Application of a Maverick Stock Capturing Strategy in the Chinese Stock Market
Authors
Yifei Wang1, *, Hui Lin2, Shiyu Yao3, Jiayun Zou4
1Department of economics, University of Calgary, Alberta, Canada
2College of life science, Sichuan Agricultural University, Yaan, China
3College of economics and management, Hefei Normal University, Hefei, China
4College of humanities, Sichuan Agricultural University, Yaan, China
*Corresponding author.
Email: yifeiiris.wang@gmail.com
Corresponding Author
Yifei Wang
Available Online 29 December 2022.
- DOI
- 10.2991/978-94-6463-042-8_76How to use a DOI?
- Keywords
- Trading strategy; Maverick stock; Stock return; Stock market
- Abstract
In this paper, we propose a maverick stock trading strategy and apply it to the Chinese stock market. We use a high-frequency trade data of Chinese stock market in 2019 and apply the trading strategy every day. Data comes from the CSMAR database. Our trading strategy shows an amazingly high return. We further find that the strategy behaves better when trade in all the markets together. When trading in different markets respectively, the return is still much higher than the market index’s return, where the highest return appears in the GEM market. This paper provides a new perspective of stock trading.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yifei Wang AU - Hui Lin AU - Shiyu Yao AU - Jiayun Zou PY - 2022 DA - 2022/12/29 TI - Application of a Maverick Stock Capturing Strategy in the Chinese Stock Market BT - Proceedings of the 2022 International Conference on mathematical statistics and economic analysis (MSEA 2022) PB - Atlantis Press SP - 527 EP - 534 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-042-8_76 DO - 10.2991/978-94-6463-042-8_76 ID - Wang2022 ER -