This study focuses on the question whether nonlinear transformation of lagged time series values and residuals are able to systematically improve the average forecasting performance of simple Autoregressive models. Furthermore it investigates the potential superior forecasting results of a...

Do expected asset returns vary through time? Why do some assets exhibit higher average returns than others? How can factors that drive expected returns in the time series be linked to factors that explain the cross-sectional dispersion in average returns? How do these findings affect...

This paper reinterprets Maganelli's (2009) idea of "Forecasting with Judgment" to obtain a dynamic algorithm for combining survey data and time series models for macroeconomic forecasting. Unlike existing combination approaches which typically assign weights to alternative forecasts, the...