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Model Uncertainty, Thick Modelling and the Predictability of Stock Returns Author info | Abstract | Publisher info | Download info | Related research | Statistics Aiolfi, Marco
Favero, Carlo A
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Recent financial research has provided evidence on the predictability of asset returns. In this Paper we consider the results contained in Pesaran-Timmerman (1995), which provided evidence on predictability of excess returns in the US stock market over the sample 1959-92. We show that the extension of the sample to the nineties weakens considerably the statistical and economic significance of the predictability of stock returns based on earlier data. We propose an extension of their framework, based on the explicit consideration of model uncertainty under rich parameterizations for the predictive models. We propose a novel methodology to deal with model uncertainty based on ‘thick’ modelling, i.e. considering a multiplicity of predictive models rather than a single predictive model. We show that portfolio allocations based on a thick modeling strategy systematically outperform thin modelling.
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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number
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Date of creation: Aug 2003Date of revision:
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Find related papers by JEL classification: C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
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