Testing Trade-Off and Pecking Order Predictions about Dividends and Debt

We use a sample of option prices, and the method of Bakshi, Kapadia and Madan (2003), to estimate the ex ante higher moments of the underlying individual securities’ risk-neutral returns distribution. We find that individual securities’ volatility, skewness, and kurtosis are strongly related to subsequent returns. Specifically, we find a negative relation between volatility and returns in thecross-section. We also find a significant relation between skewness and returns, with more negatively (positively) skewed returns associated with subsequent higher (lower) returns, while kurtosis is positively related to subsequent returns. We analyze the extent to which these returns relations represent compensation for risk. We find evidence that, even after controlling for differences in comoments, individual securities’ skewness matters. As an application, we examine whether idiosyncratic skewness in technology stocks might explain bubble pricing in Internet stocks. However, when we combine information in the risk-neutral distribution and a stochastic discount factor to estimate the implied physical distribution of industry returns, we find little evidence that the distribution of technology stocks was positively skewed during the bubble period – in fact, these stocks have the lowest skew, and the highest estimated Sharpe ratio, of all stocks in our sample.

/pdf/ex-ante-skewness-and-expected-stock-returns-1o8997wcn8.pdf

Ex Ante Skewness and Expected Stock Returns

https://www3.nd.edu/~finance/020601/news/2012Fall%20FinanceSeminarSeries-KrisJacobsPaper.pdf

Does realized skewness predict the cross-section of equity returns? ☆

http://public.econ.duke.edu/~get/wpapers/bost.pdf

Risk and return: Long-run relations, fractional cointegration, and return predictability $

Evidence on the Speed of Convergence to Market Efficiency

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments? time-series and cross-sectional properties We investigate if this week?'s realized moments are informative for the cross-section of next week'?s stock returns We ?find a very strong negative relationship between realized skewness and next week?'s 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 365 Our results on realized skewness are robust across a wide variety of implementations, 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

Does Realized Skewness Predict the Cross-Section of Equity Returns?

We use intraday data to compute weekly realized variance, skewness, and kurtosis for equity returns and study the realized moments' time-series and cross-sectional properties We investigate if this week's realized moments are informative for the cross-section of next week's stock returns We find a very strong negative relationship between realized skewness and next week's 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 19 basis points with a t-statistic of 370 Our results on realized skewness are robust across a wide variety of implementations, 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

Yes. We use intraday data to compute weekly realized variance, skewness and kurtosis for individual equities and assess whether this week?s realized moments predict next week?s stock returns in the cross-section. We sort stocks each week according to their past realized moments, form decile portfolios and analyze subsequent weekly returns. We ?nd a very strong negative relationship between realized skewness and next week?s stock returns, and a positive relationship between realized kurtosis and next week?s stock returns. We do not ?nd a strong relationship between realized volatility and 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 43 basis points with a t-statistic of 8:91. A similar strategy that buys stocks with high realized kurtosis and sells stocks with low realized kurtosis produces a weekly return of 16 basis points with a t-statistic of 2:98. Our results are robust across sample periods, portfolio weightings, and proxies for ?rm characteristics, and they are not captured by the Fama-French and Carhart factors.

/pdf/do-realized-skewness-and-kurtosis-predict-the-cross-section-4m8fouhwaj.pdf

Do Realized Skewness and Kurtosis Predict the Cross-Section of Equity Returns?

https://www.efmaefm.org/0EFMAMEETINGS/EFMA%20ANNUAL%20MEETINGS/2015-Amsterdam/papers/EFMA2015_0088_fullpaper.pdf

Diego Amaya

Papers

Does Realized Skewness Predict the Cross-Section of Equity Returns?

Does realized skewness predict the cross-section of equity returns? ☆

Does Realized Skewness Predict the Cross-Section of Equity Returns?

Do Realized Skewness and Kurtosis Predict the Cross-Section of Equity Returns?

The similarity of ECB’s communication