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Stock and Bond Return Predictability : The Discrimination Power of Model Selection Criteria

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  • Rosario Dell'Aquila
  • Elvezio Ronchetti

Abstract

We analyze the discrimination power of well-known model selection criteria when R2 is low as in typical asset return predictability studies. We find that the discrimination power is low in this setup and in particular give another interpretation to the well-cited Bossaerts and Hillion (1999) study. We then look at model selection criteria in a testing framework and propose, as a diagnostic tool, a bootstrap based procedure to construct the class of models which are statistically undistinguishable from the best model chosen by a model selection criterion. As an empirical illustration we reanalyze the Pesaran and Timmerman (1995) results and show that the class of undistiguishable models can be large. Finally we show that the similar problems arise in a more hidden way in the context of recent model uncertainty studies such as the Bayesian model selection criteria proposed by Avramov (2002) and Cremers (2002).

Suggested Citation

  • Rosario Dell'Aquila & Elvezio Ronchetti, 2004. "Stock and Bond Return Predictability : The Discrimination Power of Model Selection Criteria," Research Papers by the Institute of Economics and Econometrics, Geneva School of Economics and Management, University of Geneva 2004.05, Institut d'Economie et Econométrie, Université de Genève.
  • Handle: RePEc:gen:geneem:2004.05
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    1. Carlo A. Favero & Marco Aiolfi & Giorgio Primiceri, "undated". "Recursive `thick´ modeling of excess returns and portfolio allocation," Working Papers 197, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    2. Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-191, January.
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    4. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
    5. Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-428.
    6. Foster, F Douglas & Smith, Tom & Whaley, Robert E, 1997. " Assessing Goodness-of-Fit of Asset Pricing Models: The Distribution of the Maximal R-Squared," Journal of Finance, American Finance Association, vol. 52(2), pages 591-607, June.
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    Cited by:

    1. Arnulfo Rodríguez & Pedro N. Rodríguez, 2007. "Recursive Thick Modeling and the Choice of Monetary Policy in Mexico," Working Papers 2007-04, Banco de México.
    2. Arnulfo Rodriguez & Pedro N. Rodriguez, 2006. "Recursive Thick Modeling and the Choice of Monetary Policy in Mexico," Computing in Economics and Finance 2006 30, Society for Computational Economics.

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