Average skewness, which is defined as the average of monthly skewness values across firms, performs well at predicting future market returns. This result still holds after controlling for the size or liquidity of the firms or for current business cycle conditions. We also find that average...

Using Indian bank-level data, we examine the cross-sectional returns predictability for banking stocks in view of the distinct industry parameters prevalent in the financial services space. We find the existence of abnormal returns in banking stocks. We also observe that the celebrated...

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...

The Baker and Wurgler (2006) sentiment index purports to measure irrational investor sentiment, while the University of Michigan Consumer Sentiment Index is designed to largely reflect fundamentals. Removing this fundamental component from the Baker and Wurgler index creates an index of investor...

The estimation of expected security returns is one of the major tasks for the practical implementation of the Markowitz portfolio optimization. Against this background, in 1992 Black and Litterman developed an approach based on (theoretically established) expected equili-brium returns which...

I derive two valid forecasting models of the equity premium in monthly frequency, based on little more than no-arbitrage: A "predictability timing" version of partial least squares, given that predictability is theoretically time-varying; and a least squares model with realized market premiums...

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....

We construct a global implied volatility surface by combining information from the index options of twenty countries and regions. The convexity of the global surface positively predicts equity premia around the world, in- and out-of-sample, at horizons from one to twelve months. Semi-annually,...

We examine the potential of ChatGPT, and other large language models, in predicting stock market returns using sentiment analysis of news headlines. We use ChatGPT to indicate whether a given headline is good, bad, or irrelevant news for firms' stock prices. We then compute a numerical score and...

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...