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

In: Hidden Markov Models in Finance

Author

Listed:
  • Abdul Abiad

    (International Monetary Fund)

Abstract

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.

Suggested Citation

  • Abdul Abiad, 2007. "Early Warning Systems for Currency Crises: A Regime-Switching Approach," International Series in Operations Research & Management Science, in: Rogemar S. Mamon & Robert J. Elliott (ed.), Hidden Markov Models in Finance, chapter 10, pages 155-184, Springer.
    • Handle: RePEc:spr:isochp:978-0-387-71163-8_10
    DOI: 10.1007/0-387-71163-5_10
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    Citations

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    Cited by:

    1. Zhang, Xun & He, Zongyue & Zhu, Jiali & Li, Jing, 2018. "Quantity of finance and financial crisis: A non-monotonic investigation☆," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 129-139.
    2. Wang, Peiwan & Zong, Lu, 2023. "Does machine learning help private sectors to alarm crises? Evidence from China’s currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    3. Duprey, Thibaut & Klaus, Benjamin, 2017. "How to predict financial stress? An assessment of Markov switching models," Working Paper Series 2057, European Central Bank.
    4. Cees Diks & Cars Hommes & Juanxi Wang, 2019. "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, vol. 57(4), pages 1201-1228, October.
    5. Duprey, Thibaut & Klaus, Benjamin, 2022. "Early warning or too late? A (pseudo-)real-time identification of leading indicators of financial stress," Journal of Banking & Finance, Elsevier, vol. 138(C).

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