Proceedings of the 2017 2nd International Conference on Education, Management Science and Economics (ICEMSE 2017)

Influencing Factors and Forecast of Stock Price Manipulation Based on Panel Data Logit Model

Authors
Jianfeng Zhang, Wenxiu Hu
Corresponding Author
Jianfeng Zhang
Available Online December 2017.
DOI
https://doi.org/10.2991/icemse-17.2017.25How to use a DOI?
Keywords
Stock price manipulation, Panel data, Logit model, Manipulation forecasting, Manipulation management
Abstract
Stock price manipulation forecasting is to carry out judgment before the stock price being manipulated, and to identify indicators with which the stocks are likely to be manipulated. Based on the 2015 A-share market stock trading manipulation case panel data issued by China Securities Regulatory Commission, and on the basis of two facts that financial advantage is needed for a manipulator to implement manipulation, and that other investors are permitted to copy trading, the panel data Logit model is built to forecast the stock price manipulation by identifying the main influencing factors of stock price manipulation with the stepwise regression method. The results show that when the average stock holding ratio and the price volatility of the stock in the previous quarter are higher, and the beta value is lower, then it is more likely for the stock price to be manipulated. The overall prediction accuracy of the out-of-sample and the in-sample is 68.18 % and 70.63 % respectively, so the effectiveness is relatively good.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Jianfeng Zhang
AU  - Wenxiu Hu
PY  - 2017/12
DA  - 2017/12
TI  - Influencing Factors and Forecast of Stock Price Manipulation Based on Panel Data Logit Model
BT  - Proceedings of the 2017 2nd International Conference on Education, Management Science and Economics (ICEMSE 2017)
PB  - Atlantis Press
SP  - 103
EP  - 106
SN  - 2352-5428
UR  - https://doi.org/10.2991/icemse-17.2017.25
DO  - https://doi.org/10.2991/icemse-17.2017.25
ID  - Zhang2017/12
ER  -