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IGARCH effects: an interpretation

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  • C. Morana

Abstract

This article shows how IGARCH effects can arise as an artifact of unaccounted structural change. Using daily returns for the DM/US$ and Yen/US$ exchange rates, the finding is shown to have empirical relevance. GARCH models appear to be useful approximations, for short-term forecasting, to a data generating process that shows time varying conditional variance due to switching heteroscedasticity.

Suggested Citation

  • C. Morana, 2002. "IGARCH effects: an interpretation," Applied Economics Letters, Taylor & Francis Journals, vol. 9(11), pages 745-748.
    • Handle: RePEc:taf:apeclt:v:9:y:2002:i:11:p:745-748
    DOI: 10.1080/13504850210127254
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    References listed on IDEAS

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    Cited by:

    1. Yanlin Shi & Yang Yang, 2018. "Modeling High Frequency Data with Long Memory and Structural Change: A-HYEGARCH Model," Risks, MDPI, vol. 6(2), pages 1-28, March.
    2. Guglielmo Maria Caporale & Nikitas Pittis & Nicola Spagnolo, 2003. "IGARCH models and structural breaks," Applied Economics Letters, Taylor & Francis Journals, vol. 10(12), pages 765-768.
    3. Baillie, Richard T. & Morana, Claudio, 2009. "Modelling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1577-1592, August.
    4. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    5. Paul Beaumont & Stefan Norrbin & F. Pinar Yigit, 2007. "Time series evidence on the linkage between the volatility and growth of output," Applied Economics Letters, Taylor & Francis Journals, vol. 15(1), pages 45-48.
    6. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
    7. Lumengo Bonga-Bonga & Jamela Hoveni, 2013. "Volatility Spillovers between the Equity Market and Foreign Exchange Market in South Africa in the 1995-2010 Period," South African Journal of Economics, Economic Society of South Africa, vol. 81(2), pages 260-274, June.
    8. Sajjad Rasoul & Coakley Jerry & Nankervis John C, 2008. "Markov-Switching GARCH Modelling of Value-at-Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-31, September.
    9. Thomas Lee & John Zyren, 2007. "Volatility Relationship between Crude Oil and Petroleum Products," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 35(1), pages 97-112, March.

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