We provide a model-free test for asymmetric correlations in which stocks move more often with the market when the market goes down than when it goes up, and also provide such tests for asymmetric betas and covariances. When stocks are sorted by size, book-to-market, and momentum, we find strong...

We examine how many factors out of a wide range of 207 that have incremental information in explaining cross-sectional stock returns. First, we find that the significance of each factor changes drastically over time. After accounting for false-discovery (FDR), only 157 out of 207 factors are...

We provide an entropy approach for measuring asymmetric comovement between the return on a single asset and the market return. This approach yields a model-free test for stock return asymmetry, generalizing the correlation-based test proposed by Hong, Tu, and Zhou (2007). Based on this test, we...

Starting from the twelve distinct risk factors in four well-established asset pricing models, a pool we refer to as the winners, we construct and compare 4,095 asset pricing models and find that the model with the risk factors, Mkt, SMB, MOM, ROE, MGMT, and PEAD, performs the best in terms of...

We investigate whether firm fundamentals can explain the shape of option implied volatility (IV)curve. Extending Geske's (1977) compound option model, we link firm fundamentals to the IV curvetheoretically. Using options on all available US-listed companies, we find empirically that...

For the popular mean-variance portfolio choice problem in the case without a risk-free asset, we develop a new portfolio strategy to mitigate estimation risk. We show that in both calibrations and real datasets, optimally combining the sample global minimum variance portfolio with a sample...

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)...

Using time-series trends of a set of firms' major fundamentals, we find that there is a fundamentalmomentum in the stock market. Buying stocks in the top quintile of fundamental trends and selling stocks in the bottom quintile earns a monthly average return of 0.88%, whose magnitude is...