This paper explores whether firm characteristics matter in determining the effect of investor herding on asset returns. We find that the level of herding alone does not command a significant effect on industry returns, implied by insignificant return spreads between industries that experience...

This paper proposes an iterative model-building approach known as quantile boosting to trace out the predictive value of realized volatility and skewness for gold futures returns. Controlling for several widely studied market- and sentiment-based variables, we examine the predictive value of...

Yes, they do. Utilizing a machine-learning technique known as random forests to compute forecasts of realized (good and bad) stock market volatility, we show that incorporating the information in lagged industry returns can help improve out-of sample forecasts of aggregate stock market...