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Efficient market hypothesis and forecasting

  • Timmermann, Allan
  • Granger, Clive W. J.

The efficient market hypothesis gives rise to forecasting tests that mirror those adopted when testing the optimality of a forecast in the context of a given information set. However, there are also important differences arising from the fact that market efficiency tests rely on establishing profitable trading opportunities in ‘real time’. Forecasters constantly search for predictable patterns and affect prices when they attempt to exploit trading opportunities. Stable forecasting patterns are therefore unlikely to persist for long periods of time and will self-destruct when discovered by a large number of investors. This gives rise to nonstationarities in the time series of financial returns and complicates both formal tests of market efficiency and the search for successful forecasting approaches.

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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 20 (2004)
Issue (Month): 1 ()
Pages: 15-27

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Handle: RePEc:eee:intfor:v:20:y:2004:i:1:p:15-27
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  1. Black, Fischer, 1986. " Noise," Journal of Finance, American Finance Association, vol. 41(3), pages 529-43, July.
  2. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
  3. 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.
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  6. Josef Lakonishok, Seymour Smidt, 1988. "Are Seasonal Anomalies Real? A Ninety-Year Perspective," Review of Financial Studies, Society for Financial Studies, vol. 1(4), pages 403-425.
  7. Allan Timmermann & M. Hashem Pesaran, 2002. "Market Timing and Return Prediction under Model Instability," FMG Discussion Papers dp412, Financial Markets Group.
  8. 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.
  9. Clive W.J. Granger, 1999. "Outline of forecast theory using generalized cost functions," Spanish Economic Review, Springer, vol. 1(2), pages 161-173.
  10. 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.
  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. Douglas T. Breeden & Michael R Gibbons & Robert H. Litzenberger, . "Empirical Tests of the Consumption-Oriented CAPM," Rodney L. White Center for Financial Research Working Papers 7-89, Wharton School Rodney L. White Center for Financial Research.
  13. Hansen, Lars Peter & Singleton, Kenneth J, 1983. "Stochastic Consumption, Risk Aversion, and the Temporal Behavior of Asset Returns," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 249-65, April.
  14. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-617, December.
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  16. Harrison, J. Michael & Kreps, David M., 1979. "Martingales and arbitrage in multiperiod securities markets," Journal of Economic Theory, Elsevier, vol. 20(3), pages 381-408, June.
  17. Timmermann, Allan G, 1993. "How Learning in Financial Markets Generates Excess Volatility and Predictability in Stock Prices," The Quarterly Journal of Economics, MIT Press, vol. 108(4), pages 1135-45, November.
  18. Jensen, Michael C., 1978. "Some anomalous evidence regarding market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 95-101.
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