Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach

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 the smooth ‡exible functional form due to Gallant (1984). A Monte Carlo study …nds 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. Key words: FIGARCH, long memory, structural change, stock market volatility. JEL classi…cation: C15, C22, G1 Acknowledgements: Part of the work reported in this paper was completed while Morana was a Fulbright scholar at Michigan State University. The generosity of the Fulbright Commission and the hospitality of Michigan State University is gratefully acknowledged. The authors are grateful to Andrea Beltratti, Marcelo Fernandes and Christian Conrad for constructive comments. Part of the computations exploited the grid architecture provided to the SEMeQ Department by Avanade of Italy. Claudio Morana also gratefully acknowledges funding by CRT foundation to the project "Grid Computing and Financial Applications".