Researchers and practitioners employ a variety of time-series processes to forecast betas, using either short-memory models or implicitly imposing infinite memory. We find that both approaches are inadequate: beta factors show consistent long-memory properties. For the vast majority of stocks,...

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...

This paper examines the properties of the gold risk premium. We estimate a parsimonious model for the gold risk premium and uncover important time variations in the dynamics of the risk premium. We also estimate risk premia of the stock and bond markets, and investigate the role of gold as a...

Researchers and practitioners face many choices when estimating an asset's sensitivities toward risk factors, i.e., betas. We study the effect of different data sampling frequencies, forecast adjustments, and model combinations for beta estimation. Using the entire U.S. stock universe and a...

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...

We examine the pricing of tail risk in international stock markets. We find that the tail risk of different countries is highly integrated. Introducing a new World Fear index, we find that local and global aggregate market returns are mainly driven by global tail risk rather than local tail...

Researchers and practitioners employ a variety of time-series processes to forecast betas, using either short-memory models or implicitly imposing infinite memory. We find that both approaches are inadequate: beta factors show consistent long-memory properties. For the vast majority of stocks,...

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...

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...