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

42 Pages Posted: 1 Sep 2021 Last revised: 2 Sep 2021

See all articles by Zehua Zhang

Zehua Zhang

Hunan University

Ran Zhao

San Diego State University

Multiple version iconThere are 2 versions of this paper

Date Written: August 29, 2021

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

JEL Classification: G11, G12, G17, G41

Suggested Citation

Zhang, Zehua and Zhao, Ran, Good Volatility, Bad Volatility, and the Cross Section of Cryptocurrency Returns (August 29, 2021). Available at SSRN: https://ssrn.com/abstract=3910202 or http://dx.doi.org/10.2139/ssrn.3910202

Zehua Zhang

Hunan University ( email )

Lushan Road, Yuelu District
Changsha, Hunan
China

Ran Zhao (Contact Author)

San Diego State University ( email )

5500 Campanile Dr
San Diego, CA 92182
United States

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