| Issue |
E3S Web Conf.
Volume 235, 2021
2020 International Conference on New Energy Technology and Industrial Development (NETID 2020)
|
|
|---|---|---|
| Article Number | 03025 | |
| Number of page(s) | 6 | |
| Section | Analysis on the Development of Intelligent Supply Chain and Internet Digital Industrialization | |
| DOI | https://doi.org/10.1051/e3sconf/202123503025 | |
| Published online | 03 February 2021 | |
To explore the mystery of the idiosyncratic volatility of the A-share market
1
College of Management, Sichuan Agricultural University, Chengdu, China
2
College of Economics, Sichuan Agricultural University, Chengdu, China
3
School of Finance, Southwestern University of Finance and Economics, Chengdu, China
a zhuoling_r795@163.com
b huang.xuehao@qq.com
c mingjia_quant@163.com
Return and risk are inevitable topics in financial research. This paper explores the relationship between IVOL (idiosyncratic volatility) and cross-sectional return (risk premium and excess return) of the Chinese A-share market. With the monthly data of 237 months from January 2001 to September 2019 of Ashare of Shanghai and Shenzhen stock exchange, IVOL of each stock by the regressions is conducted through rolling window based on the four factors model of Carhart. Whether there is a significant positive or negative relationship between the IVOL and the cross-sectional return of the stock by combination analysis and crosssection regression are tested in the paper. The research shows that, after excluding the influence of financial crisis and stock disaster, from January 2001 to September 2019, there is a significant positive relationship between the special volatility and cross-sectional return in Chinese A-share market under normal market conditions, and there is no so-called “mystery of the special volatility”.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.