IDEAS home Printed from https://ideas.repec.org/a/ris/apltrx/0290.html
   My bibliography  Save this article

Joint distribution of stock indices: Methodological aspects of construction and selection of copula models

Author

Listed:
  • Knyazev, Alexander

    () (Astrakhan State University, Astrakhan, Russian Federation)

  • Lepekhin, Oleg

    () (Astrakhan State University, Astrakhan, Russian Federation)

  • Shemyakin, Arkady

    () (University of St. Thomas, St. Paul, USA)

Abstract

The paper discusses the practical aspects of modeling joint distribution of pairs of national stock indices via copula functions. Parameters of marginal distributions and the association parameter describing the dependence structure are estimated using empirical Bayes method numerically implemented with the help of random walk Metropolis algorithm. A comparison of parametric and semiparametric approaches to copula model construction is performed. The problem of selection of a class of pair copula functions approximating such empirical characteristics of stock indices dependence as Kendall’s concordance, joint empirical cumulative distribution function, and tail behavior.

Suggested Citation

  • Knyazev, Alexander & Lepekhin, Oleg & Shemyakin, Arkady, 2016. "Joint distribution of stock indices: Methodological aspects of construction and selection of copula models," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 42, pages 30-53.
    • Handle: RePEc:ris:apltrx:0290
    as

    Download full text from publisher

    File URL: http://pe.cemi.rssi.ru/pe_2016_42_030-053.pdf
    File Function: Full text
    Download Restriction: no

    References listed on IDEAS

    as
    1. Bronshtein , Efim & Prokudina, Elena & Gerasimova, Anna & Dubinskaya, Ksenya, 2011. "Estimation of the interdependence of time series of stocks prices based on copula," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 22(2), pages 22-31.
    2. Marius Hofert & Matthias Scherer, 2011. "CDO pricing with nested Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, vol. 11(5), pages 775-787.
    3. Justel, Ana & Peña, Daniel & Zamar, Rubén, 1997. "A multivariate Kolmogorov-Smirnov test of goodness of fit," Statistics & Probability Letters, Elsevier, vol. 35(3), pages 251-259, October.
    4. You, Leyuan & Daigler, Robert T., 2010. "Is international diversification really beneficial?," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 163-173, January.
    5. T. Ane & L. Ureche-Rangau, 2008. "Time-varying conditional dependence in chinese stock markets," Post-Print hal-00578249, HAL.
    6. Coeurdacier, Nicolas & Guibaud, Stéphane, 2011. "International portfolio diversification is better than you think," Journal of International Money and Finance, Elsevier, vol. 30(2), pages 289-308, March.
    7. repec:spo:wpmain:info:hdl:2441/c8dmi8nm4pdjkuc9g70969520 is not listed on IDEAS
    8. Fortin, Ines & Kuzmics, Christoph, 2002. "Tail-Dependence in Stock-Return Pairs," Economics Series 126, Institute for Advanced Studies.
    9. Twm Evans & David G. McMillan, 2009. "Financial co-movement and correlation: evidence from 33 international stock market indices," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 1(3), pages 215-241.
    10. Anil Sharma & Neha Seth, 2012. "Literature review of stock market integration: a global perspective," Qualitative Research in Financial Markets, Emerald Group Publishing, vol. 4(1), pages 84-122, April.
    11. repec:kap:compec:v:50:y:2017:i:2:d:10.1007_s10614-016-9587-y is not listed on IDEAS
    12. Geert Bekaert & Robert J. Hodrick & Xiaoyan Zhang, 2009. "International Stock Return Comovements," Journal of Finance, American Finance Association, vol. 64(6), pages 2591-2626, December.
    13. EnDer Su, 2017. "Measuring and Testing Tail Dependence and Contagion Risk Between Major Stock Markets," Computational Economics, Springer;Society for Computational Economics, vol. 50(2), pages 325-351, August.
    14. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions. II," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 23(3), pages 98-132.
    15. Puzanova, Natalia, 2011. "A hierarchical Archimedean copula for portfolio credit risk modelling," Discussion Paper Series 2: Banking and Financial Studies 2011,14, Deutsche Bundesbank.
    16. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    17. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    18. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions. III," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 24(4), pages 100-130.
    19. Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 401-419, June.
    20. Kojadinovic, Ivan & Yan, Jun, 2010. "Comparison of three semiparametric methods for estimating dependence parameters in copula models," Insurance: Mathematics and Economics, Elsevier, vol. 47(1), pages 52-63, August.
    21. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    22. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.
    23. Blagoveschensky, Yury, 2012. "Basics of copula’s theory," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 26(2), pages 113-130.
    24. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters,in: THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78 World Scientific Publishing Co. Pte. Ltd..
    25. Fermanian, Jean-David, 2005. "Goodness-of-fit tests for copulas," Journal of Multivariate Analysis, Elsevier, vol. 95(1), pages 119-152, July.
    26. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March.
    27. repec:spo:wpecon:info:hdl:2441/c8dmi8nm4pdjkuc9g70969520 is not listed on IDEAS
    28. Thierry Ane & Loredana Ureche-Rangau & Chiraz Labidi-Makni, 2008. "Time-varying conditional dependence in Chinese stock markets," Applied Financial Economics, Taylor & Francis Journals, vol. 18(11), pages 895-916.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    copula; stock indices; empirical Bayes; semiparametric approach; Metropolis algorithm;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:ris:apltrx:0290. 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: (Anatoly Peresetsky). General contact details of provider: http://appliedeconometrics.cemi.rssi.ru/ .

    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.