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Hidden Markov Models in Finance pp 155–184Cite as

Early Warning Systems for Currency Crises: A Regime-Switching Approach

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 104))

Summary

Previous early warning systems (EWS) for currency crises have relied on models that require a priori dating of crises. This paper proposes an alternative EWS, based on a Markov-switching model, which identifies and characterizes crisis periods endogenously; this also allows the model to utilize information contained in exchange rate dynamics. The model is estimated on data from 1972–1999 for the Asian crisis countries, taking a country-by-country approach. The model outperforms standard EWSs, both in signaling crises and reducing false alarms. Two lessons emerge. First, accounting for the dynamics of exchange rates is important. Second, different indicators matter for different countries, suggesting that the assumption of parameter constancy underlying panel estimates of EWSs may contribute to poor performance.

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References

  1. Abiad, A. (2002). “Early warning systems for currency crises: A Markov-switching approach with application to southeast Asia”. Ph.D. Dissertation, University of Pennsylvania.

    Google Scholar 

  2. Aziz, J., Caramazza, F. and R. Salgado (2000). “Currency crises: in search of common elements”. International Monetary Fund Policy Working Paper: WP/00/67, March.

    Google Scholar 

  3. Berg, A. and C. Pattillo (1999). “Predicting currency crises: the indicators approach and an alternative”. Journal of International Money and Finance, 18(4): 561–86.

    Article  Google Scholar 

  4. Berg, A., Borensztein E. and C. Pattillo (2004). “Assessing early warning systems: how have they worked in practice?”. International Monetary Fund Working Paper: WP/04/52, March.

    Google Scholar 

  5. Caramazza, F., Ricci, L. and R. Salgado (2000). “Trade and financial contagion in currency crises”. International Monetary Fund Policy Working Paper: WP/00/55, March.

    Google Scholar 

  6. Cecchetti, S.G., Lam, P. and N.C. Mark (1990). “Mean reversion in equilibrium asset prices”. American Economic Review, 80(3): 398–418.

    Google Scholar 

  7. Cerra, V. and S.C. Saxena (2002). “Contagion, monsoons, and domestic turmoil in Indonesia’s currency crisis”, Review of International Economics, 10(1): 36–44.

    Article  Google Scholar 

  8. Davies, R.B. (1977). “Hypothesis testing when a nuisance parameter is present only under the alternative”. Biometrika, 64(2): 247–254.

    Article  MATH  MathSciNet  Google Scholar 

  9. Davies, R.B. (1987). “Hypothesis testing when a nuisance parameter is present only under the alternative”. Biometrika, 74(1): 33–43.

    MATH  MathSciNet  Google Scholar 

  10. Diebold, F.X., Weinbach, G.C. and J.H. Lee (1994). “Regime switching with time-varying transition probabilities”. Nonstationary Time Series Analysis and Cointegration, ed. C.P. Hargreaves, Oxford University Press.

    Google Scholar 

  11. Edison, H.J. (2003). “Do indicators of financial crises work? an evaluation of an early warning system”. International Journal of Finance & Economics, 8(1): 11–53.

    Article  Google Scholar 

  12. Eichengreen, B., Rose, A. and C. Wyplosz (1996). “Contagious currency crises: first tests”. Scandinavian Journal of Economics, 98(4): 463–84

    Article  Google Scholar 

  13. Engel, C. and J.D. Hamilton (1990). “Long swings in the dollar: are they in the data, and do the markets know it?”. American Economic Review, 80(4): 689–713.

    Google Scholar 

  14. Filardo, A.J. (1994). “Business cycle phases and their transitional dynamics”. Journal of Business and Economic Statistics, 3(12): 299–308.

    Article  Google Scholar 

  15. Filardo, A.J. and S.F. Gordon (1993). “Business cycle durations”. Federal Reserve Bank of Kansas Research Working Paper No. 28, 93–111, October.

    Google Scholar 

  16. Frankel, J. and A. Rose (1996). “Currency crashes in emerging markets: an empirical treatment”. Journal of International Economics, 41(3): 351–366.

    Article  Google Scholar 

  17. Fratzscher, M. (1999). “What causes currency crises: sunspots, contagion or fundamentals?”. European University Institute Dept. of Economics Working Paper No. 99/39 (December).

    Google Scholar 

  18. Garcia, R. (1998). “Asymptotic null distribution of the likelihood ratio test in Markov switching models”. International Economic Review, 39(3): 763–788.

