Cross-sectional Skewness

Simon Oh and Jessica Wachter ()

No 25113, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: This paper evaluates skewness in the cross-section of stock returns in light of predictions from a well-known class of models. Cross-sectional skewness in monthly returns far exceeds what the standard lognormal model of returns would predict. However, skewness in long-run returns substantially understates what the lognormal model would predict. Nonstationary share dynamics imply a breakdown in the distinction between market and idiosyncratic risk in the lognormal model. We present an alternative model that matches the skewness in the data and implies stationary wealth shares. In this model, idiosyncratic risk is the primary driver of growth in the economy.

JEL-codes: G12 (search for similar items in EconPapers)
Date: 2018-09
New Economics Papers: this item is included in nep-fmk and nep-rmg
Note: AP
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Published as Sangmin S Oh & Jessica A Wachter & Hui Chen, 2022. "Cross-Sectional Skewness," The Review of Asset Pricing Studies, vol 12(1), pages 155-198.

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