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

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  • Guidolin, Massimo
  • Hyde, Stuart

Abstract

It is often suggested that through a judicious choice of predictors that track business cycles 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 nonlinear econometric frameworks, such as Markov switching (MS), are also natural tools to compute optimal portfolios in the presence of stochastic good and bad market states. In this paper we examine whether simple VARs can produce portfolio rules similar to those obtained under MS, 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, 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 nonlinear models for a long-horizon investor with constant relative risk aversion. We conclude that most VARs cannot produce portfolio rules, hedging demands, or (net of transaction costs) out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks. We also compute the improvement in realized performance that may be achieved adopting more complex MS models and report this may be substantial in the case of regime switching ARCH.

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  • Guidolin, Massimo & Hyde, Stuart, 2012. "Can VAR models capture regime shifts in asset returns? A long-horizon strategic asset allocation perspective," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 695-716.
  • Handle: RePEc:eee:jbfina:v:36:y:2012:i:3:p:695-716
    DOI: 10.1016/j.jbankfin.2011.10.011
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    Cited by:

    1. Carolina Fugazza & Massimo Guidolin & Giovanna Nicodano, 2010. "1/N and Long Run Optimal Portfolios: Results for Mixed Asset Menus," Carlo Alberto Notebooks 190, Collegio Carlo Alberto.
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    4. Guidolin, Massimo & Hyde, Stuart, 2012. "Simple VARs cannot approximate Markov switching asset allocation decisions: An out-of-sample assessment," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3546-3566.
    5. Vladimir Zdorovenin & Jacques Pézier, 2011. "Does Information Content of Option Prices Add Value for Asset Allocation?," ICMA Centre Discussion Papers in Finance icma-dp2011-03, Henley Business School, Reading University.
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    7. Dewandaru, Ginanjar & Masih, Rumi & Bacha, Obiyathulla Ismath & Masih, A. Mansur. M., 2015. "Combining momentum, value, and quality for the Islamic equity portfolio: Multi-style rotation strategies using augmented Black Litterman factor model," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 205-232.
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    9. 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.
    10. Giulia Dal Pra & Massimo Guidolin & Manuela Pedio & Fabiola Vasile, 2016. "Do Regimes in Excess Stock Return Predictability Create Economic Value? An Out-of-Sample Portfolio Analysis," BAFFI CAREFIN Working Papers 1637, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    11. 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.
    12. 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.

    More about this item

    Keywords

    Predictability; Strategic asset allocation; Markov switching; Vector autoregressive models; Out-of-sample performance;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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