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Testing unit roots and long range dependence of foreign exchange

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  • Zhiping Lu
  • Dominique Guegan

Abstract

Foreign exchange rate plays an important role in international finance. This paper examines unit roots and the long range dependence of 23 foreign exchange rates using Robinson's (1994) test, which is one of the most efficient tests when testing fractional orders of seasonal/cyclical long memory processes. Monte Carlo simulations are carried out to explore the accuracy of the test before implementing the empirical applications
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  • Zhiping Lu & Dominique Guegan, 2011. "Testing unit roots and long range dependence of foreign exchange," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(6), pages 631-638, November.
    • Handle: RePEc:bla:jtsera:v:32:y:2011:i:6:p:631-638
    DOI: j.1467-9892.2011.00720.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-9892.2011.00720.x
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    References listed on IDEAS

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    1. L. A. Gil-Alana & P. M. Robinson, 2001. "Testing of seasonal fractional integration in UK and Japanese consumption and income," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 95-114.
    2. Gil-Alana, L. A. & Robinson, P. M., 1997. "Testing of unit root and other nonstationary hypotheses in macroeconomic time series," Journal of Econometrics, Elsevier, vol. 80(2), pages 241-268, October.
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    Cited by:

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    3. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034.

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    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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