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The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns

  • Massimo Guidolin
  • Carrie Fangzhou Na

We address one interesting case — the predictability of excess US asset returns from macroeconomic factors within a flexible regime switching VAR framework — in which the presence of regimes may lead to superior forecasting performance from forecast combinations. After having documented that forecast combinations provide gains in prediction accuracy and these gains are statistically significant, we show that combinations may substantially improve portfolio selection. We find that the best performing forecast combinations are those that either avoid estimating the pooling weights or that minimize the need for estimation. In practice, we report that the best performing combination schemes are based on the principle of relative, past forecasting performance. The economic gains from combining forecasts in portfolio management applications appear to be large, stable over time, and robust to the introduction of realistic transaction costs.

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File URL: http://research.stlouisfed.org/wp/2006/2006-059.pdf
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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2006-059.

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Date of creation: 2007
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Publication status: Published in Forecasting in the Presence of Structural Breaks and Model Uncertainty, M. Wohar and D. Rapach, eds., May 2008, pp. 601-61
Handle: RePEc:fip:fedlwp:2006-059
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  1. Timmermann, Allan, 2006. "Forecast Combinations," Handbook of Economic Forecasting, Elsevier.
  2. Francis X. Diebold & Todd A. Gunther & Anthony S. Tay, 1997. "Evaluating Density Forecasts," NBER Technical Working Papers 0215, National Bureau of Economic Research, Inc.
  3. Massimo Guidolin & Allan Timmermann, 2005. "Economic Implications of Bull and Bear Regimes in UK Stock and Bond Returns," Economic Journal, Royal Economic Society, vol. 115(500), pages 111-143, 01.
  4. Elliott, Graham & Timmermann, Allan, 2002. "Optimal Forecast Combination Under General Loss Functions and Forecast Error Distributions," University of California at San Diego, Economics Working Paper Series qt15r9t2q2, Department of Economics, UC San Diego.
  5. Guidolin, Massimo & Ono, Sadayuki, 2006. "Are the dynamic linkages between the macroeconomy and asset prices time-varying?," Journal of Economics and Business, Elsevier, vol. 58(5-6), pages 480-518.
  6. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-44, January.
  7. PALM, Franz C. & ZELLNER, Arnold, . "To Combine or not to Combine? Issues of Combining Forecasts," CORE Discussion Papers RP -1027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  8. Guidolin, Massimo & Timmermann, Allan, 2006. "Term structure of risk under alternative econometric specifications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 285-308.
  9. Paul Weller & Christopher Neely, 1999. "Predictability in International Asset Returns: A Re-examination," Working Papers wp99-03, Warwick Business School, Finance Group.
  10. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
  11. David M. Cutler & James M. Poterba & Lawrence H. Summers, 1988. "What Moves Stock Prices?," NBER Working Papers 2538, National Bureau of Economic Research, Inc.
  12. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
  13. Massimo Guidolin & Allan Timmerman, 2005. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Working Papers 2005-003, Federal Reserve Bank of St. Louis.
  14. Andrew Ang & Geert Bekaert, 1998. "Regime Switches in Interest Rates," NBER Working Papers 6508, National Bureau of Economic Research, Inc.
  15. Francis X. Diebold & Glenn D. Rudebusch & Daniel E. Sichel, 1991. "Further evidence on business cycle duration dependence," Working Papers 91-11, Federal Reserve Bank of Philadelphia.
  16. Fama, Eugene F. & French, Kenneth R., 1988. "Dividend yields and expected stock returns," Journal of Financial Economics, Elsevier, vol. 22(1), pages 3-25, October.
  17. Sola, Martin & Driffill, John, 1994. "Testing the term structure of interest rates using a stationary vector autoregression with regime switching," Journal of Economic Dynamics and Control, Elsevier, vol. 18(3-4), pages 601-628.
  18. Michael P. Clements & Hans-Martin Krolzig, 1998. "A comparison of the forecast performance of Markov-switching and threshold autoregressive models of US GNP," Econometrics Journal, Royal Economic Society, vol. 1(Conferenc), pages C47-C75.
