Good Volatility, Bad Volatility, and the Cross Section of Cryptocurrency Returns

43 Pages Posted: 16 Sep 2022

See all articles by Zehua Zhang

Zehua Zhang

Hunan University

Ran Zhao

San Diego State University

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Abstract

This paper examines the distributional properties of cryptocurrency realized variation measures (RVM) and the predictability of RVM on future returns. We show the cryptocurrency volatility persistence and the importance of the asymmetry on volatility forecasting. Signed jumps variations contribute around 18% of the cryptocurrency return quadratic variations. The realized signed jump (RSJ) strongly predicts the cross-sectional future excess returns. Sorting the cryptocurrencies into portfolios sorted by RSJ yields statistically and economically significant differences in future excess returns. This jump risk premium remains significant after controlling for cryptocurrency market characteristics and existing risk factors. The standard cross-sectional regression convinces the cryptocurrency return predictability from RSJ by controlling multiple cryptocurrency characteristics. The investor attention explains the predictability of realized jump risk in future cryptocurrency returns.

Keywords: cryptocurrency, realized jump, return predictability, realized volatility

Suggested Citation

Zhang, Zehua and Zhao, Ran, Good Volatility, Bad Volatility, and the Cross Section of Cryptocurrency Returns. Available at SSRN: https://ssrn.com/abstract=4220651

Zehua Zhang (Contact Author)

Hunan University ( email )

Lushan Road, Yuelu District
Changsha, Hunan
China

Ran Zhao

San Diego State University ( email )

5500 Campanile Dr
San Diego, CA 92182
United States

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