Can the degree of predictability found in the data be explained by existing asset pricing models? We provide two theoretical upper bounds on the R-squares of predictive regressions. Using data on the market and component portfolios, we find that the empirical R-squares are significantly greater...

We propose a novel measure of the ex-ante commodity downside-risk premium (CDP) for each commodity based on a term structure model of commodity futures. Our theory-based CDP, capturing forward-looking information in the futures markets, outperforms well-known characteristics in explaining the...

We show that the conditional risk estimation in the ICAPM model (Merton, 1973) should contain the unspanned uncertainty beyond stock market if the interest rate is not sufficient to describe the dynamic investment state. Borrowing an aggregated uncertainty measure that captures unspanned...

In this paper, we propose a cross-sectional option momentum strategy that is based on the risk component of delta-hedged option returns. We find strong evidence of risk continuation in option returns. Specifically, options with a high risk component significantly outperform those with a low risk...

We establish the out-of-sample predictability of monthly exchange rate changes via machine learning techniques based on 70 predictors capturing country characteristics, global variables, and their interactions. To guard against overfitting, we use the elastic net to estimate a high-dimensional...

We investigate an important question for institutional investors — namely, which hedge fund investing styles help to hedge against bad times? We define good versus bad times as (1) up and down equity market regimes derived from the 200-day moving average of the S&P 500 price index or (2)...