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

Published online by Cambridge University Press:  30 January 2019

Tim Bollerslev Open the ORCID record for Tim Bollerslev [Opens in a new window] ,
Sophia Zhengzi Li  and
Bingzhi Zhao
Tim Bollerslev
Affiliation:
Bollerslev, [email protected], Department of Economics Duke University, the National Bureau of Economic Research (NBER) and Center for Research in Econometric Analysis of Time Series (CREATES)
Sophia Zhengzi Li*
Affiliation:
Li, [email protected], Department of Finance and Economics Rutgers University
Bingzhi Zhao
Affiliation:
Zhao, [email protected], Numeric Investors LLC
*
Li (corresponding author), [email protected]
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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.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 55 , Issue 3 , May 2020 , pp. 751 - 781
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2019

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Footnotes

We thank an anonymous referee and Hendrik Bessembinder (the editor) for their very helpful comments, which greatly improved the paper. We also thank Peter Christoffersen, Alex Hsu, Anh Le, Jia Li, Andrew Patton, Riccardo Sabbatucci, Ravi Sastry, Gill Segal, and George Tauchen, along with seminar participants in the Duke financial econometrics lunch group, the Society for Financial Econometrics (SoFiE) summer school at Harvard, the 2017 Midwest Finance Association Annual Meeting, the 2017 Financial Intermediation Research Society Conference, the 2017 European Finance Association Conference, the 2017 Northern Finance Association Conference, and the 2018 Finance Down Under Conference for their many helpful comments and suggestions. The views expressed herein are solely those of the authors and do not necessarily represent those of Numeric Investors LLC nor Man Group PLC.

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