Long memory in foreign-exchange rates

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)Comment/debate

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Original languageEnglish
Pages (from-to)93-101
Journal / PublicationJournal of Business and Economic Statistics
Issue number1
Publication statusPublished - Jan 1993
Externally publishedYes


Using the Geweke-Porter-Hudak test, we find evidence of long memory in exchange-rate data. This implies that the empirical evidence of unit roots in exchange rates may not be robust to long-memory alternatives. Fractionally integrated autoregressive moving average (ARFIMA) models are estimated by both the time-domain exact maximum likelihood (ML) method and the frequency-domain approximate ML method. Impulse-response functions and forecasts based on these estimated ARFIMA models are evaluated to gain insight into the long-memory characteristics of exchange rates. Some tentative explanations of the long memory found in the exchange rates are discussed. © 1993 American Statistical Association.

Research Area(s)

  • Exchange-rate dynamics, Forecast, GPH test, Impulse-response function, Maximum likelihood estimation