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Prequential analysis of stock market returns

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  • David Bessler
  • Robert Ruffley

Abstract

The Brier score and a covariance partition due to Yates are considered to study the probabilistic forecasts of a vector autoregression on stock market returns. Probabilistic forecasts from a model and data developed by Campbell (1991) are studied with ordinary least squares. Calibration measures and the Brier score and its partition are used for model assessment. The partitions indicate that the ordinary least squares version of Campbell's model does not forecast stock market returns particularly well. While the model offers honest probabilistic forecasts (they are well-calibrated), the model shows little ability to sort events that occur into different groups from events that do not occur. The Yates-partition demonstrates this shortcoming. Calibration metrics do not.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 36 (2004)
Issue (Month): 5 ()
Pages: 399-412

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Handle: RePEc:taf:applec:v:36:y:2004:i:5:p:399-412

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  1. Campbell, John Y, 1991. "A Variance Decomposition for Stock Returns," Economic Journal, Royal Economic Society, vol. 101(405), pages 157-79, March.
  2. Francis X. Diebold & Jinyong Hahn & Anthony S. Tay, 1999. "Multivariate Density Forecast Evaluation And Calibration In Financial Risk Management: High-Frequency Returns On Foreign Exchange," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 661-673, November.
  3. Zellner, Arnold & Hong, Chansik & Min, Chung-ki, 1991. "Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 275-304.
  4. Robert J. Shiller & John Y. Campbell, 1986. "The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors," Cowles Foundation Discussion Papers 812, Cowles Foundation for Research in Economics, Yale University.
  5. Kling, John L & Bessler, David A, 1989. "Calibration-Based Predictive Distributions: An Application of Prequential Analysis to Interest Rates, Money, Prices, and Output," The Journal of Business, University of Chicago Press, vol. 62(4), pages 477-99, October.
  6. Covey, Ted & Bessler, David A, 1992. "Testing for Granger's Full Causality," The Review of Economics and Statistics, MIT Press, vol. 74(1), pages 146-53, February.
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Cited by:
  1. Casillas-Olvera, Gabriel & Bessler, David A., 2006. "Probability forecasting and central bank accountability," Journal of Policy Modeling, Elsevier, vol. 28(2), pages 223-234, February.

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