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Modelling exchange rates volatility with multivariate long-memory ARCH processes

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  • Teyssière, Gilles

Abstract

We consider two multivariate long-memory ARCH models, which extend the univariate long-memory ARCH models, we first consider a long-memory extension of the restricted constant conditional correlations (CCC) model introduced by Bollerslev (1990), and we propose a new unrestricted conditional covariance matrix model which models the conditional covariances as long-memory ARCH processes. We apply these two models to two daily returns on foreign exchanges (FX) rates series, the Pound-US dollar, and the Deutschmark-US dollar. The estimation results for both models show: (i) that the unrestricted model outperforms the restricted CCC model, and (ii) that all the elements of the conditional covariance matrix share the same degree of long-memory for the period April 1979 - January 1997. However, this result does not hold for the floating periods March 1973 - January 1997 and September 1971 - January 1997. This break in the long-term structure may be caused by the European Monetary System inception in March 1979.

Suggested Citation

  • Teyssière, Gilles, 1999. "Modelling exchange rates volatility with multivariate long-memory ARCH processes," SFB 373 Discussion Papers 1999,5, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:19995
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    More about this item

    Keywords

    heteroskedasticity; Long-memory processes; multivariate long-memory ARCH models; multivariate FIGARCH models;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G00 - Financial Economics - - General - - - General

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