history of the asset in question. A hypothetical insurance market is set up, where competing forecasting algorithms are used …. One algorithm is used by each hypothetical agent in an "ex post ante" forecasting exercise, using the available history of … forecasting algorithms …

dividend yield is typically viewed as a reflection of either changing risk, related to the business cycle, or irrational … risk as well as expected return, we develop Bayesian methods to examine the interaction between the data and an investor … and a riskless asset. In general, however, the simple risk/return model of Merton (1980) explains very little of the yield …

This paper considers the problem of forecasting a collection of short time series using cross sectional information in … population distribution of the random coefficients. We show that the risk of a predictor based on a non-parametric kernel … estimate of the Tweedie correction is asymptotically equivalent to the risk of a predictor that treats the correlated …

We consider the problem of short-term time series forecasting (nowcasting) when there are more possible predictors than …

We study the usefulness of root tests as diagnostic tools for selecting forecasting models. Difference stationary and …

This paper considers forecasting a single time series using more predictors than there are time series observations … forecasts based on the estimated factors are efficient. In an application to forecasting U.S. inflation and industrial …