An Overview of FIGARCH and Related Time Series Models

نویسندگان

  • Maryam Tayefi
  • T. V. Ramanathan
چکیده

This paper reviews the theory and applications related to fractionally integrated generalized autoregressive conditional heteroscedastic (FIGARCH) models, mainly for describing the observed persistence in the volatility of a time series. The long memory nature of FIGARCHmodels allows to be a better candidate than other conditional heteroscedastic models for modeling volatility in exchange rates, option prices, stock market returns and inflation rates. We discuss some of the important properties of FIGARCH models in this review. We also compare the FIGARCH with the autoregressive fractionally integrated moving average (ARFIMA) model. Problems related to parameter estimation and forecasting using a FIGARCHmodel are presented. The application of a FIGARCH model to exchange rate data is discussed. We briefly introduce some other models, that are closely related to FIGARCH models. The paper ends with some concluding remarks and future directions of research. Zusammenfassung: Dieser Aufsatz bespricht die Theorie und Anwendungen im Zusammenhang mit Fractionally Integrated Generalized Autoregressive Conditional Heteroscedastic (FIGARCH) Modellen, vor allem für die Beschreibung der beobachteten Persistenz in der Volatilität einer Zeitreihe. Die LongMemoryNatur von FIGARCHModellen ermöglicht es, ein besserer Kandidat als andere bedingte heteroskedastische Modelle zur Modellierung der Volatilität bei Wechselkursen, Optionspreisen, Aktienrenditen und Inflationsraten zu sein. Wir diskutieren einige der wichtigsten Eigenschaften von FIGARCH Modellen in diesem Review. Wir vergleichen auch das FIGARCH Modell mit dem Autoregressive Fractionally Integrated Moving Average (ARFIMA) Modell. Probleme im Zusammenhang mit der Parameterschätzung und der Prognose mit FIGARCH Modellen werden vorgestellt. Die Anwendung eines FIGARCHModells auf Wechselkursdaten wird diskutiert. Kurz werden einige andere Modelle vorgestellt, die eng mit FIGARCH Modellen verwandt sind. Der Beitrag endet mit abschließenden Bemerkungen und zukünftige Ausrichtung der Forschung.

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تاریخ انتشار 2012