    Article  ADS  MathSciNet  Google Scholar 

  19. Goldfeld, S.M. and R.E. Quandt (1973). “A Markov model for switching regressions”. Journal of Econometrics, 1: 3–16.

    Article  MATH  Google Scholar 

  20. Hamilton, J.D. (1988). “Rational expectations econometric analysis of changes in regime: an investigation of the term structure of interest rates”. Journal of Economic Dynamics and Control, 12: 385–423.

    Article  MathSciNet  Google Scholar 

  21. Hamilton, J.D. (1989). “A new approach to the economic analysis of nonstationary time series and the business cycle”. Econometrica, 57: 357–84.

    Article  MATH  MathSciNet  Google Scholar 

  22. Hamilton, J.D. (1990). “Analysis of time series subject to changes in regime”. Journal of Econometrics, 45: 39–70.

    Article  MathSciNet  Google Scholar 

  23. Hamilton, J.D. (1994). Time Series Analysis. Princeton, NJ: Princeton University Press.

    MATH  Google Scholar 

  24. Hamilton, J.D. (1996). “Specification testing in Markov-switching time series models”. Journal of Econometrics, 70: 127–57.

    Article  MATH  MathSciNet  Google Scholar 

  25. Hamilton, J.D. and O. Jorda (2002). “A Model of the federal funds rate target”. Journal of Political Economy, 110(5): 1135–1167.

    Article  Google Scholar 

  26. Hansen, B.E. (1992). “The likelihood ratio test under nonstandard conditions: testing the Markov switching model of GNP”. Journal of Applied Econometrics, 7: 195–198.

    Article  Google Scholar 

  27. Hansen, B.E. (1996). “Inference when a nuisance parameter is not identified under the null hypothesis”. Econometrica, 64: 413–30.

    Article  MATH  MathSciNet  Google Scholar 

  28. Jeanne, O. and P. Masson (2000). “Currency crises, sunspots and Markov-switching regimes”. Journal of International Economics, 50(2): 327–350.

    Article  Google Scholar 

  29. Kamin, S.B., Schindler, J.W. and S.L. Samuel (2001). “The contributions of domestic and external factors to emerging market devaluation crises: an early warning systems approach”. Board of Governors of the Federal Reserve System, International Finance Discussion Paper No. 711.

    Google Scholar 

  30. Kaminsky, G. and C. Reinhart (1999). “The twin crises: causes of banking and balance-of-payments crises”. American Economic Review, 89(3): 473–500.

    Article  Google Scholar 

  31. Kaminsky, G., (1998). “Leading indicators of currency crises”. IMF Staff Papers, 45(1): 1–48.

    Google Scholar 

  32. Kim, C.J. and C.R. Nelson (1999). State-space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications, Cambridge, MA: MIT Press.

    Google Scholar 

  33. Lee, J.H. (1991). “Non-stationary Markov-switching models of exchange rates: the pound-dollar exchange rate”. Ph.D. Dissertation, University of Pennsylvania.

    Google Scholar 

  34. Mariano, R.S. and F.X. Gong (1998). “Testing under non-standard conditions in the frequency domain: with applications to Markov regime switching models of exchange rates and the federal funds rate”. Federal Reserve Bank of New York Staff Papers.

    Google Scholar 

  35. (2002). “A regime switching approach to studying speculative attacks: a focus on EMS crises”. Empirical Economics, 27(2): 299–334.

    Google Scholar 

  36. Quandt, R.E. (1958). “The estimation of parameters of linear regression system obeying two separate regimes”. Journal of the American Statistical Association, 55: 873–80.

    Article  MathSciNet  Google Scholar 

  37. Sachs, J.D., Tornell, A. and A. Velasco (1996). “Financial crises in emerging markets: the lessons from 1995”. Brookings Papers on Economic Activity, 1996(1): 147–215.

    Article  Google Scholar 

  38. Yin, G.G. and Q. Zhang (1998). Continuous-time Markov chains and applications. a singular perturbation approach. Berlin, Springer.

    MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. International Monetary Fund, 700 19th St. NW, Washington, DC, 20431, USA

    Abdul Abiad

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  1. Abdul Abiad
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Correspondence to Abdul Abiad .

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Editors and Affiliations

  1. University of Western Ontario, London, Canada

    Rogemar S. Mamon

  2. University of Calgary, Calgary, Canada

    Robert J. Elliott

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Abiad, A. (2007). Early Warning Systems for Currency Crises: A Regime-Switching Approach. In: Mamon, R.S., Elliott, R.J. (eds) Hidden Markov Models in Finance. International Series in Operations Research & Management Science, vol 104. Springer, Boston, MA. https://doi.org/10.1007/0-387-71163-5_10

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