We address one interesting case — the predictability of excess US asset returns from macroeconomic factors within a flexible regime switching VAR framework — in which the presence of regimes may lead to superior forecasting performance from forecast combinations. After having documented that forecast combinations provide gains in prediction accuracy and these gains are statistically significant, we show that combinations may substantially improve portfolio selection. We find that the best-performing forecast combinations are those that either avoid estimating the pooling weights or that minimize the need for estimation. In practice, we report that the best-performing combination schemes are based on the principle of relative, past forecasting performance. The economic gains from combining forecasts in portfolio management applications appear to be large, stable over time, and robust to the introduction of realistic transaction costs.

The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns

GUIDOLIN, MASSIMO;
2008

Abstract

We address one interesting case — the predictability of excess US asset returns from macroeconomic factors within a flexible regime switching VAR framework — in which the presence of regimes may lead to superior forecasting performance from forecast combinations. After having documented that forecast combinations provide gains in prediction accuracy and these gains are statistically significant, we show that combinations may substantially improve portfolio selection. We find that the best-performing forecast combinations are those that either avoid estimating the pooling weights or that minimize the need for estimation. In practice, we report that the best-performing combination schemes are based on the principle of relative, past forecasting performance. The economic gains from combining forecasts in portfolio management applications appear to be large, stable over time, and robust to the introduction of realistic transaction costs.
2008
9780444529428
David E. Rapach, Mark E. Wohar
Forecasting in the Presence of Structural Breaks and Model Uncertainty
Guidolin, Massimo; C. F., Na
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/3719735
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