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

Listed author(s):
  • Richard T. Baillie
  • Claudio Morana

    ()

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, speci?ed by Gallant (1984)'s flexible functional form. 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.

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File URL: http://www.biblioecon.unito.it/biblioservizi/RePEc/icr/wp2007/ICERwp11-07.pdf
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Paper provided by ICER - International Centre for Economic Research in its series ICER Working Papers - Applied Mathematics Series with number 11-2007.

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Length: 26 pages
Date of creation: Mar 2007
Handle: RePEc:icr:wpmath:11-2007
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  45. repec:knz:cofedp:9914 is not listed on IDEAS
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