Skewness in Expected Macro Fundamentals and the Predictability of Equity Returns: Evidence and Theory

Abstract

We document that the first and third cross-sectional moments of the distribution of GDP growth rates made by professional forecasters can predict equity excess returns, a finding which is robust to controlling for a large set of well established predictive factors. We show that introducing time-varying skewness in the distribution of expected growth prospects in an otherwise standard endowment economy can substantially increase the model implied equity Sharpe ratios, and produce a large amount of fluctuation in equity risk premia.

Disasters Everywhere: The Costs of Business Cycles Reconsidered

“…Our results apply to peacetime advanced economies, a sample considered exempt from the more frequent dislocations seen in emerging markets or wartime eras. Our finding ties into recent research on the importance of skewness for macro and finance puzzles (Colacito, Ghysels, Meng, and Siwasarit, 2016;Dew-Becker, Tahbaz-Salehi, and Vedolin, 2019) as well as the micro skewness underpinnings at the firm or household level (Busch, Domeij, Guvenen, and Madera, 2018;Salgado, Guvenen, and Bloom, 2019). In this research, skewness is a general phenomenon present at all times, not just in disaster episodes.…”

Aggregate Skewness and the Business Cycle

“…prices, labor market indicators and financial variables) and ii) understand which variables contribute most to overall skewness. 2 The common skewness factor is strongly procyclical and explains only a limited 1 Theoretical and empirical contributions highlighting the role of time-varying skewness include, for example, Colacito et al (2016), Dew-Becker et al (2019), Jensen et al (2020) and Fève et al (2021) at the macro level, and Busch et al (2018), Salgado et al (2019), andDew-Becker (2022) at the micro level. 2 The simple and transparent derivation of our expected skewness factor allows to update it seamlessly and monthly updates can be downloaded from the authors' websites.…”

Uncertainty and the predictability of stock returns

“…While most of aforementioned studies focus on in-sample tests, an influential paper by Goyal and Welch (2008) shows that it is difficult to find significant out-of-sample return predictability using a single predictor. A branch of studies has subsequently identified new variables that provide predictive content for stock returns, such as short interest (Rapach et al, 2016), variance risk premia (Bollerslev et al, 2009), oil price changes (Driesprong et al, 2008), technical indicators (Neely et al, 2014), news implied volatility (Manela & Moreira, 2017), economic policy uncertainty Brogaard and Detzel (2015), aligned investor sentiment (Huang et al, 2015), and skewness in expected macro fundamentals (Colacito et al, 2016). We focus on the traditional fundamentals suggested by Goyal and Welch (2008) because the data are broad enough to test our method and are most widely used in the literature.…”