Make 24bps a week trading skewness?
That is what Amaya, Christofferson, Jacobs, and Vasquez find.
We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and assess whether this week’s realized moments are informative for the cross-section of next week’s stock returns. We sort stocks each week according to their realized moments, form decile portfolios, and analyze subsequent weekly returns. We find a very strong negative relationship between realized skewness and next weeks stock returns. A trading strategy that buys stocks in the lowest realized skewness decile and sells stocks in the highest realized skewness decile generates an average weekly return of 24 basis points with a t-statistic of 3:65. Our results on skewness are robust across a wide variety of implementations, unlike those for alternative skewness measures. They are also robust across sample periods, portfolio weightings, and firm characteristics, and are not captured by the Fama-French and Carhart factors. We find some evidence that the relationship between realized kurtosis and next week’s stock returns is positive, but the evidence is not always robust and statistically significant. We do not find a strong relationship between realized volatility and next week’s stock returns.
Here is the table with all the goodies:
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Definitions of common statistics used in our analysis are available here (towards the bottom)