACD) trading algorithm is developed. Then, we apply deep learning towards further enhancing the proposed trading strategy, aimed at capturing the deep trend of stock market for a big profit. At last, by accounting for behavioral and social finance, we investigate systematically trading strategies to accommodate individuals{\textquoteright} irrational behavior and the restless social and economic dynamics. Promisingly, the proposed trading paradigm can be easily scaled and transformed over time.",

author = "Robin Qiu and Jeffrey Gong and Jason Qiu",

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doi = "10.1007/978-3-030-75166-1_5",

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Qiu, R, Gong, J & Qiu, J 2022, Capturing the Deep Trend of Stock Market for a Big Profit. in H Yang, R Qiu & W Chen (eds), AI and Analytics for Public Health - Proceedings of the 2020 INFORMS International Conference on Service Science. Springer Proceedings in Business and Economics, Springer Science and Business Media B.V., pp. 101-110, INFORMS International Conference on Service Science, ICSS 2020, Virtual, Online, 12/19/20. https://doi.org/10.1007/978-3-030-75166-1_5

Capturing the Deep Trend of Stock Market for a Big Profit. / Qiu, Robin; Gong, Jeffrey; Qiu, Jason.
AI and Analytics for Public Health - Proceedings of the 2020 INFORMS International Conference on Service Science. ed. / Hui Yang; Robin Qiu; Weiwei Chen. Springer Science and Business Media B.V., 2022. p. 101-110 (Springer Proceedings in Business and Economics).

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

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AB - This paper explores a new and holistic trading paradigm for profit in the long run. We propose a trading strategy that combines a variety of social, economic, and trading technical indicators to substantially improve the performance of securities trading. Firstly, an enhanced moving average convergence divergence (MACD) trading algorithm is developed. Then, we apply deep learning towards further enhancing the proposed trading strategy, aimed at capturing the deep trend of stock market for a big profit. At last, by accounting for behavioral and social finance, we investigate systematically trading strategies to accommodate individuals’ irrational behavior and the restless social and economic dynamics. Promisingly, the proposed trading paradigm can be easily scaled and transformed over time.

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Qiu R, Gong J, Qiu J. Capturing the Deep Trend of Stock Market for a Big Profit. In Yang H, Qiu R, Chen W, editors, AI and Analytics for Public Health - Proceedings of the 2020 INFORMS International Conference on Service Science. Springer Science and Business Media B.V. 2022. p. 101-110. (Springer Proceedings in Business and Economics). doi: 10.1007/978-3-030-75166-1_5

Capturing the Deep Trend of Stock Market for a Big Profit

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