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Can VAR models capture regime shifts in asset returns? a long-horizon strategic asset allocation perspective

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  • Massimo Guidolin
  • Stuart Hyde

Abstract

In the empirical portfolio choice literature it is often invoked that through the choice of predictors that may closely track business cycle conditions and market sentiment, simple Vector Autoregressive (VAR) models could produce optimal strategic portfolio allocations that hedge against the bull and bear dynamics typical of financial markets. However, a distinct literature exists that shows that non-linear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. In this paper we examine whether and how simple VARs can produce empirical portfolio rules similar to those obtained under a range of multivariate Markov switching models, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem on US data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those typical of non-linear models that account for bull-bear dynamics and characterize the differences in the implied hedging demands for a long-horizon investor with constant relative risk aversion preferences. We conclude that most (if not all) VARs cannot produce portfolio rules, hedging demands, or out-of-sample performances that approximate those obtained from equally simple non-linear frameworks.

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Paper provided by Federal Reserve Bank of St. Louis in its series Working Papers with number 2010-002.

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Date of creation: 2010
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Handle: RePEc:fip:fedlwp:2010-002

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Keywords: Econometric models ; Vector autoregression ; Asset pricing ; Rate of return;

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  1. Heij, Christiaan & van Dijk, Dick & Groenen, Patrick J.F., 2008. "Macroeconomic forecasting with matched principal components," International Journal of Forecasting, Elsevier, vol. 24(1), pages 87-100.
  2. Kim, Chang-Jin & Nelson, Charles R. & Startz, Richard, 1998. "Testing for mean reversion in heteroskedastic data based on Gibbs-sampling-augmented randomization1," Journal of Empirical Finance, Elsevier, vol. 5(2), pages 131-154, June.
  3. Chan, Yeung Lewis & Viceira, Luis & Campbell, John, 2003. "A Multivariate Model of Strategic Asset Allocation," Scholarly Articles 3163263, Harvard University Department of Economics.
  4. Anthony W. Lynch & Pierluigi Balduzzi, 2000. "Predictability and Transaction Costs: The Impact on Rebalancing Rules and Behavior," Journal of Finance, American Finance Association, vol. 55(5), pages 2285-2309, October.
  5. Brennan, Michael J. & Schwartz, Eduardo S. & Lagnado, Ronald, 1997. "Strategic asset allocation," Journal of Economic Dynamics and Control, Elsevier, vol. 21(8-9), pages 1377-1403, June.
  6. Massimo Guidolin & Stuart Hyde & David McMillan & Sadayuki Ono, 2009. "Non-linear predictability in stock and bond returns: when and where is it exploitable?," Working Papers 2008-010, Federal Reserve Bank of St. Louis.
  7. Allan Timmermann & Massimo Guidolin, 2006. "An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 1-22.
  8. Amit Goyal & Ivo Welch, 2004. "A Comprehensive Look at the Empirical Performance of Equity Premium Prediction," Yale School of Management Working Papers amz2412, Yale School of Management, revised 01 Jan 2006.
  9. Michael Dueker, 1995. "Markov switching in GARCH processes and mean reverting stock market volatility," Working Papers 1994-015, Federal Reserve Bank of St. Louis.
  10. Timmermann, Allan, 2000. "Moments of Markov switching models," Journal of Econometrics, Elsevier, vol. 96(1), pages 75-111, May.
  11. David H. Cutler & James M. Poterba & Lawrence H. Summers, 1988. "What Moves Stock Prices?," Working papers 487, Massachusetts Institute of Technology (MIT), Department of Economics.
  12. Frauendorfer, Karl & Jacoby, Ulrich & Schwendener, Alvin, 2007. "Regime switching based portfolio selection for pension funds," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2265-2280, August.
