Good Volatility, Bad Volatility and the Cross-Section of Stock Returns

77 Pages Posted: 17 Feb 2015 Last revised: 12 Dec 2018

See all articles by Tim Bollerslev

Tim Bollerslev

Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Sophia Zhengzi Li

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick

Bingzhi Zhao

Man Numeric

Date Written: December 11, 2018

Abstract

Based on intraday data for a large cross-section of individual stocks and newly developed econometric procedures, we decompose the realized variation for each of the stocks into separate so-called realized up and down semi-variance measures, or “good” and “bad” volatilities, associated with positive and negative high-frequency price increments, respectively. Sorting the individual stocks into portfolios based on their normalized good minus bad volatilities results in economically large and highly statistically significant differences in the subsequent portfolio returns. These differences remain significant after controlling for other firm characteristics and explanatory variables previously associated with the cross-section of expected stock returns

Keywords: Cross-sectional return variation; return predictability; high-frequency-data; semi-variance; jump variation

JEL Classification: C13, C14, G11, G12

Suggested Citation

Bollerslev, Tim and Li, Sophia Zhengzi and Zhao, Bingzhi, Good Volatility, Bad Volatility and the Cross-Section of Stock Returns (December 11, 2018). Journal of Financial and Quantitative Analysis (JFQA), Forthcoming, Available at SSRN: https://ssrn.com/abstract=2565660 or http://dx.doi.org/10.2139/ssrn.2565660

Tim Bollerslev (Contact Author)

Duke University - Finance ( email )

Durham, NC 27708-0120
United States
919-660-1846 (Phone)
919-684-8974 (Fax)

Duke University - Department of Economics

213 Social Sciences Building
Box 90097
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National Bureau of Economic Research (NBER)

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Sophia Zhengzi Li

Rutgers, The State University of New Jersey - Rutgers Business School at Newark & New Brunswick ( email )

100 Rockafeller Rd
Piscataway, NJ 08854
United States

HOME PAGE: http://https://sites.google.com/site/szlwebpage/

Bingzhi Zhao

Man Numeric ( email )

200 Pier 4 Blvd
5th Floor
Boston, MA 02210
United States

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