Model Uncertainty, Thick Modelling and the predictability of Stock Returns

Marco Aiolfi and Carlo Favero ()

No 221, Working Papers from IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University

Abstract: Recent financial research has provided evidence on the predictability of asset returns. In this paper we consider the results contained in Pesaran-Timmerman (1995), hich provided evidence on predictability over the sample 1959-1992. We show that the extension of the sample to the ninetieth 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´´ modeling, i.e. on considering a multiplicity of predictive models rather than a single predictive model. We show that portfolio allocations based on a thick modelling strategy sistematically overperforms thin modelling.

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Working Paper: Model Uncertainty, Thick Modelling and the Predictability of Stock Returns (2003)
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