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Forecasting volatility in developing countries' nominal exchange returns

  • N. Antonakakis
  • J. Darby

This article identifies the best models for forecasting the volatility of daily exchange returns of developing countries. An emerging consensus in the recent literature focusing on industrialized countries has noted the superior performance of the Fractionally Integrated Generalized Autoregressive Conditionally Heteroscedastic (FIGARCH) model in the case of industrialized countries, a result that is reaffirmed here. However, we show that when dealing with developing countries' data the IGARCH model results in substantial gains in terms of the in-sample results and out-of-sample forecasting performance.

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File URL: http://hdl.handle.net/10.1080/09603107.2013.844323
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Article provided by Taylor & Francis Journals in its journal Applied Financial Economics.

Volume (Year): 23 (2013)
Issue (Month): 21 (November)
Pages: 1675-1691

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Handle: RePEc:taf:apfiec:v:23:y:2013:i:21:p:1675-1691
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  1. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
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  17. repec:cup:cbooks:9780521378574 is not listed on IDEAS
  18. Vilasuso, Jon, 2002. "Forecasting exchange rate volatility," Economics Letters, Elsevier, vol. 76(1), pages 59-64, June.
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