4-Factor Model for Overnight Returns

TL;DR

This paper introduces a 4-factor model based on intraday data to predict overnight returns, focusing on size, volatility, momentum, and liquidity, and demonstrates its effectiveness through historical regressions and an intraday alpha.

Contribution

The paper presents a novel 4-factor model specifically designed for overnight returns, excluding long horizon factors, and validates its predictive power using historical regressions and an intraday alpha.

Findings

The 4 factors show significant predictive power for overnight returns.

Historical regressions indicate sizable t-statistics for the factors.

The model improves intraday mean-reversion strategies.

Abstract

We propose a 4-factor model for overnight returns and give explicit definitions of our 4 factors. Long horizon fundamental factors such as value and growth lack predictive power for overnight (or similar short horizon) returns and are not included. All 4 factors are constructed based on intraday price and volume data and are analogous to size (price), volatility, momentum and liquidity (volume). Historical regressions a la Fama and MacBeth (1973) suggest that our 4 factors have sizable serial t-statistic and appear to be relevant predictors for overnight returns. We check this by using our 4-factor model in an explicit intraday mean-reversion alpha.