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Long Memory In Exchange Rates: International Evidence

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  • Christos Floros

Abstract

In this paper we test for the presence of fractional integration, or long memory, in the daily returns of exchange rates using ARFIMA(p,d,q) models. We consider 34 exchange rates against the US dollar (USD) covering the period April 1991 to April 2006. The results suggest that 17 exchange rates show strong evidence of long memory. This indicates that shocks to the exchange rates persist over a long period of time (this is stronger in emerging market economies). This also indicates that these markets are not stable, and hence they offer an opportunity to investors and traders to add some risk to their strategies. The lack of long memory in the daily returns of exchange rates supports the efficient market hypothesis (EMH). These findings are helpful to traders dealing with long dated assets.

Suggested Citation

  • Christos Floros, 2008. "Long Memory In Exchange Rates: International Evidence," The International Journal of Business and Finance Research, The Institute for Business and Finance Research, vol. 2(1), pages 31-39.
    • Handle: RePEc:ibf:ijbfre:v:2:y:2008:i:1:p:31-39
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    Citations

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    Cited by:

    1. Al-Shboul, Mohammad & Alsharari, Nizar, 2019. "The dynamic behavior of evolving efficiency: Evidence from the UAE stock markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 73(C), pages 119-135.
    2. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & You, Kefei, 2018. "Exchange rate linkages between the ASEAN currencies, the US dollar and the Chinese RMB," Research in International Business and Finance, Elsevier, vol. 44(C), pages 227-238.
    3. Atikullah Ibrahim* & Siti Aida Sheikh Hussin & Zalina Zahid & SitiShalizaMohd Khairi, 2018. "Evaluation of Long Memory on the Malaysia Exchange Rate Market," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 653-656:6.
    4. Omane-Adjepong, Maurice & Boako, Gidoen & Alagidede, Paul, 2018. "Modelling heterogeneous speculation in Ghana’s foreign exchange market: Evidence from ARFIMA-FIGARCH and Semi-Parametric methods," MPRA Paper 86617, University Library of Munich, Germany.

    More about this item

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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