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Long Memory and Volatility Dynamics in the US Dollar Exchange Rate


  • Guglielmo Maria Caporale
  • Luis A. Gil-Alana


This paper focuses on nominal exchange rates, specifically the US dollar rate vis-à-vis the Euro and the Japanese Yen at a daily frequency. We model both absolute values of returns and squared returns using long-memory techniques, being particularly interested in volatility modelling and forecasting given their importance for FOREX dealers. Compared with previous studies using a standard fractional integration framework such as Granger and Ding (1996), we estimate a more general model which allows for dependence not only at the zero but also at other frequencies. The results show differences in the behaviour of the two series: a long-memory cyclical model and a standard I(d) model seem to be the most appropriate for the US dollar rate vis-à-vis the Euro and the Japanese Yen respectively.

Suggested Citation

  • Guglielmo Maria Caporale & Luis A. Gil-Alana, 2010. "Long Memory and Volatility Dynamics in the US Dollar Exchange Rate," Discussion Papers of DIW Berlin 975, DIW Berlin, German Institute for Economic Research.
  • Handle: RePEc:diw:diwwpp:dp975

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    References listed on IDEAS

    1. John Cotter, 2005. "Uncovering long memory in high frequency UK futures," The European Journal of Finance, Taylor & Francis Journals, vol. 11(4), pages 325-337.
    2. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 261-268, July.
    3. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December.
    4. Wang, Changyun, 2004. "Futures trading activity and predictable foreign exchange market movements," Journal of Banking & Finance, Elsevier, vol. 28(5), pages 1023-1041, May.
    5. Philipp Sibbertsen, 2004. "Long memory in volatilities of German stock returns," Empirical Economics, Springer, vol. 29(3), pages 477-488, September.
    6. Andersen, Torben G & Bollerslev, Tim, 1997. " Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns," Journal of Finance, American Finance Association, vol. 52(3), pages 975-1005, July.
    7. Christopher F. Baum & John T. Barkoulas & Mustafa Caglayan, 1999. "Persistence in International Inflation Rates," Southern Economic Journal, Southern Economic Association, vol. 65(4), pages 900-913, April.
    8. Granger, Clive W. J. & Ding, Zhuanxin, 1996. "Varieties of long memory models," Journal of Econometrics, Elsevier, vol. 73(1), pages 61-77, July.
    9. Perron, Pierre & Rodriguez, Gabriel, 2003. "GLS detrending, efficient unit root tests and structural change," Journal of Econometrics, Elsevier, vol. 115(1), pages 1-27, July.
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    11. Luis A. Gil-Alana, 2008. "Fractional integration and structural breaks at unknown periods of time," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 163-185, January.
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    13. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
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    Cited by:

    1. Trenca Ioan & Cociuba Mihail Ioan, 2011. "Modeling Romanian Exchange Rate Evolution With Garch, Tgarch, Garch- In Mean Models," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(special), pages 299-305, July.
    2. Bruno Versailles, 2012. "Market Intergration and Border Effects in Eastern Africa," CSAE Working Paper Series 2012-01, Centre for the Study of African Economies, University of Oxford.

    More about this item


    Fractional integration; Long memory; Exchange rates; Volatility;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • O40 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - General

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