  19. Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December.
  20. Berkowitz, Jeremy, 2001. "Testing Density Forecasts, with Applications to Risk Management," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 465-74, October.
  21. Aiolfi, Marco & Favero, Carlo A., 2003. "Model Uncertainty, Thick Modelling and the Predictability of Stock Returns," CEPR Discussion Papers 3997, C.E.P.R. Discussion Papers.
  22. Geert Bekaert & Robert J. Hodrick, 1991. "Characterizing Predictable Components in Excess Returns on Equity and Foreign Exchange Markets," NBER Working Papers 3790, National Bureau of Economic Research, Inc.
  23. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
  24. Campbell, John, 1987. "Stock Returns and the Term Structure," Scholarly Articles 3207699, Harvard University Department of Economics.
  25. Amit Goyal & Ivo Welch, 2003. "Predicting the Equity Premium with Dividend Ratios," Management Science, INFORMS, vol. 49(5), pages 639-654, May.
  26. Turner, C.M. & Startz, R. & Nelson, C.R., 1989. "The Markov Model Of Heteroskedasticity, Risk And Learning In The Stock Market," Working Papers 89-01, University of Washington, Department of Economics.
  27. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  28. David Hendry & Michael Clements, 2001. "Pooling of Forecasts," Economics Series Working Papers 2002-W09, University of Oxford, Department of Economics.
  29. 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.
  30. 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.
  31. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
  32. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2006. "Investing for the long-run in European real estate," Working Papers 2006-028, Federal Reserve Bank of St. Louis.
  33. Christopher M. Turner & Richard Startz & Charles R. Nelson, 1989. "A Markov Model of Heteroskedasticity, Risk, and Learning in the Stock Market," NBER Working Papers 2818, National Bureau of Economic Research, Inc.
  34. Chan, Louis K. C. & Karceski, Jason & Lakonishok, Josef, 1998. "The Risk and Return from Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(02), pages 159-188, June.
  35. James H. Stock & Mark W. Watson, 2001. "Forecasting Output and Inflation: The Role of Asset Prices," NBER Working Papers 8180, National Bureau of Economic Research, Inc.
  36. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
  37. repec:cup:cbooks:9780521634809 is not listed on IDEAS
  38. Victor Fenton & Gallant, A. Ronald, 1996. "Qualitative and Asymptotic Performance of SNP Density Estimators," Working Papers 96-17, Duke University, Department of Economics.
  39. Robert B. Davies, 2002. "Hypothesis testing when a nuisance parameter is present only under the alternative: Linear model case," Biometrika, Biometrika Trust, vol. 89(2), pages 484-489, June.
  40. Bunn, Derek W., 1985. "Statistical efficiency in the linear combination of forecasts," International Journal of Forecasting, Elsevier, vol. 1(2), pages 151-163.
  41. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  42. Ravazzolo, F. & van Dijk, D.J.C. & Paap, R. & Franses, Ph.H.B.F., 2006. "Bayesian Model Averaging in the Presence of Structural Breaks," Econometric Institute Research Papers EI 2006-33, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  43. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
  44. Diebold, Francis X, 1988. "Serial Correlation and the Combination of Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 105-11, January.
  45. Paye, Bradley S. & Timmermann, Allan, 2006. "Instability of return prediction models," Journal of Empirical Finance, Elsevier, vol. 13(3), pages 274-315, June.
  46. Fama, Eugene F. & French, Kenneth R., 1989. "Business conditions and expected returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 25(1), pages 23-49, November.
  47. Yang, Yuhong, 2004. "Combining Forecasting Procedures: Some Theoretical Results," Econometric Theory, Cambridge University Press, vol. 20(01), pages 176-222, February.
  48. Gray, Stephen F., 1996. "Modeling the conditional distribution of interest rates as a regime-switching process," Journal of Financial Economics, Elsevier, vol. 42(1), pages 27-62, September.
  49. René Garcia, 1995. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," CIRANO Working Papers 95s-07, CIRANO.
  50. Rapach, David E. & Wohar, Mark E., 2006. "In-sample vs. out-of-sample tests of stock return predictability in the context of data mining," Journal of Empirical Finance, Elsevier, vol. 13(2), pages 231-247, March.
  51. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
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