Expected Skewness And Momentum

Expected Skewness And Momentum via SSRN

Heiko Jacobs

University of Mannheim – Department of Business Administration and Finance, Especially Banking

Tobias Regele

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University of Mannheim – Department of Business Administration and Finance, especially Banking

Martin Weber

University of Mannheim – Department of Banking and Finance

May 2015


Motivated by the time-series insights of Daniel and Moskowitz (2014), we investigate the link between expected skewness and momentum in the cross-section. The three factor alpha of skewness-enhanced (-weakened) momentum strategies is about twice (half) as large as the traditional momentum alpha. In fact, skewness is among the most important cross-sectional determinants of momentum. Our findings do not neatly fit within a specific prominent theory of momentum. Due to the simplicity of the approach, its economic magnitude, and its existence among large stocks and in the recent past, the results appear difficult to reconcile with the efficient market hypothesis.

Expected Skewness And Momentum – Introduction

One of the most puzzling and robust anomalies in capital markets is the momentum effect, which denotes the continuation of medium term returns (Jegadeesh and Titman, 1993, 2001). In this paper, we comprehensively explore a new dimension in firm-level momentum profitability. More precisely, we document a strong relation between expected idiosyncratic skewness and momentum profits in the cross-section of stock returns.1 The impact of skewness is economically large, statistically highly significant, holds among large firms, in the recent past, and after controlling for virtually all rm characteristics previously linked to momentum profitability (e.g. past returns, volatility, continuously arriving information, credit rating, the 52-week high or unrealized capital gains). In sum, skewness appears to be among the most important cross-sectional determinants of momentum profits.

Analyzing the relation of skewness and momentum constitutes a promising endeavour for at least the following three reasons. First, recent asset pricing models show that skewness is an important determinant of equilibrium asset returns (Barberis and Huang, 2008; Brunner- meier et al., 2007; Mitton and Vorkink, 2007; Bordalo et al., 2013), which is corroborated by empirical evidence (Boyer et al., 2010; Bali et al., 2011; Conrad et al., 2013). Thus, analyzing the interaction of skewness and known anomalies in capital markets constitutes an auspicious undertaking. Second, recent work has uncovered that the time-series of momentum returns is negatively skewed (Daniel and Moskowitz, 2014; Barroso and Santa-Clara, 2015), and we know that and momentum is pervasive (Asness et al., 2013). Therefore, as a matter of course, examining the connection between skewness and momentum in the cross-section is a natural and promising choice. Third, among academics and practitioners alike, there is an ongoing and controversial debate among the firm-level determinants of momentum (Bandarchuk and Hilscher, 2013; Asness et al., 2014).

We hypothesize that the outperformance of winners is partly driven by negative skewness, whereas the underperformance of losers in parts derives from their positive skew. If losers are on average more positively skewed than winners, then the resulting winners-losers momentum portfolio will be negatively skewed. Therefore, we conjecture that, in the cross-section, the average long-short momentum returns increase with the difference in the level of skewness of the long and short leg of the portfolio.

As a proxy for expected skewness, our baseline analysis relies on the measure proposed by Bali et al. (2011) because of its simplicity, its economic persuasiveness and its ability to predict realized skewness. This measure is calculated as the maximum daily return during the preceding month. We benchmark our findings against the profitability of the traditional momentum approach based on past return quintiles, which, after dropping small and illiquid stocks, delivers an average value-weighted monthly excess return of 0.81% (t = 4.28) in the United States over the period from January 1927 to December 2011.

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