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Out-of-sample forecast tests robust to the choice of window size

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  • Barbara Rossi
  • Atsushi Inoue

Abstract

This paper proposes new methodologies for evaluating out-of-sample forecasting performance that are robust to the choice of the estimation window size. The methodologies involve evaluating the predictive ability of forecasting models over a wide range of window sizes. The authors show that the tests proposed in the literature may lack the power to detect predictive ability and might be subject to data snooping across different window sizes if used repeatedly. An empirical application shows the usefulness of the methodologies for evaluating exchange rate models' forecasting ability.

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Bibliographic Info

Paper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 11-31.

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Date of creation: 2011
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Handle: RePEc:fip:fedpwp:11-31

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Keywords: Forecasting;

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References

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Citations

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Cited by:
  1. Rossi, José Luiz Júnior, 2013. "Liquidity and Exchange Rates," Insper Working Papers, Insper Working Paper, Insper Instituto de Ensino e Pesquisa wpe_325, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
  2. Christophe Amat & Tomasz Michalski & Gilles Stoltz, 2014. "Forecasting exchange rates better than the random walk thanks to machine learning techniques," Working Papers, HAL halshs-01003914, HAL.
  3. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper Series, The Rimini Centre for Economic Analysis 66_13, The Rimini Centre for Economic Analysis.
  4. Barbara Rossi, 2012. "Comment on "Taylor Rule Exchange Rate Forecasting during the Financial Crisis"," NBER Chapters, National Bureau of Economic Research, Inc, in: NBER International Seminar on Macroeconomics 2012, pages 106-116 National Bureau of Economic Research, Inc.
  5. Barbara Rossi, 2013. "Exchange rate predictability," Economics Working Papers, Department of Economics and Business, Universitat Pompeu Fabra 1369, Department of Economics and Business, Universitat Pompeu Fabra.
  6. Barbara Rossi & Atsushi Inoue, 2011. "Out-of-sample forecast tests robust to the choice of window size," Working Papers, Federal Reserve Bank of Philadelphia 11-31, Federal Reserve Bank of Philadelphia.
  7. Peter Reinhard Hansen & Allan Timmermann, 2012. "Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics," Economics Working Papers, European University Institute ECO2012/24, European University Institute.
  8. Corradi, Valentina & Swanson, Norman R., 2014. "Testing for structural stability of factor augmented forecasting models," Journal of Econometrics, Elsevier, Elsevier, vol. 182(1), pages 100-118.
  9. Barbara Rossi & Tatevik Sekhposyany, 2014. "Forecast Rationality Tests in the Presence of Instabilities, With Applications to Federal Reserve and Survey Forecasts," Working Papers, Barcelona Graduate School of Economics 765, Barcelona Graduate School of Economics.
  10. Rossi, José Luiz Júnior, 2014. "The Usefulness of Financial Variables in Predicting Exchange Rate Movements," Insper Working Papers, Insper Working Paper, Insper Instituto de Ensino e Pesquisa wpe_332, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
  11. Richard A. Ashley & Christopher F. Parmeter, 2013. "Sensitivity Analysis of Inference in GMM Estimation With Possibly-Flawed Moment Conditions," Working Papers, Virginia Polytechnic Institute and State University, Department of Economics e07-40, Virginia Polytechnic Institute and State University, Department of Economics.
  12. Richard A. Ashley & Kwok Ping Tsang, 2014. "Credible Granger-Causality Inference with Modest Sample Lengths: A Cross-Sample Validation Approach," Econometrics, MDPI, Open Access Journal, MDPI, Open Access Journal, vol. 2(1), pages 72-91, March.
  13. Francis X. Diebold, 2012. "Comparing Predictive Accuracy, Twenty Years Later: A Personal Perspective on the Use and Abuse of Diebold-Mariano Tests," NBER Working Papers 18391, National Bureau of Economic Research, Inc.
  14. Gürkaynak, Refet S. & Kisacikoglu, Burçin & Rossi, Barbara, 2013. "Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?," CEPR Discussion Papers, C.E.P.R. Discussion Papers 9576, C.E.P.R. Discussion Papers.
  15. Geert Mesters & Siem Jan Koopman, 2012. "A Forty Year Assessment of Forecasting the Boat Race," Tinbergen Institute Discussion Papers, Tinbergen Institute 12-110/III, Tinbergen Institute.

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