Weekly Idiosyncratic Risk Metrics and Idiosyncratic Momentum: Evidence from the Chinese Stock Market

26 Pages Posted: 8 Nov 2019

See all articles by Huai-long Shi

Huai-long Shi

Nanjing University of Information Science & Technology

Wei-Xing Zhou

East China University of Science and Technology - School of Business

Date Written: October 27, 2019

Abstract

This paper focuses on the weekly idiosyncratic momentum (IMOM) as well as its risk-adjusted versions with respect to various idiosyncratic risk metrics. Using the A-share individual stocks in the Chinese market from January 1997 to December 2017, we first evaluate the performance of the weekly momentum and idiosyncratic momentum based on raw returns and idiosyncratic returns, respectively. After that the univariate portfolio analysis is conducted to investigate the return predictability with respect to various idiosyncratic risk metrics. Further, we perform a comparative study on the performance of the IMOMportfolios with respect to various risk metrics. At last, we explore the possible explanations to the IMOM as well as risk-based IMOM portfolios. We find that 1) there is a prevailing contrarian effect and a IMOM effect for the whole sample; 2) a negative relation exists between most of the idiosyncratic risk metrics and the cross-sectional returns, and better performance is found that is linked to idiosyncratic volatility (IVol) and maximum drawdowns (IMDs); 3) additionally, the IVol-based and IMD-based IMOM portfolios exhibit a better explanatory power to the IMOM portfolios with respect to other risk metrics; 4) finally, higher profitability of the IMOM as well as IVol-based and IMD-based IMOM portfolios is found to be related to upside market states, high levels of liquidity and high levels of investor sentiment.

Keywords: Momentum effect, Contrarian effect, Idiosyncratic risk, Chinese stock market

JEL Classification: G10, G11, G12

Suggested Citation

Shi, Huai-Long and Zhou, Wei-Xing, Weekly Idiosyncratic Risk Metrics and Idiosyncratic Momentum: Evidence from the Chinese Stock Market (October 27, 2019). Available at SSRN: https://ssrn.com/abstract=3477049 or http://dx.doi.org/10.2139/ssrn.3477049

Huai-Long Shi

Nanjing University of Information Science & Technology ( email )

No.219, Ningliu Road
Nanjing, Jiangsu 21004
China

Wei-Xing Zhou (Contact Author)

East China University of Science and Technology - School of Business ( email )

130 Meilong Road
Shanghai, 200237
China

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