Advanced Search
MyIDEAS: Login to save this article or follow this journal

Finite-Sample Properties of the Maximum Likelihood Estimator in GARCH(1,1) and IGARCH(1,1) Models: A Monte Carlo Investigation

Contents:

Author Info

  • Lumsdaine, Robin L
Registered author(s):

    Abstract

    This paper compares GARCH(1,1) and IGARCH(1,1) models via a Monte Carlo study of the finite sample properties of the maximum likelihood estimator and related test statistics. While the asymptotic distribution is well approximated by the estimated t statistics, other commonly used statistics do not behave as well. In addition, the estimators themselves are skewed in small samples. For the null hypothesis of IGARCH(1,1), Wald tests typically have the best size while the standard Lagrange multiplier statistic is badly oversized; versions that are robust to possible nonnormality of the data perform marginally better. An empirical example demonstrates these results.

    Download Info

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below under "Related research" whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Bibliographic Info

    Article provided by American Statistical Association in its journal Journal of Business and Economic Statistics.

    Volume (Year): 13 (1995)
    Issue (Month): 1 (January)
    Pages: 1-10

    as in new window
    Handle: RePEc:bes:jnlbes:v:13:y:1995:i:1:p:1-10

    Contact details of provider:
    Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main

    Order Information:
    Web: http://www.amstat.org/publications/index.html

    Related research

    Keywords:

    References

    No references listed on IDEAS
    You can help add them by filling out this form.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as in new window

    Cited by:
    1. Rodrigo Alfaro & Carmen Gloria Silva, 2008. "Measuring Equity Volatility: the case of Chilean Stock Index," Working Papers Central Bank of Chile 462, Central Bank of Chile.
    2. Manabu Asai & Michael McAleer, 2009. "Dynamic Conditional Correlations for Asymmetric Processes," CARF F-Series CARF-F-168, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    3. Christiansen, Charlotte, 2000. "Credit Spreads and the Term Structure of Interest Rates," Finance Working Papers 00-14, University of Aarhus, Aarhus School of Business, Department of Business Studies.
    4. Deb, Partha, 1997. "Finite sample properties of the ARCH class of models with stochastic volatility," Economics Letters, Elsevier, vol. 55(1), pages 27-34, August.
    5. Marcel P. Visser, 2011. "GARCH Parameter Estimation Using High-Frequency Data," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 9(1), pages 162-197, Winter.
    6. 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.
    7. Xu, Xinzhong & Taylor, Stephen J., 1995. "Conditional volatility and the informational efficiency of the PHLX currency options market," Journal of Banking & Finance, Elsevier, vol. 19(5), pages 803-821, August.
    8. Teruo Nakatsuma & Hiroki Tsurumi, 1996. "ARMA-GARCH Models: Bayes Estimation Versus MLE, and Bayes Non-stationarity Test," Departmental Working Papers 199619, Rutgers University, Department of Economics.
    9. Martens, Martin, 2001. "Forecasting daily exchange rate volatility using intraday returns," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 1-23, February.
    10. Błażej Mazur & Mateusz Pipień, 2012. "On the Empirical Importance of Periodicity in the Volatility of Financial Returns - Time Varying GARCH as a Second Order APC(2) Process," Central European Journal of Economic Modelling and Econometrics, CEJEME, vol. 4(2), pages 95-116, June.

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:bes:jnlbes:v:13:y:1995:i:1:p:1-10. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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