A stock's exposure to systematic risk factors is surrounded by substantial uncertainty. This beta uncertainty is both economically and statistically significantly priced in the cross-section of stock returns. Stocks with high beta uncertainty substantially under-perform those with low beta...

By studying 81 countries over a period of up to 144 years, with different classes of predictor variables and various forecast specifications, we conduct the most comprehensive equity premium predictability analysis to date. We find that excess returns are more predictable in Emerging and...

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...

This paper investigates price jumps in commodity markets. We find that jumps are rare and extreme events but occur less frequently than in stock markets. Nonetheless, jump correlations across commodities can be high depending on the commodity sectors. Energy, metal and grains commodities show...

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...

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...

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...

For centuries, Jews have been associated with financial services. We find that present-day households in German counties where Jewish persecution was higher in the Middle Ages and the Nazi period invest less in stocks, have lower savings in bank deposits, and are less likely to get a mortgage,...

This paper evaluates the predictive performance of machine learning techniques in estimating time-varying betas of US stocks. Compared to established estimators, tree-based models and neural networks outperform from both a statistical and an economic perspective. Random forests perform the best...