We show that the net corporate payout yield predicts both the stock market index and house prices and that the log home rent-price ratio predicts both house prices and labor income growth. We incorporate the predictability in a rich life-cycle model of household decisions involving consumption...

When using high-frequency data, the conditional CAPM can explain asset-pricing anomalies. Using conditional betas based on daily data, the model works reasonably well for a recent sample period. However, it fails to explain the size anomaly as well as 3 out of 6 of the anomaly component excess...

In a calibrated consumption-portfolio model with stock, housing, and labor income predictability, we disentangle the welfare effects of skill and luck. Skilled investors are able to take advantage of all sources of predictability, whereas unskilled investors ignore predictability. Lucky...

We revisit the apparent historical success of technical trading rules on daily prices of the DJIA index from 1897 to 2011, and use the False Discovery Rate as a new approach to data snooping. The advantage of the FDR over existing methods is that it selects more outperforming rules which allows...

Returns and cash flow growth for the aggregate U.S. stock market are highly and robustly predictable. Using a single factor extracted from the cross section of book- to-market ratios, we find an out-of-sample return forecasting R-squared as high as 13% at the annual frequency (0.9% monthly). We...

We examine the pricing of tail risk in international stock markets. Studying all MSCI Developed and Emerging Markets countries, we find that the tail risk of these countries is highly integrated. We find that both local and our newly computed global tail risk strongly predict global equity index...

We study the term structure of variance (total risk), systematic, and idiosyncratic risk. Consistent with the expectations hypothesis, we find that, for the entire market, the slope of the term structure of variance is mainly informative about the path of future variance. Thus, there is little...

Researchers and practitioners face many choices when estimating an asset's sensitivities toward risk factors, i.e., betas. Using the entire U.S. stock universe and a sample period of more than 50 years, we find that a historical estimator based on daily return data with an exponential weighting...

We conduct a comprehensive comparison of market beta estimation techniques. We study the performance of several historical, time-series model, and option implied estimators for estimating realized market beta. Thereby, we find the hybrid methodology of Buss and Vilkov (2012) to consistently...

We confront prominent asset pricing models with the classical out-of-sample cross-sectional test of Fama and MacBeth (1973). For all models, we uncover three main findings: (i) the intercept coefficients are economically large and highly statistically significant; (ii) the cross-sectional factor...