Do return prediction models add economic value?

Tolga Cenesizoglu and Allan Timmermann

Journal of Banking & Finance, 2012, vol. 36, issue 11, 2974-2987

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.

Keywords: Predictability of stock returns; Mean squared forecast error; Economic and statistical measures of forecasting performance (search for similar items in EconPapers)
JEL-codes: G11 G14 G17 (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (93)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:36:y:2012:i:11:p:2974-2987

DOI: 10.1016/j.jbankfin.2012.06.008

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