Abstract
The study tests whether realised moments of stock returns (mean, variance, skewness and kurtosis) computed from daily returns over the last month, quarter and year can predict the 1-month cross-sectional stock returns of 40 US-traded liquid stocks in the period 1986-2019. The performed univariate regression analysis confirmed a statistically significant positive effect between all the realised moments, computed over the last quarter and year, and the future 1-month cross-sectional stock returns, while the 1-month realised moments proved to be mostly insignificant. Multivariate analysis, performed with Elastic Net Regression, has confirmed that investment strategies utilising information from realised moments were able to significantly outperform a random investment in the out-sample period 2004-2019.
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