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Modeling exchange volatility in Egypt using GARCH models

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  • Bouoiyour, Jamal
  • Selmi, Refk

Abstract

In this study, we consider the generalized autoregressive conditional heteroscedastic approach in modeling real effective exchange rate in Egypt using monthly data from 1994 to 2009. Various GARCH extensions are performed here. The main results show that real effective exchange rate volatility may have different behaviors based on measures enable to determine it. More importantly, when we take into account volatility clustering (i.e. Standard GARCH), we observe a quite persistence implying a mean reverting variance process. However, when we consider the leverage effect (i.e. Exponential GARCH), we notice a tendency to a long memory which can be itself a source of an explosive process.

Suggested Citation

  • Bouoiyour, Jamal & Selmi, Refk, 2012. "Modeling exchange volatility in Egypt using GARCH models," MPRA Paper 49131, University Library of Munich, Germany, revised Mar 2013.
  • Handle: RePEc:pra:mprapa:49131
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    References listed on IDEAS

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    1. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    2. Higgins, Matthew L & Bera, Anil K, 1992. "A Class of Nonlinear ARCH Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 33(1), pages 137-158, February.
    3. 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.
    4. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    5. Mandelbrot, Benoit B, 1972. "Correction of an Error in "The Variation of Certain Speculative Prices" (1963)," The Journal of Business, University of Chicago Press, vol. 45(4), pages 542-543, October.
    6. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    7. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. Sayo Ayodeji, 2015. "Modeling Asymmetric Effect in African Currency Markets: Evidence from Kenya," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 4(3), pages 1-2.

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    JEL classification:

    • E0 - Macroeconomics and Monetary Economics - - General
    • F14 - International Economics - - Trade - - - Empirical Studies of Trade

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