Presenting a model for predicting currency crises in Iran

Document Type : Original Article

Authors

1 Ph.D. Candidate in Finance-Financial Engineering, Shahid Beheshti University, Tehran, Iran

2 Assistant Prof., Department of Finance and Insurance, Shahid Beheshti University, Tehran, Iran.

3 Associate Prof., Department of Finance and Insurance, Shahid Beheshti University, Tehran, Iran.

Abstract

Identifying the pattern of exchange rate fluctuations makes it easier to predict currency crises and can help prevent or reduce their harmful consequences. The present study seeks to provide a model to better identify the pattern of exchange rate fluctuations and also predict the likelihood of a currency crisis in Iran in the future. The degree of government intervention in the foreign exchange market affects how this variable fluctuates; therefore, exchange rate fluctuations in Iran (managed floating exchange rate system) can’t be similar to exchange rate fluctuations in developed countries (floating exchange rate system). Despite the large differences in the exchange rate fluctuations of Iran and developed countries, domestic researchers have used Markov's 2-regime model to identify the pattern of Rial changes. using 3 criteria: maximum likelihood, Akaik, and Hanan Quinn, we show that for detecting the pattern of rial changes, the Markov switching 3-regime model is better than Markov switching 2-regime model. The results also show that 2-regime model fits better with euro and pound fluctuations. Forecasts show that the probability of Iran’s presence in the Currency Crisis Regime in the next one or two years is decreasing and the probability of Relative Stable Regime is increasing. Therefore, we predict that in the coming years, Iran will enter a new period of Relative Stable Regime. The present study has been conducted in the period of 1387 to 1400.

