Analysis and Analog Simulation of the Investors’ Margin Trading Behavior
- DOI
- 10.2991/icitme-18.2018.22How to use a DOI?
- Keywords
- margin trading; behavioral finance; analog simulation
- Abstract
This paper took investors’ margin trading behavior as the object of study and suggested the hypothesis that the behavioral financial factors would increase market volatility and affected investors’ returns in the environment of margin trading system through theoretical analysis. On the basis of the hypothesis, this paper used the data of margin trading of A stock market in China to carry out measurement test, and indicated that investors’ margin trading behavior existed significant overconfidence, disposal effect and herd effect. Further, this paper constructed artificial stock market and carried out analog simulation of the investors’ margin trading behavior, which shows that the introduction of margin trading system increases the market risk to a certain extent, but it also can be reduced by pre-learning process. Meanwhile, it can be found that the introduction of margin trading increases the returns of fundamental analysis traders, technical analysis traders and noise traders in varying degrees. Compared with other traders, the trend trading strategy adopted by technical analysis traders who make use of excessive market volatility to gain higher income in the margin trading transaction under the incomplete and effective market background.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Bo Zhang AU - Xueting Cao AU - Allen Yang PY - 2018/08 DA - 2018/08 TI - Analysis and Analog Simulation of the Investors’ Margin Trading Behavior BT - Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018) PB - Atlantis Press SP - 108 EP - 115 SN - 1951-6851 UR - https://doi.org/10.2991/icitme-18.2018.22 DO - 10.2991/icitme-18.2018.22 ID - Zhang2018/08 ER -