  13. Massimo Guidolin & Allan Timmerman, 2006. "Asset allocation under multivariate regime switching," Working Papers 2005-002, Federal Reserve Bank of St. Louis.
  14. Kandel, Shmuel & Stambaugh, Robert F, 1996. " On the Predictability of Stock Returns: An Asset-Allocation Perspective," Journal of Finance, American Finance Association, vol. 51(2), pages 385-424, June.
  15. Yacine Aït-Sahalia, 2001. "Variable Selection for Portfolio Choice," Journal of Finance, American Finance Association, vol. 56(4), pages 1297-1351, 08.
  16. Richard D.F. Harris & Rene Sanchez-Valle, 2000. "The Gilt-Equity Yield Ratio and the Predictability of UK and US Equity Returns," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(3&4), pages 333-357.
  17. Garcia, R. & Perron, P., 1990. "An Anlysis Of The Real Interest Rate Under Regime Shifts," Papers 353, Princeton, Department of Economics - Econometric Research Program.
  18. Andrew Ang & Joseph Chen & Yuhang Xing, 2005. "Downside risk," Proceedings, Board of Governors of the Federal Reserve System (U.S.).
  19. Markus Haas, 2004. "A New Approach to Markov-Switching GARCH Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(4), pages 493-530.
  20. Balvers, Ronald J & Cosimano, Thomas F & McDonald, Bill, 1990. " Predicting Stock Returns in an Efficient Market," Journal of Finance, American Finance Association, vol. 45(4), pages 1109-28, September.
  21. Gomes, Francisco J., 2007. "Exploiting short-run predictability," Journal of Banking & Finance, Elsevier, vol. 31(5), pages 1427-1440, May.
  22. Ang, Andrew & Timmermann, Allan G, 2011. "Regime Changes and Financial Markets," CEPR Discussion Papers 8480, C.E.P.R. Discussion Papers.
  23. Clare, A D & Thomas, S H & Wickens, M R, 1994. "Is the Gilt-Equity Yield Ratio Useful for Predicting UK Stock Returns?," Economic Journal, Royal Economic Society, vol. 104(423), pages 303-15, March.
  24. Ludvigson, Sydney C. & Ng, Serena, 2007. "The empirical risk-return relation: A factor analysis approach," Journal of Financial Economics, Elsevier, vol. 83(1), pages 171-222, January.
  25. Chu, Ba, 2011. "Recovering copulas from limited information and an application to asset allocation," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1824-1842, July.
  26. Ang, Andrew & Bekaert, Geert & Liu, Jun, 2005. "Why stocks may disappoint," Journal of Financial Economics, Elsevier, vol. 76(3), pages 471-508, June.
  27. Henkel, Sam James & Martin, J. Spencer & Nardari, Federico, 2011. "Time-varying short-horizon predictability," Journal of Financial Economics, Elsevier, vol. 99(3), pages 560-580, March.
  28. Zakamouline, Valeri & Koekebakker, Steen, 2009. "Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1242-1254, July.
  29. Fama, Eugene F. & Schwert, G. William, 1977. "Asset returns and inflation," Journal of Financial Economics, Elsevier, vol. 5(2), pages 115-146, November.
  30. 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.
  31. 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.
  32. John Y. Campbell & Tuomo Vuolteenaho, 2003. "Bad Beta, Good Beta," Harvard Institute of Economic Research Working Papers 2016, Harvard - Institute of Economic Research.
  33. Allan Timmermann & M. Hashem Pesaran, 1999. "A Recursive Modelling Approach to Predicting UK Stock Returns," FMG Discussion Papers dp322, Financial Markets Group.
  34. Avramov, Doron, 2002. "Stock return predictability and model uncertainty," Journal of Financial Economics, Elsevier, vol. 64(3), pages 423-458, June.
  35. Pérez Quirós, Gabriel & Timmermann, Allan, 2001. "Business cycle asymmetries in stock returns: evidence from higher order moments and conditional densities," Working Paper Series 0058, European Central Bank.
  36. Campbell, John, 1987. "Stock Returns and the Term Structure," Scholarly Articles 3207699, Harvard University Department of Economics.
  37. Henry, Ólan T., 2009. "Regime switching in the relationship between equity returns and short-term interest rates in the UK," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 405-414, February.
  38. Allan Timmermann & Gabriel Perez-Quiros, 1999. "Firm Size and Cyclical Variations in Stock Returns," FMG Discussion Papers dp335, Financial Markets Group.
