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Economic and Statistical Measures of Forecast Accuracy

  • Granger, C.W.J.
  • Pesaran, M. H.

This paper argues in favour of a closer link between decision and forecast evaluation problems. Although the idea of using decision theory for forecast evaluation appears early in the dynamic stochastic programming literature, and has continued to be used in meteorological forecasts, it is hardly mentioned in standard academic textbooks on economic forecasting. Some of the main issues involved are illustrated in the context of a two-state, two-action decision problem as well as in a more general setting. Relationships between statistical and economic methods of forecast evaluation are discussed and useful links between Kuipers score, used as a measure of forecast accuracy in the meteorology literature, and the market timing tests used in finance, are established. An empirical application to the problem of stock market predictability is also provided, and the conditions under which such predictability could be exploited in the presence of transaction costs are discussed.

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Paper provided by Faculty of Economics, University of Cambridge in its series Cambridge Working Papers in Economics with number 9910.

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Date of creation: May 1999
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Handle: RePEc:cam:camdae:9910
Contact details of provider: Web page: http://www.econ.cam.ac.uk/index.htm

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  1. John Y. Campbell & Luis M. Viceira, 1998. "Consumption and Portfolio Decisions When Expected Returns Are Time Varying," Harvard Institute of Economic Research Working Papers 1835, Harvard - Institute of Economic Research.
  2. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  3. Pesaran, M Hashem & Timmermann, Allan, 1992. "A Simple Nonparametric Test of Predictive Performance," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(4), pages 561-65, October.
  4. Christoffersen & Diebold, . "Further Results on Forecasting and Model Selection Under Asymmetric Loss," Home Pages _059, University of Pennsylvania.
  5. Pesaran, M.H. & Timmermann, A., 1992. "Forecasting Stock Returns," Cambridge Working Papers in Economics 9216, Faculty of Economics, University of Cambridge.
  6. Campbell, John Y., 1987. "Stock returns and the term structure," Journal of Financial Economics, Elsevier, vol. 18(2), pages 373-399, June.
  7. Weiss, Andrew A, 1996. "Estimating Time Series Models Using the Relevant Cost Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 539-60, Sept.-Oct.
  8. Michael P. Clements & David F. Hendry, 2001. "Forecasting Non-Stationary Economic Time Series," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262531895, June.
  9. Granger, Clive W. J., 1992. "Forecasting stock market prices: Lessons for forecasters," International Journal of Forecasting, Elsevier, vol. 8(1), pages 3-13, June.
  10. 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.
  11. Clare, A D & Thomas, S H & Wickens, M R, 1994. "Is the Gilt-Equity Yield Ratio Useful for Predicting UK Stock Returns?," Economic Journal, Royal Economic Society, vol. 104(423), pages 303-15, March.
  12. Kenneth D. West & Hali J. Edison & Dongchul Cho, 1993. "A utility based comparison of some models of exchange rate volatility," International Finance Discussion Papers 441, Board of Governors of the Federal Reserve System (U.S.).
  13. Black, Angela & Fraser, Patricia, 1995. "U.K. Stock Returns: Predictability and Business Conditions," The Manchester School of Economic & Social Studies, University of Manchester, vol. 63(0), pages 85-102, Suppl..
  14. 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.
  15. repec:cup:cbooks:9780521634809 is not listed on IDEAS
  16. 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.
  17. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-90, June.
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