Modeling long memory and structural breaks in conditional variances: An adaptive FIGARCH approach

Arbeitspapier

This paper introduces a new long memory volatility process, denoted by Adaptive FIGARCH, or A-FIGARCH, which is designed to account for both long memory and structural change in the conditional variance process. Structural change is modeled by allowing the intercept to follow a slowly varying function, specified by Gallant (1984)'s flexible functional form. A Monte Carlo study finds that the A-FIGARCH model outperforms the standard FIGARCH model when structural change is present, and performs at least as well in the absence of structural instability. An empirical application to stock market volatility is also included to illustrate the usefulness of the technique.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Working Paper ; No. 593

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Statistical Simulation Methods: General ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Foreign Exchange
• Thema: FIGARCH, Long memory, Structural change, Stock market volatility ; ARCH-Modell ; Modell-Spezifikation ; Simulation ; Zeitreihenanalyse

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Baillie, Richard T. ; Morana, Claudio
• Ereignis: Veröffentlichung
• (wer): Queen Mary University of London, Department of Economics
• (wo): London
• (wann): 2007

Weitere Informationen

• Handle: http://hdl.handle.net/10419/62853
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