Modeling Long Memory and Structural Breaks in Conditional Variances: An Adaptive FIGARCH Approach
Posted: 27 Mar 2007 Last revised: 9 Jun 2013
Date Written: June 1, 2007
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 smooth deterministic process, 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.
Keywords: FIGARCH, long memory, structural change, stock market volatility
JEL Classification: C15, C22, G1
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