Tactical Industry Allocation and Model Uncertainty

30 Pages Posted: 2 Apr 2008

See all articles by Manuel Ammann

Manuel Ammann

University of St. Gallen - School of Finance

Michael Verhofen

University of St. Gallen - Swiss Institute of Banking and Finance; Allianz Global Investors

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Abstract

We use Bayesian model averaging to analyze industry return predictability in the presence of model uncertainty. The posterior analysis shows the importance of inflation and earnings yield in predicting industry returns. The out-of-sample performance of the Bayesian approach is, in general, superior to that of other statistical model selection criteria. However, the out-of-sample forecasting power of a naive i.i.d. forecast is similar to the Bayesian forecast. A variance decomposition into model risk, estimation risk, and forecast error shows that model risk is less important than estimation risk.

Suggested Citation

Ammann, Manuel and Verhofen, Michael, Tactical Industry Allocation and Model Uncertainty. Financial Review, Vol. 43, Issue 2, pp. 273-302, May 2008, Available at SSRN: https://ssrn.com/abstract=1115531 or http://dx.doi.org/10.1111/j.1540-6288.2008.00194.x

Manuel Ammann (Contact Author)

University of St. Gallen - School of Finance ( email )

Unterer Graben 21
St.Gallen, CH-9000
Switzerland

Michael Verhofen

University of St. Gallen - Swiss Institute of Banking and Finance ( email )

Unterer Graben 21
St. Gallen, CH-9000
Switzerland

HOME PAGE: http://www.verhofen.com

Allianz Global Investors ( email )

Frankfurt
Germany

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