Stock and Bond Return Predictability : The Discrimination Power of Model Selection Criteria
AbstractWe 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).
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Bibliographic InfoPaper provided by Département des Sciences Économiques, Université de Genève in its series Research Papers by the Department of Economics, University of Geneva with number 2004.05.
Length: 25 pages
Date of creation: Jun 2004
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-09-05 (All new papers)
- NEP-ECM-2004-09-05 (Econometrics)
- NEP-FIN-2004-09-05 (Finance)
- NEP-FMK-2004-09-05 (Financial Markets)
- NEP-RMG-2004-09-05 (Risk Management)
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- K. J. Martijn Cremers, 2002. "Stock Return Predictability: A Bayesian Model Selection Perspective," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1223-1249.
- Christoffersen & Diebold, .
"Further Results on Forecasting and Model Selection Under Asymmetric Loss,"
_059, University of Pennsylvania.
- Christoffersen, Peter F & Diebold, Francis X, 1996. "Further Results on Forecasting and Model Selection under Asymmetric Loss," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 561-71, Sept.-Oct.
- Campbell, John, 1987.
"Stock Returns and the Term Structure,"
3207699, Harvard University Department of Economics.
- Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
- Pesaran, M. H. & Timmermann, A., 1996.
"A Recursive Modelling Approach to Predicting UK Stock Returns',"
Cambridge Working Papers in Economics
9625, Faculty of Economics, University of Cambridge.
- Pesaran, M Hashem & Timmermann, Allan, 2000. "A Recursive Modelling Approach to Predicting UK Stock Returns," Economic Journal, Royal Economic Society, vol. 110(460), pages 159-91, January.
- Allan Timmermann & M. Hashem Pesaran, 1999. "A Recursive Modelling Approach to Predicting UK Stock Returns," FMG Discussion Papers dp322, Financial Markets Group.
- Carlo A. Favero & Marco Aiolfi & Giorgio Primiceri, . "Recursive `thick´ modeling of excess returns and portfolio allocation," Working Papers 197, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
- Donald B. Keim & Robert F. Stambaugh, .
"Predicting Returns in the Stock and Bond Markets,"
Rodney L. White Center for Financial Research Working Papers
15-85, Wharton School Rodney L. White Center for Financial Research.
- Brock, W. & Lakonishok, J. & Lebaron, B., 1991.
"Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns,"
90-22, Wisconsin Madison - Social Systems.
- Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-64, December.
- Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
- Granger, Clive W. J. & Jeon, Yongil, 2004. "Thick modeling," Economic Modelling, Elsevier, vol. 21(2), pages 323-343, March.
- Granger, C.W.J. & Pesaran, H., 1996. "A Decision_Theoretic Approach to Forecast Evaluation," Cambridge Working Papers in Economics 9618, Faculty of Economics, University of Cambridge.
- Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, vol. 68(5), pages 1097-1126, September.
- 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 405-28.
- David Hendry & Michael Clements, 2001.
"Pooling of Forecasts,"
Economics Series Working Papers
2002-W09, University of Oxford, Department of Economics.
- Pesaran, M. H. & Weeks, M., 1999. "Non-nested Hypothesis Testing: An Overview," Cambridge Working Papers in Economics 9918, Faculty of Economics, University of Cambridge.
- Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
- Arnulfo Rodríguez & Pedro N. Rodríguez, 2007. "Recursive Thick Modeling and the Choice of Monetary Policy in Mexico," Working Papers 2007-04, Banco de México.
- 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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