IDEAS home Printed from https://ideas.repec.org/a/bpj/sndecm/v12y2008i3n3.html
   My bibliography  Save this article

Optimal Test for Markov Switching GARCH Models

Author

Listed:
  • Hu Liang

    () (University of Leeds)

  • Shin Yongcheol

    () (University of Leeds)

Abstract

Empirically, the sum of GARCH parameter estimates is found to be close to unity, suggesting that the conditional volatility of most stock return data are likely to follow an integrated GARCH (IGARCH) process. However, such an extremely high persistence in unconditional variance may be overstated because of neglected structural breaks or parameter changes. As a result it is important to distinguish between these two processes, one being a globally stationary process and the other being a nonstationary IGARCH process. Though there are a number of studies modelling asymmetry leverage effects and advancing a battery of specification tests, studies that directly propose specification tests against Markov switching (MS) GARCH models are almost nonexistent. This paper develops such tests against MS-GARCH processes, which is shown to be asymptotically equivalent to the LR test. Furthermore, we consider the case in which the conditional variance follows an IGARCH process under the null whilst it is globally stationary under the alternative. Monte Carlo studies show that our proposed tests have a good finite sample performance. In an application to the weekly stock return data for five East Asian emerging markets, we find strong evidence in favor of MS-GARCH models.

Suggested Citation

  • Hu Liang & Shin Yongcheol, 2008. "Optimal Test for Markov Switching GARCH Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(3), pages 1-27, September.
  • Handle: RePEc:bpj:sndecm:v:12:y:2008:i:3:n:3
    as

    Download full text from publisher

    File URL: https://www.degruyter.com/view/j/snde.2008.12.3/snde.2008.12.3.1528/snde.2008.12.3.1528.xml?format=INT
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    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. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, pages 121-138.
    2. Engle, Robert F & Ng, Victor K, 1993. " Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    3. Hansen, Bruce E, 1996. "Inference When a Nuisance Parameter Is Not Identified under the Null Hypothesis," Econometrica, Econometric Society, vol. 64(2), pages 413-430, March.
    4. Dueker, Michael J, 1997. "Markov Switching in GARCH Processes and Mean-Reverting Stock-Market Volatility," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 26-34, January.
    5. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    6. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, pages 93-115.
    7. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, pages 1383-1414.
    8. Celso Brunetti & Roberto S. Mariano & Chiara Scotti & Augustine H. H. Tan, 2003. "Markov Switching Garch Models of Currency Crises in Southeast Asia," PIER Working Paper Archive 03-008, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    9. Thomas Mikosch & Cătălin Stărică, 2004. "Nonstationarities in Financial Time Series, the Long-Range Dependence, and the IGARCH Effects," The Review of Economics and Statistics, MIT Press, pages 378-390.
    10. Chesher, Andrew D, 1984. "Testing for Neglected Heterogeneity," Econometrica, Econometric Society, vol. 52(4), pages 865-872, July.
    11. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, pages 307-327.
    12. Jensen, S ren Tolver & Rahbek, Anders, 2004. "Asymptotic Inference For Nonstationary Garch," Econometric Theory, Cambridge University Press, vol. 20(06), pages 1203-1226, December.
    13. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    14. Garcia, Rene, 1998. "Asymptotic Null Distribution of the Likelihood Ratio Test in Markov Switching Models," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 763-788, August.
    15. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    16. Felix Chan & Michael McAleer, 2002. "Maximum likelihood estimation of STAR and STAR-GARCH models: theory and Monte Carlo evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 509-534.
    17. Busch, Thomas, 2005. "A robust LR test for the GARCH model," Economics Letters, Elsevier, vol. 88(3), pages 358-364, September.
    18. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
    19. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    20. Guglielmo Maria Caporale & Nikitas Pittis & Nicola Spagnolo, 2003. "IGARCH models and structural breaks," Applied Economics Letters, Taylor & Francis Journals, vol. 10(12), pages 765-768.
    21. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    2. Joanna Janczura & Rafał Weron, 2013. "Goodness-of-fit testing for the marginal distribution of regime-switching models with an application to electricity spot prices," AStA Advances in Statistical Analysis, Springer;German Statistical Society, pages 239-270.
    3. Janczura, Joanna & Weron, Rafal, 2010. "Goodness-of-fit testing for regime-switching models," MPRA Paper 22871, University Library of Munich, Germany.
    4. Thomas Chuffart, 2015. "Selection Criteria in Regime Switching Conditional Volatility Models," Econometrics, MDPI, Open Access Journal, vol. 3(2), pages 1-28, May.

    More about this item

    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:bpj:sndecm:v:12:y:2008:i:3:n:3. 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: (Peter Golla). General contact details of provider: https://www.degruyter.com .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.