  39. Andrew Ang & Geert Bekaert, 2001. "Stock Return Predictability: Is it There?," NBER Working Papers 8207, National Bureau of Economic Research, Inc.
  40. Jér�me B. Detemple & René Garcia & Marcel Rindisbacher, 2003. "A Monte Carlo Method for Optimal Portfolios," Journal of Finance, American Finance Association, vol. 58(1), pages 401-446, 02.
  41. Massimo Guidolin & Allan Timmerman, 2005. "Size and value anomalies under regime shifts," Working Papers 2005-007, Federal Reserve Bank of St. Louis.
  42. 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.
  43. Bae, Jinho & Kim, Chang-Jin & Nelson, Charles R., 2007. "Why are stock returns and volatility negatively correlated?," Journal of Empirical Finance, Elsevier, vol. 14(1), pages 41-58, January.
  44. Massimo Guidolin & Carrie Fangzhou Na, 2007. "The economic and statistical value of forecast combinations under regime switching: an application to predictable U.S. returns," Working Papers 2006-059, Federal Reserve Bank of St. Louis.
  45. 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.
  46. 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.
  47. Campbell, John Y. & Viceira, Luis M., 2002. "Strategic Asset Allocation: Portfolio Choice for Long-Term Investors," OUP Catalogue, Oxford University Press, number 9780198296942, September.
  48. Massimo Guidolin & Allan Timmermann, 2008. "International asset allocation under regime switching, skew, and kurtosis preferences," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 889-935, April.
  49. Andrew Ang & Geert Bekaert, 2003. "How do Regimes Affect Asset Allocation?," NBER Working Papers 10080, National Bureau of Economic Research, Inc.
  50. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-78, December.
  51. Normandin, Michel & St-Amour, Pascal, 2008. "An empirical analysis of aggregate household portfolios," Journal of Banking & Finance, Elsevier, vol. 32(8), pages 1583-1597, August.
  52. Fortin, Ines & Hlouskova, Jaroslava, 2011. "Optimal asset allocation under linear loss aversion," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2974-2990, November.
  53. Balduzzi, Pierluigi & Lynch, Anthony W., 1999. "Transaction costs and predictability: some utility cost calculations," Journal of Financial Economics, Elsevier, vol. 52(1), pages 47-78, April.
  54. John H. Boyd & Jian Hu & Ravi Jagannathan, 2005. "The Stock Market's Reaction to Unemployment News: Why Bad News Is Usually Good for Stocks," Journal of Finance, American Finance Association, vol. 60(2), pages 649-672, 04.
  55. Lynch, Anthony W., 2001. "Portfolio choice and equity characteristics: characterizing the hedging demands induced by return predictability," Journal of Financial Economics, Elsevier, vol. 62(1), pages 67-130, October.
  56. Samuelson, Paul A, 1969. "Lifetime Portfolio Selection by Dynamic Stochastic Programming," The Review of Economics and Statistics, MIT Press, vol. 51(3), pages 239-46, August.
  57. Nicholas Barberis, 2000. "Investing for the Long Run when Returns Are Predictable," Journal of Finance, American Finance Association, vol. 55(1), pages 225-264, 02.
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Cited by:
  1. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla & Masih, A. Mansur M., 2014. "Combining Momentum, Value, and Quality for the Islamic Equity Portfolio: Multi-style Rotation Strategies using Augmented Black Litterman Factor Model," MPRA Paper 56965, University Library of Munich, Germany.
  2. Apostolos Thomadakis, 2012. "Contagion or Flight-to-Quality Phenomena in Stock and Bond Returns," School of Economics Discussion Papers 0612, School of Economics, University of Surrey.
  3. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2010. "1/N and long run optimal portfolios: results for mixed asset menus," Working Papers 2010-003, Federal Reserve Bank of St. Louis.
  4. Massimo Guidolin & Stuart Hyde, 2012. "Optimal Portfolios for Occupational Funds under Time-Varying Correlations in Bull and Bear Markets? Assessing the Ex-Post Economic Value," Working Papers 455, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  5. Nyberg, Henri, 2013. "Predicting bear and bull stock markets with dynamic binary time series models," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3351-3363.

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