Does the macroeconomy predict UK asset returns in an nonlinear fashion? Comprehensive out-of-sample evidence - Massimo Guidolin; Stuart Hyde; David McMillan; Sadayuki Ono (The University of Manchester, Manchester Business School, 2010)
We perform a comprehensive examination of the recursive, comparative predictive performance of a number of linear and non-linear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STR) regime switching models, and a range of linear specifications in addition to univariate models in which conditional heteroskedasticity is captured by GARCH type specifications and in which predicted volatilities appear in the conditional mean. The results demonstrate that U.K. asset returns require non-linear dynamics be modeled. In particular, the evidence in favour of adopting a Markov switching framework is strong. Our results appear robust to the choice of sample period, changes in the adopted loss function and to the methodology employed to test the null hypothesis of equal predictive accuracy across competing models.
Keywords: C53; E44; G12; C32; 330; regime switching; threshold; smooth transition; predictive regressions; forecasting