According to present-value models, a financial valuation ratio should predict future stock returns or cash flows but empirically shows little power. This paper develops insights about stock return predictability and reconciles the contradicting findings. We decompose a financial ratio into (1) a...

This paper proposes a novel semiparametric time-varying model for long-horizon predictive regressions in which the coefficients are allowed to change over time with unspecified functional forms. A linear projection method is employed to deal with the embedded endogeneity issue. We pursue an...

We decompose earnings yield into a smoothing component and a stationary residual component to isolate the fluctuations due to variation in expected returns from those due to the change in the forecast of dividend dynamics. The residual component forms a powerful predictor of dividend growth...

This article examines the time-series predictive ability of the monthly option-implied idiosyncratic skewness (Skew) for the aggregate stock market. We find that Skew is a strong predictor of the U.S. equity premium using both in-sample and out-of-sample tests at forecast horizons up to 36...

We study the predictability of cross-sectional uncertainty (CSU) proposed by Dew-Becker and Giglio (2021) for stock returns. We find that CSU exhibits significant power for predicting monthly stock returns with annual out-of-sample R^2 of 6.34%, greater than popular predictors. CSU generates...