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Do return prediction models add economic value?

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  • Cenesizoglu, Tolga
  • Timmermann, Allan
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    Abstract

    We compare statistical and economic measures of forecasting performance across a large set of stock return prediction models with time-varying mean and volatility. We find that it is very common for models to produce higher out-of-sample mean squared forecast errors than a model assuming a constant equity premium, yet simultaneously add economic value when their forecasts are used to guide portfolio decisions. While there is generally a positive correlation between a return prediction model’s out-of-sample statistical performance and its ability to add economic value, the relation tends to be weak and only explains a small part of the cross-sectional variation in different models’ economic value.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Banking & Finance.

    Volume (Year): 36 (2012)
    Issue (Month): 11 ()
    Pages: 2974-2987

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    Handle: RePEc:eee:jbfina:v:36:y:2012:i:11:p:2974-2987

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    Web page: http://www.elsevier.com/locate/jbf

    Related research

    Keywords: Predictability of stock returns; Mean squared forecast error; Economic and statistical measures of forecasting performance;

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    References

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    Cited by:
    1. Cenedese, Gino & Sarno, Lucio & Tsiakas, Ilias, 2014. "Foreign exchange risk and the predictability of carry trade returns," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 302-313.
    2. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.

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