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Forecast accuracy after pretesting with an application to the stock market

  • Jan R. Magnus

    (CentER, Tilburg University, The Netherlands)

  • Dmitry Danilov

    (Eurandom, Eindhoven University of Technology, The Netherlands)

In econometrics, as a rule, the same data set is used to select the model and, conditional on the selected model, to forecast. However, one typically reports the properties of the (conditional) forecast, ignoring the fact that its properties are affected by the model selection (pretesting). This is wrong, and in this paper we show that the error can be substantial. We obtain explicit expressions for this error. To illustrate the theory we consider a regression approach to stock market forecasting, and show that the standard predictions ignoring pretesting are much less robust than naive econometrics might suggest. We also propose a forecast procedure based on the 'neutral Laplace estimator', which leads to an improvement over standard model selection procedures. Copyright © 2004 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.916
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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 23 (2004)
Issue (Month): 4 ()
Pages: 251-274

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Handle: RePEc:jof:jforec:v:23:y:2004:i:4:p:251-274
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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  1. Balvers, Ronald J & Cosimano, Thomas F & McDonald, Bill, 1990. " Predicting Stock Returns in an Efficient Market," Journal of Finance, American Finance Association, vol. 45(4), pages 1109-28, September.
  2. Abadir, K.M. & Magnus, J.R., 2001. "Notation in Econometrics : A Proposal for a Standard," Discussion Paper 2001-8, Tilburg University, Center for Economic Research.
  3. Danilov, D.L. & Magnus, J.R., 2001. "On the Harm that Pretesting Does," Discussion Paper 2001-37, Tilburg University, Center for Economic Research.
  4. Jan R. Magnus, 2002. "Estimation of the mean of a univariate normal distribution with known variance," Econometrics Journal, Royal Economic Society, vol. 5(1), pages 225-236, June.
  5. Fama, Eugene F & French, Kenneth R, 1992. " The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-65, June.
  6. Jan R. Magnus & J. Durbin, 1999. "Estimation of Regression Coefficients of Interest When Other Regression Coefficients Are of No Interest," Econometrica, Econometric Society, vol. 67(3), pages 639-644, May.
  7. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
  8. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
  9. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-36, May-June.
  10. Danilov, D.L. & Magnus, J.R., 2002. "Estimation of the Mean of a Univariate Normal Distribution When the Variance is not Known," Discussion Paper 2002-77, Tilburg University, Center for Economic Research.
  11. Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
  12. 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.
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