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Modeling volatility with time-varying FIGARCH models

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  • Belkhouja, Mustapha
  • Boutahary, Mohamed
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    Abstract

    This paper puts the light on a new class of time-varying FIGARCH or TV-FIGARCH processes to model the volatility. This new model has the feature to account for the long memory and the structural change in the conditional variance process. The structural change is modeled by a logistic function allowing the intercept to vary over time. We also implement a modeling strategy for our TV-FIGARCH specification whose performance is examined by a Monte Carlo study. An empirical application to the crude oil price and the S&P 500 index is carried out to illustrate the usefulness of our techniques. The main result of this paper is that the long memory behavior of the absolute returns is not only explained by the existence of the long memory in the volatility but also by deterministic changes in the unconditional variance.

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    Bibliographic Info

    Article provided by Elsevier in its journal Economic Modelling.

    Volume (Year): 28 (2011)
    Issue (Month): 3 (May)
    Pages: 1106-1116

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    Handle: RePEc:eee:ecmode:v:28:y:2011:i:3:p:1106-1116

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    Web page: http://www.elsevier.com/locate/inca/30411

    Related research

    Keywords: FIGARCH Long memory Nonlinear time series Structural change Time-varying parameter model;

    References

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    1. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    2. Eitrheim, Øyvind & Teräsvirta, Timo, 1995. "Testing the Adequacy of Smooth Transition Autoregressive Models," Working Paper Series in Economics and Finance 56, Stockholm School of Economics.
    3. Lobato, Ignacio N & Savin, N E, 1998. "Real and Spurious Long-Memory Properties of Stock-Market Data: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(3), pages 280-83, July.
    4. Andrea Beltratti & Claudio Morana, 2004. "Breaks and Persistency: Macroeconomic Causes of Stock Market Volatility," Working Papers 20, SEMEQ Department - Faculty of Economics - University of Eastern Piedmont.
    5. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    6. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    7. Morana, Claudio & Beltratti, Andrea, 2004. "Structural change and long-range dependence in volatility of exchange rates: either, neither or both?," Journal of Empirical Finance, Elsevier, vol. 11(5), pages 629-658, December.
    8. Christian Conrad & Berthold R. Haag, 2006. "Inequality Constraints in the Fractionally Integrated GARCH Model," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(3), pages 413-449.
    9. Fong, Wai Mun & See, Kim Hock, 2002. "A Markov switching model of the conditional volatility of crude oil futures prices," Energy Economics, Elsevier, vol. 24(1), pages 71-95, January.
    10. Stefan Lundbergh & Timo Teräsvirta, 1999. "Evaluating GARCH Models," Tinbergen Institute Discussion Papers 99-008/4, Tinbergen Institute.
    11. Lobato, I.N. & Savin, N.E., 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Working Papers 96-07, University of Iowa, Department of Economics.
    12. Gourieroux, Christian & Jasiak, Joann, 2001. "Memory and infrequent breaks," Economics Letters, Elsevier, vol. 70(1), pages 29-41, January.
    13. Martin Martens & Dick van Dijk & Michiel de Pooter, 2004. "Modeling and Forecasting S&P 500 Volatility: Long Memory, Structural Breaks and Nonlinearity," Tinbergen Institute Discussion Papers 04-067/4, Tinbergen Institute.
    14. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
    15. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    16. G. William Schwert, 1990. "Business Cycles, Financial Crises, and Stock Volatility," NBER Working Papers 2957, National Bureau of Economic Research, Inc.
    17. William Schwert, G., 1989. "Business cycles, financial crises, and stock volatility : Reply to Shiller," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 31(1), pages 133-137, January.
    18. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    19. Granger, Clive W.J. & Hyung, Namwon, 1999. "Occasional Structural Breaks and Long Memory," University of California at San Diego, Economics Working Paper Series qt4d60t4jh, Department of Economics, UC San Diego.
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    Cited by:
    1. Delavari, Majid & Gandali Alikhani, Nadiya & Naderi, Esmaeil, 2013. "Does long memory matter in forecasting oil price volatility?," MPRA Paper 46356, University Library of Munich, Germany.
    2. Delavari, Majid & Gandali Alikhani, Nadiya, 2012. "The Effect of Crude Oil Price on the Methanol price," MPRA Paper 49727, University Library of Munich, Germany.
    3. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "How do OPEC news and structural breaks impact returns and volatility in crude oil markets? Further evidence from a long memory process," Energy Economics, Elsevier, vol. 42(C), pages 343-354.
    4. Ho, Kin-Yip & Shi, Yanlin & Zhang, Zhaoyong, 2013. "How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 436-456.

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