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The Idiosyncratic Volatility Puzzle – Anomaly or Data Mining?

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  • Kowalke, Leon

Abstract

In this study, I investigate the robustness of the idiosyncratic volatility puzzle to the configuration of the research design. Using the regression- as well as the portfolio-based concept, I start with the replication of the idiosyncratic volatility puzzle approving the findings of Ang et al. (2006). However, when idiosyncratic volatility is estimated from monthly data and a time window spanning 1 or 5 years, the puzzle vanishes, regardless of the research method employed. Similar result hold if only stocks with a market capitalization above the cross-sectional median or those with a price higher than 10$ are used. Independent of the weighting scheme, the puzzle is also absent in the regression-based context when the risk premia are estimated by generalized least squares weighting returns by the inverse of their variance estimates. The same finding is derived in the portfolio-based context by extending the holding period to 12 months or controlling for the past month maximum daily return.

Suggested Citation

  • Kowalke, Leon, 2022. "The Idiosyncratic Volatility Puzzle – Anomaly or Data Mining?," Junior Management Science (JUMS), Junior Management Science e. V., vol. 7(4), pages 945-985.
    • Handle: RePEc:zbw:jumsac:295008
    DOI: 10.5282/jums/v7i4pp945-985
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    References listed on IDEAS

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    1. Ang, Andrew & Hodrick, Robert J. & Xing, Yuhang & Zhang, Xiaoyan, 2009. "High idiosyncratic volatility and low returns: International and further U.S. evidence," Journal of Financial Economics, Elsevier, vol. 91(1), pages 1-23, January.
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