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Markov Switching Garch Models of Currency Crises in Southeast Asia

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Author Info

  • Celso Brunetti

    ()
    (Department of Economics, University of Pennsylvania)

  • Roberto S. Mariano

    ()
    (Department of Economics, University of Pennsylvania and School of Economics and Social Studies, Singapore Management University)

  • Chiara Scotti

    ()
    (Department of Economics, University of Pennsylvania)

  • Augustine H. H. Tan

    ()
    (School of Economics and Social Studies, Singapore Management University)

Abstract

This paper develops a model which is able to forecast exchange rate turmoil. Our starting point relies on the empirical evidence that exchange rate volatility is not constant. In fact, the modeling strategy adopted refers to the vast literature of the GARCH class of models, where the variance process is explicitly modeled. Further empirical evidence shows that it is possible to distinguish between two different regimes: “ordinary” versus “turbulence”. Low exchange rate changes are associated with low volatility (ordinary regime) and high exchange rate devaluations go together with high volatility. This calls for a regime switching approach. In our model we also allow the transition probabilities to vary over time as functions of economic and financial indicators. We find that real effective exchange rate, money supply relative to reserves, stock index returns and bank stock index returns and volatility are the major indicators.

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Bibliographic Info

Paper provided by Penn Institute for Economic Research, Department of Economics, University of Pennsylvania in its series PIER Working Paper Archive with number 03-008.

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Length: 44 pages
Date of creation: 18 Mar 2003
Date of revision:
Handle: RePEc:pen:papers:03-008

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Keywords: Currency crises; Markov Switching Models; Volatility;

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References

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  1. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-35, April.
  2. Steven Radelet & Jeffrey D. Sachs, 1998. "The East Asian Financial Crisis: Diagnosis, Remedies, Prospects," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 29(1), pages 1-90.
  3. Baillie, Richard T & Bollerslev, Tim, 2002. "The Message in Daily Exchange Rates: A Conditional-Variance Tale," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 60-68, January.
  4. Graciela L. Kaminsky & Carmen M. Reinhart, 1996. "The twin crises: the causes of banking and balance-of-payments problems," International Finance Discussion Papers 544, Board of Governors of the Federal Reserve System (U.S.).
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  23. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
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Citations

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Cited by:
  1. Gallo, Giampiero M. & Otranto, Edoardo, 2008. "Volatility spillovers, interdependence and comovements: A Markov Switching approach," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 3011-3026, February.
  2. Giampiero M. Gallo & Edoardo Otranto, 2007. "Volatility transmission across markets: a Multichain Markov Switching model," Applied Financial Economics, Taylor & Francis Journals, vol. 17(8), pages 659-670.
  3. Humala, Alberto & Rodríguez, Gabriel, 2009. "Foreign Exchange Intervention and Exchange Rate Volatility in Peru," Working Papers 2009-008, Banco Central de Reserva del Perú.
  4. Kim Liow & Zhiwei Chen & Jingran Liu, 2011. "Multiple Regimes and Volatility Transmission in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 42(3), pages 295-328, April.
  5. Khalifa, Ahmed A.A. & Hammoudeh, Shawkat & Otranto, Edoardo, 2014. "Patterns of volatility transmissions within regime switching across GCC and global markets," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 512-524.

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