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...

This paper provides a comprehensive analysis of price effects after one-day abnormal returns and their evolution in the US stock market for the case of Dow Jones Index over the period 1890-2018. Using different statistical tests (both parametrical and non-parametrical) as well as additional...

This article attempts to examine whether the equity premium in the United States can be predicted from a com-prehensive set of 18 economic and financial predictors over a monthly out-of-sample period of 2000:2 to 2011:12, using an in-sample period of 1990:2-2000:1. To do so, we consider, in...

This article attempts to examine whether the equity premium in the United States can be predicted from a comprehensive set of 18 economic and financial predictors over a monthly out-of-sample period of 2000:2 to 2011:12, using an in-sample period of 1990:2-2000:1. To do so, we consider, in...