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Long memory in the R$ / US$ exchange rate: A robust analysis

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  • Laurini, Márcio Poletti
  • Portugal, Marcelo Savino

Abstract

This article shows that the evidence of long memory for the daily R$ /US$ exchange rate series after the implementation of the Real Plan is not robust when we analyze the existence of structural breaks in this series. We demonstrate that the long memory observed is caused by changes in the structure of variance, captured by a Markov Switching model in all the parameters. A Monte Carlo study shows that the long memory structure can be induced by changes in the unconditional variance parameters, and that the data generating mechanism is a short memory process.

Suggested Citation

  • Laurini, Márcio Poletti & Portugal, Marcelo Savino, 2004. "Long memory in the R$ / US$ exchange rate: A robust analysis," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 24(1), May.
  • Handle: RePEc:sbe:breart:v:24:y:2004:i:1:a:2705
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    References listed on IDEAS

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    1. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    2. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    3. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    4. Granger, C. W. J., 1980. "Long memory relationships and the aggregation of dynamic models," Journal of Econometrics, Elsevier, vol. 14(2), pages 227-238, October.
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    Cited by:

    1. Quinton Morris & Gary Van Vuuren & Paul Styger, 2009. "Further Evidence Of Long Memory In The South African Stock Market," South African Journal of Economics, Economic Society of South Africa, vol. 77(1), pages 81-101, March.
    2. Chatziantoniou, Ioannis & Filis, George & Floros, Christos, 2017. "Asset prices regime-switching and the role of inflation targeting monetary policy," Global Finance Journal, Elsevier, vol. 32(C), pages 97-112.
    3. Sergio Da Silva & Annibal Figueiredo & Iram Gleria & Raul Matsushita, 2007. "Hurst exponents, power laws, and efficiency in the Brazilian foreign exchange market," Economics Bulletin, AccessEcon, vol. 7(1), pages 1-11.
    4. repec:ebl:ecbull:v:7:y:2007:i:1:p:1-11 is not listed on IDEAS

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