IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v114y2012i1p72-75.html
   My bibliography  Save this article

On the origin of high persistence in GARCH-models

Author

Listed:
  • Krämer, Walter
  • Tameze, Baudouin
  • Christou, Konstantinos

Abstract

We show that the (Baillie and Chung, 2001) minimum distance estimates of the GARCH (1,1) model induce spurious persistence in the volatility when there are structural changes in the mean of the process.

Suggested Citation

  • Krämer, Walter & Tameze, Baudouin & Christou, Konstantinos, 2012. "On the origin of high persistence in GARCH-models," Economics Letters, Elsevier, vol. 114(1), pages 72-75.
    • Handle: RePEc:eee:ecolet:v:114:y:2012:i:1:p:72-75
    DOI: 10.1016/j.econlet.2011.09.012
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176511003417
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.econlet.2011.09.012?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kramer, Walter & Azamo, Baudouin Tameze, 2007. "Structural change and estimated persistence in the GARCH(1,1)-model," Economics Letters, Elsevier, vol. 97(1), pages 17-23, October.
    2. Thomas Mikosch & Catalin Starica, 2004. "Non-stationarities in financial time series, the long range dependence and the IGARCH effects," Econometrics 0412005, University Library of Munich, Germany.
    3. Richard T. Baillie & Huimin Chung, 2001. "Estimation of GARCH Models from the Autocorrelations of the Squares of a Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(6), pages 631-650, November.
    4. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    5. Krämer, Walter, 2008. "Long memory with Markov-Switching GARCH," Economics Letters, Elsevier, vol. 99(2), pages 390-392, May.
    6. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
    7. Cătălin Stărică & Clive Granger, 2005. "Nonstationarities in Stock Returns," The Review of Economics and Statistics, MIT Press, vol. 87(3), pages 503-522, August.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Babikir, Ali & Gupta, Rangan & Mwabutwa, Chance & Owusu-Sekyere, Emmanuel, 2012. "Structural breaks and GARCH models of stock return volatility: The case of South Africa," Economic Modelling, Elsevier, vol. 29(6), pages 2435-2443.
    2. Yanlin Shi, 2023. "Long memory and regime switching in the stochastic volatility modelling," Annals of Operations Research, Springer, vol. 320(2), pages 999-1020, January.
    3. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    4. Gürtler, Marc & Rauh, Ronald, 2012. "Challenging traditional risk models by a non-stationary approach with nonparametric heteroscedasticity," Working Papers IF41V1, Technische Universität Braunschweig, Institute of Finance.
    5. Aloui, Chaker & Hamida, Hela ben, 2014. "Modelling and forecasting value at risk and expected shortfall for GCC stock markets: Do long memory, structural breaks, asymmetry, and fat-tails matter?," The North American Journal of Economics and Finance, Elsevier, vol. 29(C), pages 349-380.
    6. Scharth, Marcel & Medeiros, Marcelo C., 2009. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
    7. Azamo, Baudouin Tameze & Krämer, Walter, 2006. "Structural Change and long memory in the GARCH(1,1)-model," Technical Reports 2006,33, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    8. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Discussion Paper 2007-35, Tilburg University, Center for Economic Research.
    9. David E. Rapach & Jack K. Strauss, 2008. "Structural breaks and GARCH models of exchange rate volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 65-90.
    10. Gürtler, Marc & Kreiss, Jens-Peter & Rauh, Ronald, 2009. "A non-stationary approach for financial returns with nonparametric heteroscedasticity," Working Papers IF31V2, Technische Universität Braunschweig, Institute of Finance.
    11. repec:hum:wpaper:sfb649dp2008-002 is not listed on IDEAS
    12. Farooq Malik, 2015. "Revisiting the relationship between risk and return," Review of Quantitative Finance and Accounting, Springer, vol. 44(1), pages 25-40, January.
    13. Pal, Debdatta, 2022. "Does hospitality industry stock volatility react asymmetrically to health and economic crises?," Economic Modelling, Elsevier, vol. 108(C).
    14. Cizek, P., 2010. "Modelling Conditional Heteroscedasticity in Nonstationary Series," Discussion Paper 2010-84, Tilburg University, Center for Economic Research.
    15. Bildirici, Melike & Ersin, Özgür, 2012. "Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models," MPRA Paper 40330, University Library of Munich, Germany, revised May 2012.
    16. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
    17. Gürtler, Marc & Rauh, Ronald, 2009. "Shortcomings of a parametric VaR approach and nonparametric improvements based on a non-stationary return series model," Working Papers IF32V2, Technische Universität Braunschweig, Institute of Finance.
    18. Hillebrand, Eric & Schnabl, Gunther & Ulu, Yasemin, 2009. "Japanese foreign exchange intervention and the yen-to-dollar exchange rate: A simultaneous equations approach using realized volatility," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 490-505, July.
    19. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
    20. Malik, Farooq, 2021. "Volatility spillover between exchange rate and stock returns under volatility shifts," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 605-613.
    21. Krämer, Walter, 2008. "Long memory with Markov-Switching GARCH," Economics Letters, Elsevier, vol. 99(2), pages 390-392, May.

    More about this item

    Keywords

    Minimum distance estimates; Structural change; Long memory; GARCH;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecolet:v:114:y:2012:i:1:p:72-75. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ecolet .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.