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Asymptotic Inference About Predictive Ability: Additional Appendix

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  • West, K.D.

Abstract

smooth functions of out of sample predictions and prediction errors, when there is a long time series of predictions and realizations, and each prediction is based on regression parameters estimated from a long time series. The aim is to provide tools for inference about predictive accuracy and efficiency, and, more generally, about predictive ability. The paper allows for nonlinear models and estimators, as well as for possible dependence of predictions and prediction errors on estimated regression parameters. Simulations indicate that the procedures work well. This additional appendix contains material omitted from the body of the paper to save space; additional simulation results, proofs, and additional references.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • West, K.D., 1994. "Asymptotic Inference About Predictive Ability: Additional Appendix," Working papers 9418, Wisconsin Madison - Social Systems.
  • Handle: RePEc:att:wimass:9418
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    Cited by:

    1. Mayer, Walter J. & Liu, Feng & Dang, Xin, 2017. "Improving the power of the Diebold–Mariano–West test for least squares predictions," International Journal of Forecasting, Elsevier, vol. 33(3), pages 618-626.
    2. Lin, Wen-Ling, 1995. "Market closure and predictability of intradaily stock returns in the United States and Japan," Journal of Empirical Finance, Elsevier, vol. 2(1), pages 19-44, March.
    3. Barbara Rossi & Atsushi Inoue, 2012. "Out-of-Sample Forecast Tests Robust to the Choice of Window Size," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 432-453, April.
    4. Rossi, Barbara & Sekhposyan, Tatevik, 2011. "Understanding models' forecasting performance," Journal of Econometrics, Elsevier, vol. 164(1), pages 158-172, September.
    5. Chinn, Menzie D. & Meese, Richard A., 1995. "Banking on currency forecasts: How predictable is change in money?," Journal of International Economics, Elsevier, vol. 38(1-2), pages 161-178, February.

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    Keywords

    econometrics;

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