Capturing the Deep Trend of Stock Market for a Big Profit

Robin Qiu, Jeffrey Gong, Jason Qiu

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish (US)
Title of host publicationAI and Analytics for Public Health - Proceedings of the 2020 INFORMS International Conference on Service Science
EditorsHui Yang, Robin Qiu, Weiwei Chen
PublisherSpringer Science and Business Media B.V.
Pages101-110
Number of pages10
ISBN (Print)9783030751654
DOIs
StatePublished - 2022
EventINFORMS International Conference on Service Science, ICSS 2020 - Virtual, Online
Duration: Dec 19 2020Dec 21 2020

Publication series

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

Conference

ConferenceINFORMS International Conference on Service Science, ICSS 2020
CityVirtual, Online
Period12/19/2012/21/20

All Science Journal Classification (ASJC) codes

  • General Business, Management and Accounting
  • Economics, Econometrics and Finance(all)

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