We analyze the daily predictability of investor sentiment across four major asset classes and compare sentiment measures based on news and social media with those based on trade information. For the majority of assets, trade-based sentiment measures outperform their text-based equivalents for...

We provide the first comprehensive analysis of options-implied information for predicting 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 only few option characteristics...

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 provide the asymptotic theory for the widely used Fama and MacBeth (1973) two-pass regression in the usual case of a large number of assets. We find that the convergence of the OLS two-pass estimator depends critically on the time series sample size in addition to the number of...

We show that short interest is arguably the strongest known predictor of aggregate stock returns. It outperforms a host of popular return predictors both in and out of sample, with annual r-squared statistics of 12.89% and 13.24%, respectively. In addition, short interest can generate utility...

In this paper, motivated by existing and growing evidence on multiple macroeconomic volatilities, we extend the long-run risks model of Bansal and Yaron (2004) by allowing both a long- and a short-run volatility components in the evolution of economic fundamentals. With this extension, the new...

Stock market predictability is of considerable interest in both academic research and investment practice. Ross (2005) provides a simple and elegant upper bound on the predictive regression R-squared that R^2 = (1 R_f)^2 Var(m) for a given asset pricing model with kernel m, where R_f is the...