Higher moments matter! Cross‐sectional (higher) moments and the predictability of stock returns
| Autor: | Lars Kaiser, Sebastian Stöckl |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
040101 forestry
Economics and Econometrics 050208 finance Short run Equity premium puzzle 05 social sciences 04 agricultural and veterinary sciences Growth stock Skewness 0502 economics and business Predictive power Kurtosis Econometrics 0401 agriculture forestry and fisheries Predictability Volatility (finance) Finance Mathematics |
| Zdroj: | Review of Financial Economics. 39:455-481 |
| ISSN: | 1873-5924 1058-3300 |
| DOI: | 10.1002/rfe.1121 |
| Popis: | In this paper we investigate the predictive power of cross-sectional volatility, skewness and kurtosis for future stock returns. Adding to the work of Maio (2015), who finds cross-sectional volatility to forecast a decline in the equity premium with high predictive power in-sample as well as out-of-sample, we highlight the additional role of cross-sectional skewness and cross-sectional kurtosis. We find cross-sectional skewness to deliver a significant contribution to the performance of cross-sectional volatility in the short run (less than 12 months forecasts), while cross-sectional skewness and cross-sectional kurtosis contribute significantly to the performance of cross-sectional volatility at horizons greater than 12 months. Furthermore, we document a clear benefit of including higher moments when disaggregating excess market returns along the value and size dimension. In this case, both cross-sectional skewness and cross-sectional kurtosis span the predictive quality towards large-cap and growth stocks. Overall, the addition of higher order cross-sectional moments significantly improves the predictive performance of cross-sectional volatility, a variable that is already regarded as having high predictive power with respect to the equity premium. |
| Databáze: | OpenAIRE |
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