The limit distribution of conventional test statistics for predictability may depend on the degree of persistence of the predictors. Therefore, diverging results and conclusions may arise because of the different asymptotic theories adopted. Using differencing transformations, we introduce a new...

This paper develops parameter instability and structural change tests within predictive regressions for economic systems governed by persistent vector autoregressive dynamics. Specifically, in a setting where all – or a subset – of the variables may be fractionally integrated and the...

Chen and Deo (2009a) proposed procedures based on restricted maximum likelihood (REML) for estimation and inference in the context of predictive regression. Their method achieves bias reduction in both estimation and inference which assists in overcoming size distortion in predictive hypothesis...

Multi-step-ahead forecasts of forecast uncertainty in practice are often based on the horizon-specific sample means of recent squared forecast errors, where the number of available past forecast errors decreases one-to-one with the forecast horizon. In this paper, the efficiency gains from the...

The contour map of estimation error of Expected Shortfall (ES) is constructed. It allows one to quantitatively determine the sample size (the length of the time series) required by the optimization under ES of large institutional portfolios for a given size of the portfolio, at a given...

We demonstrate that annual peak demand days are characterized by both extreme values of predictors (such as weather) and large unpredictable "shocks" to demand. OLS approaches incorporate the former feature, but not the latter, leading OLS to produce downwardly-biased estimates of the annual...