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...

This paper proposes a two-state predictive regression model and shows that stock market 12-month return (TMR), the time-series momentum predictor of Moskowitz, Ooi, and Pedersen (2012), forecasts the aggregate stock market negatively in good times and positively in bad times. The out-of-sample...

This study analyses point forecasts of exact scoreline outcomes for football matches in the English Premier League. These forecasts were made for distinct competitions and originally judged differently. We compare these with implied probability forecasts using bookmaker odds and a crowd of...

We analyze the joint out-of-sample predictive ability of a comprehensive set of 299 firm characteristics for cross-sectional stock returns. We develop a cross-sectional out-of-sample R2 statistic that provides an informative measure of the accuracy of cross-sectional return forecasts in terms of...

We measure the information content of monthly analyst consensus forecasts for one-year-forward earnings per share (EPS) based on two well-established price discovery measures drawn from the area of market micro-structure research. Employing a 36-year sample of large US companies listed in the...

Asset allocation is critically dependent on the ability to forecast the equity risk premium (ERP) out-of-sample. But, is superior econometric predictability across the business cycle synonymous to predictability at all times? We evaluate recently introduced ERP forecasting models, which have...

We use sequential energy inventory announcements to shed new light on the informational efficiency of financial markets. Our findings provide clear evidence of inefficiency in crude oil futures and stock markets. This inefficiency can be exploited by sophisticated traders. We examine the effect...

This paper examines the role of information from the options market in forecasting the equity premium. We provide empirical evidence that the equity premium is predictable out-of-sample using a set of CBOE strategy benchmark indices as predictors. We use a range of econometric approaches to...

This paper reviews research that uses big data and/or machine learning methods to provide insight relevant for equity valuation. Given the huge volume of research in this area, the review focuses on studies that either use or inform on accounting variables. The article concludes by providing...

Asset returns change with fundamentals and other factors, such as technical information and sentiment over time. In modeling time-varying expected returns, this article focuses on the out-of-sample predictability of the aggregate stock market return via extensions of the conventional predictive...