In most games, for equilibrium to result, players need to forecast the equilibrium strategies of others. We elicit forecasts of outcomes in a series of hawk-dove (aka chicken) games played by other players. We ask whether these forecasts are consistent with any correlated equilibrium of a class...

I introduce a new framework to study environments with both structural and strategic uncertainty, different from Harsanyi's (1967-8) `Bayesian games', that allows a researcher to test the robustness of Nash predictions while maintaining certain desirable restrictions on players' beliefs. The...

Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...

In this paper we investigate the predictive power of cross-sectional volatility, skewness and kurtosis for future stock returns. Adding to the work of Maio (2016), who finds cross-sectional volatility to forecast a decline in the equity premium with high predictive power in-sample as well as...

In this paper, I argue that we can use consumer and investor perceptions to forecast short-term fluctuations in asset prices. Using tweets scraped from Twitter between 2009 and 2019, I perform textual analysis to construct daily sentiment indices. While other scholars have relied on third-party...

In this paper, we document evidence that downside betas tend to comove more than upside betas during a financial crisis, but upside betas tend to comove more than the downside betas during financial booms. We find that the asymmetry between Downside-Beta Comovement and Upside-Beta Comovement is...

This paper examines the cross-sectional properties of stock return forecasts based on Fama-MacBeth regressions using all firms contained in the STOXX Europe 600 index during the September 1999-December 2018 period. Our estimation approach is strictly out-of-sample, mimicking an investor who...

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...

We provide a short and selected review of the vast literature on cross-section predictability. We focus on the state of art methods used to forecast the cross-section of stock returns with major predictors and are primarily interested in the ideas, methods, and their applications. To understand...

I propose to forecast the market returns through its constituents. In contrast to the voluminous literature that concentrates on the predictive power of aggregate cross-sectional or macroeconomic predictors, I analyze the return predictability of sub-portfolios that compose the market portfolio....