Advanced Search
MyIDEAS: Login to save this paper or follow this series

Choice of Sample Split in Out-of-Sample Forecast Evaluation

Contents:

Author Info

  • Peter Reinhard Hansen

    ()
    (European University Institute and CREATES)

  • Allan Timmermann

    ()
    (UCSD and CREATES)

Abstract

Out-of-sample tests of forecast performance depend on how a given data set is split into estimation and evaluation periods, yet no guidance exists on how to choose the split point. Empirical forecast evaluation results can therefore be difficult to interpret, particularly when several values of the split point might have been considered. When the sample split is viewed as a choice variable, rather than being ?xed ex ante, we show that very large size distortions can occur for conventional tests of predictive accu- racy. Spurious rejections are most likely to occur with a short evaluation sample, while conversely the power of forecast evaluation tests is strongest with long out-of-sample periods. To deal with size distortions, we propose a test statistic that is robust to the effect of considering multiple sample split points. Empirical applications to predictabil- ity of stock returns and in?ation demonstrate that out-of-sample forecast evaluation results can critically depend on how the sample split is determined.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: ftp://ftp.econ.au.dk/creates/rp/12/rp12_43.pdf
Download Restriction: no

Bibliographic Info

Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2012-43.

as in new window
Length: 42
Date of creation: 07 Feb 2012
Date of revision:
Handle: RePEc:aah:create:2012-43

Contact details of provider:
Web page: http://www.econ.au.dk/afn/

Related research

Keywords: Out-of-sample forecast evaluation; data mining; recursive estimation; predictability of stock returns; in?ation forecasting.;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. M. Hashem Pesaran & Andreas Pick & Allan Timmermann, 2010. "Variable Selection, Estimation and Inference for Multi-period Forecasting Problems," DNB Working Papers, Netherlands Central Bank, Research Department 250, Netherlands Central Bank, Research Department.
  2. Donald B. Keim & Robert F. Stambaugh, . "Predicting Returns in the Stock and Bond Markets," Rodney L. White Center for Financial Research Working Papers, Wharton School Rodney L. White Center for Financial Research 15-85, Wharton School Rodney L. White Center for Financial Research.
  3. Todd E. Clark & Kenneth D. West, 2005. "Approximately normal tests for equal predictive accuracy in nested models," Research Working Paper, Federal Reserve Bank of Kansas City RWP 05-05, Federal Reserve Bank of Kansas City.
  4. Kenneth D. West, 1994. "Asymptotic Inference About Predictive Ability," Macroeconomics, EconWPA 9410002, EconWPA.
  5. Davidson, James & de Jong, Robert M., 2000. "The Functional Central Limit Theorem And Weak Convergence To Stochastic Integrals Ii," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 16(05), pages 643-666, October.
  6. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, Econometric Society, vol. 61(4), pages 821-56, July.
  7. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 23, pages 365-380, October.
  8. McCracken, Michael W., 2007. "Asymptotics for out of sample tests of Granger causality," Journal of Econometrics, Elsevier, Elsevier, vol. 140(2), pages 719-752, October.
  9. Campbell, John & Thompson, Samuel P., 2008. "Predicting Excess Stock Returns Out of Sample: Can Anything Beat the Historical Average?," Scholarly Articles 2622619, Harvard University Department of Economics.
  10. Massimiliano Marcellino & James Stock & Mark Watson, 2005. "A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series," Working Papers, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University 285, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  11. Inoue, Atsushi & Kilian, Lutz, 2002. "In-Sample or Out-of-Sample Tests of Predictability: Which One Should We Use?," CEPR Discussion Papers, C.E.P.R. Discussion Papers 3671, C.E.P.R. Discussion Papers.
  12. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
  13. Campbell, J.Y. & Shiller, R.J., 1988. "Stock Prices, Earnings And Expected Dividends," Papers, Princeton, Department of Economics - Econometric Research Program 334, Princeton, Department of Economics - Econometric Research Program.
  14. John Y. Campbell & Motohiro Yogo, 2003. "Efficient Tests of Stock Return Predictability," NBER Working Papers 10026, National Bureau of Economic Research, Inc.
  15. Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers, Econometric Society 0319, Econometric Society.
  16. Todd Clark & Michael W. McCracken, 2011. "Advances in forecast evaluation," Working Paper, Federal Reserve Bank of Cleveland 1120, Federal Reserve Bank of Cleveland.
  17. Halbert White, 2000. "A Reality Check for Data Snooping," Econometrica, Econometric Society, Econometric Society, vol. 68(5), pages 1097-1126, September.
  18. Hansen, Bruce E., 1992. "Convergence to Stochastic Integrals for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 8(04), pages 489-500, December.
  19. Todd Clark & Michael McCracken, 2005. "Evaluating Direct Multistep Forecasts," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 24(4), pages 369-404.
  20. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, Elsevier, vol. 22(1), pages 3-25, October.
  21. Sydney C. Ludvigson & Serena Ng, 2009. "Macro Factors in Bond Risk Premia," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 22(12), pages 5027-5067, December.
  22. Inoue, Atsushi & Kilian, Lutz, 2008. "How Useful Is Bagging in Forecasting Economic Time Series? A Case Study of U.S. Consumer Price Inflation," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 103, pages 511-522, June.
  23. Wooldridge, Jeffrey M. & White, Halbert, 1988. "Some Invariance Principles and Central Limit Theorems for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, Cambridge University Press, vol. 4(02), pages 210-230, August.
  24. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
  25. Barbara Rossi & Atsushi Inoue, 2011. "Out-of-Sample Forecast Tests Robust to Window Size Choice," Working Papers, Duke University, Department of Economics 11-04, Duke University, Department of Economics.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Fang, Jiali & Jacobsen, Ben & Qin, Yafeng, 2014. "Predictability of the simple technical trading rules: An out-of-sample test," Review of Financial Economics, Elsevier, Elsevier, vol. 23(1), pages 30-45.
  2. 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.
  3. Biqing Cai & Jiti Gao, 2013. "Hermite Series Estimation in Nonlinear Cointegrating Models," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics 17/13, Monash University, Department of Econometrics and Business Statistics.
  4. Agnieszka Markiewicz & Andreas Pick, 2013. "Adaptive Learning and Survey Data," CDMA Working Paper Series, Centre for Dynamic Macroeconomic Analysis 201305, Centre for Dynamic Macroeconomic Analysis.
  5. repec:wyi:journl:002213 is not listed on IDEAS
  6. He, Kaijian & Wang, Lijun & Zou, Yingchao & Lai, Kin Keung, 2014. "Value at risk estimation with entropy-based wavelet analysis in exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 408(C), pages 62-71.
  7. Wang, Cindy Shin-Huei & Bauwens, Luc & Hsiao, Cheng, 2013. "Forecasting a long memory process subject to structural breaks," Journal of Econometrics, Elsevier, Elsevier, vol. 177(2), pages 171-184.
  8. Hutter, Christian & Weber, Enzo, 2013. "Constructing a new leading indicator for unemployment from a survey among German employment agencies," IAB Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] 201317, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
  9. Peter Reinhard Hansen & Allan Timmermann, 2012. "Equivalence Between Out-of-Sample Forecast Comparisons and Wald Statistics," CREATES Research Papers, School of Economics and Management, University of Aarhus 2012-45, School of Economics and Management, University of Aarhus.
  10. 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.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:aah:create:2012-43. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ().

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.