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Forecasting Prices in Regime-Switching Markets

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  • Martín González-Rozada
  • Luis Pereiro

Abstract

Linear autoregressive (LAR) models poorly predict asset prices in nonlinear, regime-switching markets. We introduce SETAR, a threshold model that accounts for nonlinearities, to test for the existence of regime-switching in global equity markets. A comparison of SETAR‘s predictive power against that of LAR models suggests that SETAR yields more accurate long forecasts, in both emerging and developed stock markets. We discuss extensions of threshold models into portfolio management, corporate valuation, and the long-term forecasting of financial indicators.

Suggested Citation

  • Martín González-Rozada & Luis Pereiro, 2013. "Forecasting Prices in Regime-Switching Markets," Department of Economics Working Papers 2013_2, Universidad Torcuato Di Tella.
    • Handle: RePEc:udt:wpecon:2013_2
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    File URL: https://www.utdt.edu/download.php?fname=_143413686233630700.pdf
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    References listed on IDEAS

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    6. Granger, Clive W. J. & Terasvirta, Timo, 1993. "Modelling Non-Linear Economic Relationships," OUP Catalogue, Oxford University Press, number 9780198773207, Decembrie.
    7. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2006. "Portfolio implications of systemic crises," Journal of Banking & Finance, Elsevier, vol. 30(8), pages 2347-2369, August.
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    Cited by:

    1. Adriana Ocejo, 2018. "Explicit solutions to utility maximization problems in a regime-switching market model via Laplace transforms," Papers 1804.08442, arXiv.org.

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