Modelling exchange rates volatility with multivariate long-memory ARCH processes

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: SFB 373 Discussion Paper ; No. 1999,5

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Financial Economics: General
• Thema: heteroskedasticity ; Long-memory processes ; multivariate long-memory ARCH models ; multivariate FIGARCH models

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Teyssière, Gilles
• Ereignis: Veröffentlichung
• (wer): Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes
• (wo): Berlin
• (wann): 1999

Weitere Informationen

• Handle: http://hdl.handle.net/10419/61735
• URN: urn:nbn:de:kobv:11-10056020
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