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Long-memory and shifts in the unconditional variance in the exchange rate euro/US dollar returns

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  • Leila Nouira
  • Ibrahim Ahamada
  • Jamel Jouini
  • Alain Nurbel

Abstract

In this paper two characteristics a priori contradictory and yet coexistent in the daily returns of exchange rate euro/US dollar are drawn. The non-stationarity of the covariance structure of the series is shown and, after the extraction of the unstable variance using the algorithm based on the cumulative sums of squares of Inclan and Tiao (Journal of the American Statistical Association, 1994, 89(427), 913-23), the existence of long-memory in the filtered series. Does the non-stationarity of the unconditional variance explain the phenomenon of long-memory? Thus a classic debate is found of which the exit does not again elucidate.

Suggested Citation

  • Leila Nouira & Ibrahim Ahamada & Jamel Jouini & Alain Nurbel, 2004. "Long-memory and shifts in the unconditional variance in the exchange rate euro/US dollar returns," Applied Economics Letters, Taylor & Francis Journals, vol. 11(9), pages 591-594.
    • Handle: RePEc:taf:apeclt:v:11:y:2004:i:9:p:591-594
    DOI: 10.1080/1350485042000230733
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    1. Ahamada, Ibrahim, 2002. "Tests for covariance stationarity and white noise, with an application to Euro/US dollar exchange rate: An approach based on the evolutionary spectral density," Economics Letters, Elsevier, vol. 77(2), pages 177-186, October.
    2. Loretan, Mico & Phillips, Peter C. B., 1994. "Testing the covariance stationarity of heavy-tailed time series: An overview of the theory with applications to several financial datasets," Journal of Empirical Finance, Elsevier, vol. 1(2), pages 211-248, January.
    3. Pagan, Adrian R. & Schwert, G. William, 1990. "Testing for covariance stationarity in stock market data," Economics Letters, Elsevier, vol. 33(2), pages 165-170, June.
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    Cited by:

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    5. Korkmaz, Turhan & Cevik, Emrah Ismail & Özataç, Nesrin, 2009. "Testing for long memory in ISE using Arfima-Figarch model and structural break test," MPRA Paper 71302, University Library of Munich, Germany.
    6. Argel S. Masa & John Francis T. Diaz, 2017. "Long-memory Modelling and Forecasting of the Returns and Volatility of Exchange-traded Notes (ETNs)," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 11(1), pages 23-53, February.
    7. Mohamed Boutahar & Jamel Jouini, 2007. "A Methodology For Detecting Breaks In The Mean And Covariance Structure Of Time Series," Working Papers halshs-00354249, HAL.
    8. John Francis Diaz & Jo-Hui Chen, 2017. "Testing for Long-memory and Chaos in the Returns of Currency Exchange-traded Notes (ETNs)," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(4), pages 1-2.
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