IDEAS home Printed from https://ideas.repec.org/a/prg/jnlpol/v2016y2016i2id1059p127-144.html
   My bibliography  Save this article

Shluková analýza skoků na kapitálových trzích
[Cluster Analysis of Jumps on Capital Markets]

Author

Listed:
  • Jan Hanousek
  • Evžen Kočenda
  • Jan Novotný

Abstract

Cluster Analysis of Jumps on Capital Markets We analyze the behavior and performance of multiple price jump indicators across capital markets and over time. By using high-frequency we perform cluster analysis of price jump indicators that share similar properties in terms of their performance in that they minimize Type I and Type II errors. We show that clusters of price jump indicators do not exhibit equal size. Clusters are stable across stock market indices and time. Detected numbers of price jumps are also stable over time. The recent financial crisis does not seem to affect the overall jumpiness of mature or emerging stock markets. Our results support the stress testing approach of the Basel III. Accords in that the jump component of the volatility process does not need to be treated separately for the purpose of stress testing.

Suggested Citation

  • Jan Hanousek & Evžen Kočenda & Jan Novotný, 2016. "Shluková analýza skoků na kapitálových trzích
    [Cluster Analysis of Jumps on Capital Markets]
    ," Politická ekonomie, University of Economics, Prague, vol. 2016(2), pages 127-144.
  • Handle: RePEc:prg:jnlpol:v:2016:y:2016:i:2:id:1059:p:127-144
    as

    Download full text from publisher

    File URL: http://www.vse.cz/polek/download.php?jnl=polek&pdf=1059.pdf
    Download Restriction: free of charge

    File URL: http://www.vse.cz/polek/1059
    Download Restriction: free of charge

    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. Ana-Maria Dumitru & Giovanni Urga, 2011. "Identifying Jumps in Financial Assets: A Comparison Between Nonparametric Jump Tests," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(2), pages 242-255, October.
    2. Arshanapalli, Bala & Fabozzi, Frank J. & Nelson, William, 2013. "The role of jump dynamics in the risk–return relationship," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 212-218.
    3. Ladislav Krištoufek & Miloslav Vošvrda, 2012. "Efektivita kapitálových trhů: fraktální dimenze, Hurstův exponent a entropie
      [Capital Markets Efficiency: Fractal Dimension, Hurst Exponent and Entropy]
      ," Politická ekonomie, University of Economics, Prague, vol. 2012(2), pages 208-221.
    4. repec:oup:jfinec:v:14:y:2016:i:1:p:29-80. is not listed on IDEAS
    5. Bjørn Eraker & Michael Johannes & Nicholas Polson, 2003. "The Impact of Jumps in Volatility and Returns," Journal of Finance, American Finance Association, vol. 58(3), pages 1269-1300, June.
    6. S. James Press, 1967. "A Compound Events Model for Security Prices," The Journal of Business, University of Chicago Press, vol. 40, pages 317-317.
    7. Jan Hanousek & Evžen Kočenda, 2011. "Foreign News and Spillovers in Emerging European Stock Markets," Review of International Economics, Wiley Blackwell, vol. 19(1), pages 170-188, February.
    8. Ole E. Barndorff-Nielsen & Neil Shephard, 2006. "Econometrics of Testing for Jumps in Financial Economics Using Bipower Variation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 4(1), pages 1-30.
    9. Jan Hanousek & Evzen Kocenda & Jan Novotny, 2014. "Price jumps on European stock markets," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 14(1), pages 10-22, March.
    10. Jiří Witzany, 2013. "Estimating Correlated Jumps and Stochastic Volatilities," Prague Economic Papers, University of Economics, Prague, vol. 2013(2), pages 251-283.
    11. Peter Carr & Liuren Wu, 2010. "Stock Options and Credit Default Swaps: A Joint Framework for Valuation and Estimation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(4), pages 409-449, Fall.
    12. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2011. "Conditional jumps in volatility and their economic determinants," "Marco Fanno" Working Papers 0138, Dipartimento di Scienze Economiche "Marco Fanno".
    13. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling, and Forecasting of Return Volatility," The Review of Economics and Statistics, MIT Press, vol. 89(4), pages 701-720, November.
    14. Torben G. Andersen & Luca Benzoni & Jesper Lund, 2002. "An Empirical Investigation of Continuous-Time Equity Return Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1239-1284, June.
    15. repec:taf:jnlbes:v:30:y:2012:i:2:p:242-255 is not listed on IDEAS
    16. Bjørn Eraker, 2004. "Do Stock Prices and Volatility Jump? Reconciling Evidence from Spot and Option Prices," Journal of Finance, American Finance Association, vol. 59(3), pages 1367-1404, June.
    17. Cecilia Mancini, 2009. "Non-parametric Threshold Estimation for Models with Stochastic Diffusion Coefficient and Jumps," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(2), pages 270-296.
    18. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    19. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    20. Jonathan R. Stroud & Michael S. Johannes, 2014. "Bayesian Modeling and Forecasting of 24-Hour High-Frequency Volatility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1368-1384, December.
    21. Jan Hanousek & Jan Novotný, 2014. "Cenové skoky během finanční nejistoty: od intuice k regulační perspektivě
      [Price Jumps during Financial Crisis: From Intuition to Financial Regulation]
      ," Politická ekonomie, University of Economics, Prague, vol. 2014(1), pages 32-48.
    22. Hanousek Jan & Kočenda Evžen & Novotný Jan, 2012. "The identification of price jumps," Monte Carlo Methods and Applications, De Gruyter, vol. 18(1), pages 53-77, January.
    23. Suzanne S. Lee & Per A. Mykland, 2008. "Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics," Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2535-2563, November.
    24. Jiang, George J. & Oomen, Roel C.A., 2008. "Testing for jumps when asset prices are observed with noise-a "swap variance" approach," Journal of Econometrics, Elsevier, vol. 144(2), pages 352-370, June.
    25. Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003. "Alternative models for stock price dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 225-257.
    26. Vortelinos, Dimitrios I. & Thomakos, Dimitrios D., 2013. "Nonparametric realized volatility estimation in the international equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 34-45.
    27. Massimiliano Caporin & Eduardo Rossi & Paolo Santucci de Magistris, 2016. "Volatility Jumps and Their Economic Determinants," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 14(1), pages 29-80.
    28. Boudt, Kris & Croux, Christophe & Laurent, Sébastien, 2011. "Robust estimation of intraweek periodicity in volatility and jump detection," Journal of Empirical Finance, Elsevier, vol. 18(2), pages 353-367, March.
    29. Peter Nyberg & Anders Wilhelmsson, 2009. "Measuring Event Risk," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(3), pages 265-287, Summer.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    price jumps measures; nonparametric testing; financial econometrics; cluster analysis; Basel agreements;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F37 - International Economics - - International Finance - - - International Finance Forecasting and Simulation: Models and Applications
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    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:prg:jnlpol:v:2016:y:2016:i:2:id:1059:p:127-144. 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: (Frantisek Sokolovsky). General contact details of provider: http://edirc.repec.org/data/uevsecz.html .

    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.