Keywords

References

  1. Abdelsalam, M. A. M., & Abdel-Latif, H. (2020). An optimal early warning system for currency crises under model uncertainty. Central Bank Review.
  2. Aghion, P., Bacchetta, P., & Banerjee, A. J. E. e. r. (2001). Currency crises and monetary policy in an economy with credit constraints. 45(7), 1121-1150.
  3. Alaminos, D., Becerra-Vicario, R., Fernández-Gámez, M. Á., & Cisneros Ruiz, A. J. (2019). Currency Crises Prediction Using Deep Neural Decision Trees. 9(23), 27-52
  4. Alstadheim, R., Bjørnland, H. C., & Maih, J. (2021). Do central banks respond to exchange rate movements? A Markov-switching structural investigation of commodity exporters and importers. Energy Economics, 96, 105138.
  5. Arbaa, O., & Varon, E. (2019). Turkish currency crisis – Spillover effects on European banks. Borsa Istanbul Review, 19(4), 372-378.
  6. Bilson, J. F. J. T. I. E. (1980). Leading indicators of currency devaluations. 22(3), 21-23.
  7. Bodart, V., & Carpantier, J. F. (2020). Currency collapses and output dynamics in commodity dependent countries. Emerging Markets Review, 42, 100669.
  8. Bollerslev, T. (1987). A conditionally heteroskedastic time series model for speculative prices and rates of return. The review of economics statistics, 542-547.
  9. Burnside, C., Eichenbaum, M., & Rebelo, S. (2004). Government guarantees and self-fulfilling speculative attacks. J Journal of Economic Theory, 119(1), 31-63.
  10. Bussiere, M., & Fratzscher, M. (2006). Towards a new early warning system of financial crises. journal of International Money Finance, 25(6), 953-973.
  11. Chan, J. C. C., & Santi, C. (2021). Speculative bubbles in present-value models: A Bayesian Markov-switching state space approach. Journal of Economic Dynamics and Control, 127, 104101.
  12. Chong, T. T. L., & Yan, I. K. (2018). Forecasting currency crises with threshold models. International Economics, 156, 156-174.
  13. Clark, P. K. J. E. j. o. t. E. S. (1973). A subordinated stochastic process model with finite variance for speculative prices. 135-155.
  14. Eijffinger, S. C. W., & Karataş, B. (2019). Together or apart? The relationship between currency and banking crises. Journal of Banking & Finance, 105631.
  15. Engel, C., & Hamilton, J. D. J. T. A. E. R. (1990). Long swings in the dollar: Are they in the data and do markets know it? , 689-713.
  16. Engle, R. F. J. E. J. o. t. e. s. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. 987-1007.
  17. Fischer, S. (2001). Exchange Rate Regimes and Crisis Prevention in Emerging Market Economies. Paper presented at the 4th Annual Conference of the Brookings Wharton Papers on Financial Services. International Monetary Fund.
  18. Fratzscher, M. (2003). On currency crises and contagion. J International Journal of Finance Economics, 8(2), 109-129.
  19. Gangopadhyay, P. (2020). A new & simple model of currency crisis: Bifurcations and the emergence of a bad equilibrium. Physica A: Statistical Mechanics and its Applications, 538, 122860.
  20. Garcia, R., & Perron, P. (1996). An analysis of the real interest rate under regime shifts. The review of economics statistics, 111-125.
  21. Glick, R., & Hutchison, M. M. (2011). Currency crises. Paper presented at the Federal Reserve Bank of San Francisco.
  22. Hamilton, J. D. J. E. J. o. t. E. S. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. 357-384.
  23. Hamilton, J. D. J. P. U. P., Princeton. (1994). Time series econometrics.
  24. Heriqbaldi, U., Widodo, W., & Ekowati, D. (2019). Real Exchange Rate Misalignment and Currency Crisis. J Bulletin of Indonesian Economic Studies(just-accepted), 1-29.
  25. Hwang, S., Satchell, S. E., & Pereira, P. L. V. (2004). How persistent is volatility? An answer with Markov regime switching stochastic volatility models. Retrieved from
  26. Kaminsky, G., Lizondo, S., & Reinhart, C. M. J. S. P. (1998). Leading indicators of currency crises. 45(1), 1-48.
  27. Kim, C.-J., & Nelson, C. R. J. M. P. B. (1999). State-space models with regime switching: classical and Gibbs-sampling approaches with applications. 1.
  28. Klaassen, F. (2005). Long swings in exchange rates: are they really in the data? Journal of Business Economic Statistics, 23(1), 87-95.
  29. Krugman, P.(1979) A model of balance-of-payments crises. Journal of money, credit banking, 11(3), 311-325.
  30. Lien, D., Lee, G., Yang, L., & Zhang, Y. (2018). Volatility spillovers among the U.S. and Asian stock markets: A comparison between the periods of Asian currency crisis and subprime credit crisis. The North American Journal of Economics and Finance, 46, 187-201.
  31. Mehin Aslani Nia, N., salmani, b., Fallahi, F., & Asgharpour, H. (2020). The effect of currency crisis on GDP dynamics: PGLS approach Quarterly Journal of Applied Theories of Economics. 7(1), 185-210. (In Persian)
  32. Nakatani, R. (2017). Structural vulnerability and resilience to currency crisis: Foreign currency debt versus export. The North American Journal of Economics and Finance, 42, 132-143.
  33. Nakatani, R. (2018). Real and financial shocks, exchange rate regimes and the probability of a currency crisis. Journal of Policy Modeling, 40(1), 60-73.
  34. Park, K. Y., & Kim, S. (2019). Detecting currency manipulation: An application of a state-space model with Markov switching. Japan and the World Economy, 49, 50-60.
  35. Ricardo, D. (1955). The Works and Correspondence of David Ricardo: Volume 10, Biographical Miscellany (Vol. 10): Cambridge University Press.
  36. Rickards, J. (2012). Currency wars: the making of the next global crisis: Penguin.
  37. Sadeghi Amroabadi, B., & Mahmoudinia, D. (2020). Simultaneous Occurrence of Banking Debt and Currency Crises (Triple Crises) in Iranian Economy and Its Determining Factors During the Period 1980-2017 Journal of Economic Modeling Research. 10(39), 187-240 (In Persian)
  38. salmani, b., asgharpour, h., & KALAMI, m. (2019). Designing an Early Warning System for the Currency Crises in Iran Logit and Markov Switching Approaches %J new economy and trad. 14(3), 97-124. (In Persian)
  39. Sevim, C., Oztekin, A., Bali, O., Gumus, S., & Guresen, E. (2014). Developing an early warning system to predict currency crises. European Journal of Operational Research, 237(3), 1095-1104.
  40. tayebi, S., & Mohammadzadeh, A. ( 2010). The Impact of Capital Control on Currency Crises in Developing Countries. . Iranian Journal of Economic Research,, 14(43), 161-187. (In Persian)
  41. Tayebnia, A., Mehrara, M., & Akhtari, A. (2019). Rational Speculative Bubbles in Iran Informal Exchange Rate and Currency Crisis: Time-varying probabilities Markov regime switching approach %J Economics Research. 19(74), 111-164 (In Persian)
  42. Xu, L., Kinkyo, T., & Hamori, S. (2018). Predicting Currency Crises: A Novel Approach Combining Random Forests and Wavelet Transform. 11. 86(4).
Financial Management Perspective
Volume 12, Issue 37
April 2022
Pages 147-173

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