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Modelling South African Currency Crises as Structural Changes in the Volatility of the Rand

Listed author(s):
  • Andrew S Duncan
  • Guangling D Liu

This study tests the theory that currency crises are associated with sudden large changes in the structure of foreign exchange market volatility. Due to increases in market uncertainty, crisis periods exhibit abnormally high levels of volatility. By studying short-term changes in volatility dynamics, it is possible to identify the start- and end-dates of crisis periods with a high degree of precision. We use the iterative cumulative sum of squares algorithm to detect multiple shifts in the volatility of rand returns between January 1994 and March 2009. Dummy variables controlling for the detected shifts in variance are incorporated in a GARCH modelling framework. The analysis indicates that previously identified crisis periods in the rand coincide with significant structural changes in market volatility.

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File URL: http://www.econrsa.org/node/163
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Paper provided by Economic Research Southern Africa in its series Working Papers with number 140.

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Date of creation: 2009
Handle: RePEc:rza:wpaper:140
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  1. Obstfeld, Maurice, 1986. "Rational and Self-fulfilling Balance-of-Payments Crises," American Economic Review, American Economic Association, vol. 76(1), pages 72-81, March.
  2. Malik, Farooq, 2003. "Sudden changes in variance and volatility persistence in foreign exchange markets," Journal of Multinational Financial Management, Elsevier, vol. 13(3), pages 217-230, July.
  3. Knedlik, Tobias, 2006. "Signaling Currency Crises in South Africa," IWH Discussion Papers 19/2006, Halle Institute for Economic Research (IWH).
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  6. Tobias Knedlik & Rolf Scheufele, 2008. "Forecasting Currency Crises: Which Methods Signaled The South African Crisis Of June 2006?," South African Journal of Economics, Economic Society of South Africa, vol. 76(3), pages 367-383, 09.
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  9. Berry Wilson & Reena Aggarwal & Carla Inclan, 1996. "Detecting volatility changes across the oil sector," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 16(3), pages 313-330, 05.
  10. Farooq Malik & Bradley Ewing & James Payne, 2005. "Measuring volatility persistence in the presence of sudden changes in the variance of Canadian stock returns," Canadian Journal of Economics, Canadian Economics Association, vol. 38(3), pages 1037-1056, August.
  11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  12. Lastrapes, William D, 1989. "Exchange Rate Volatility and U.S. Monetary Policy: An ARCH Application," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 21(1), pages 66-77, February.
  13. Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
  14. André F. Perold, 2004. "The Capital Asset Pricing Model," Journal of Economic Perspectives, American Economic Association, vol. 18(3), pages 3-24, Summer.
  15. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
  16. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-234, April.
  17. Bera, Anil K & Higgins, Matthew L, 1993. " ARCH Models: Properties, Estimation and Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 7(4), pages 305-366, December.
  18. Robert Engle, 2001. "GARCH 101: The Use of ARCH/GARCH Models in Applied Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 157-168, Fall.
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