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)...

In this paper, we study portfolio choice problem under estimation risk and show why the 1/N rule is very difficult to beat in applications and studies. First, as long as the dimensionality is high relative to sample size, we show that the usual estimated investment strategies are biased even...

Based on intraday data for a large cross section of individual stocks, we find that the risk component of stock returns exhibits strong intraday momentum, and this pattern holds from previous market close to 10:00, and every half hour since then until market close at 16:00. Strikingly, the...

In this paper, we conduct a comprehensive study of tests for mean-variance spanning. Under the regression framework of Huberman and Kandel (1987), we provide geometric interpretations not only for the popular likelihood ratio test, but also for two new spanning tests based on the Wald and...

While macroeconomic variables have been used extensively to forecast the U.S. equity risk premium and build models to explain it, relatively little attention has been paid to the technical stock market indicators widely employed by practitioners. Our paper fills this gap by studying the...

We provide the first comprehensive analysis of option information for pricing the cross-section of stock returns by jointly examining extensive sets of firm and option characteristics. Using portfolio sorts and high-dimensional methods, we show that certain option measures have significant...

We survey the literature on stock return forecasting, highlighting the challenges faced by forecasters as well as strategies for improving return forecasts. We focus on U.S. equity premium forecastability and illustrate key issues via an empirical application based on updated data. Some studies...