Forecasting volatility in developing countries' nominal exchange returns
AbstractThis 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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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Applied Financial Economics.
Volume (Year): 23 (2013)
Issue (Month): 21 (November)
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Web page: http://www.tandfonline.com/RAFE20
Other versions of this item:
- Antonakakis, Nikolaos & Darby, Julia, 2012. "Forecasting Volatility in Developing Countries' Nominal Exchange Returns," MPRA Paper 40875, University Library of Munich, Germany.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
- G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
- F31 - International Economics - - International Finance - - - Foreign Exchange
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