Consensus professional forecasts of stock returns are three times more volatile than those of non-professionals and econometricians. This "excess" volatility in professional forecasts is not due to noise. Rather, professional forecasts respond immediately, strongly, and countercyclically to...

"We consider various MIDAS (Mixed Data Sampling) regression models to predict volatility. The models differ in the specification of regressors (squared returns, absolute returns, realized volatility, realized power, and return ranges), in the use of daily or intra-daily (5-minute) data, and in...

We propose a new approach to imposing economic constraints on forecasts of the equity premium. Economic constraints are used to modify the posterior distribution of the parameters of the predictive return regression in a way that better allows the model to learn from the data. We consider two...