We test whether three well-known commodity-specific variables (basis, hedgingpressure, and momentum) may improve the predictive power for commodity futuresreturns of models otherwise based on macroeconomic factors. We compute recursive,out-of-sample forecasts for fifteen monthly commodity...

We use monthly data on the US riskless yield curve for a 1982-2015 sample to show that mixing simple regime switching dynamics with Nelson-Siegel factor forecasts from time series models extended to encompass variables that summarize the state of monetary policy, leads to superior predictive...

This paper systematically investigates the sources of differential out-of-sample predictive accuracy of heuristic frameworks based on internet search frequencies and a large set of econometric models. The volume of internet searches helps gauge the degree of investors' time-varying interest in...

We study the recursive, out-of-sample realized predictive performance of a rich set of predictor choices and models, spanning linear and Markov switching frameworks when the forecast target is represented by excess NCREIF and equity NAREIT returns. We find considerable pockets of predictive...

Intro; Title page; Table of Contents; Copyright; List of Figures; List of Tables; Preface; Chapter 1. Linear Regression Model; Abstract; 1.1 Inference in Linear Regression Models; 1.2 Testing for Violations of the Linear Regression Framework; 1.3 Specifying the Regressors; 1.4 Issues With...