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Jump Distribution Characteristics: Evidence from European Stock Markets

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  • Thierry Ane

    (Finance Department, University of Reims, France)

  • Carole Metais

    (DRM Finance, University Paris Dauphine, France)

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    Abstract

    A comparison of the realized variance and the realized bipower variation provides a nonparametric estimation of the sum of all the intraday squared jump sizes. To recover individual jumps from this overall contribution to the quadratic variation, one needs to estimate both the number of jumps per day and their respective size. We provide a framework to do so and analyze the unconditional distributional properties of the two components of a jump ¡V intensity and size ¡V for three leading European stock market indexes.

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    Bibliographic Info

    Article provided by College of Business, and College of Finance, Feng Chia University, Taichung, Taiwan in its journal International Journal of Business and Economics.

    Volume (Year): 9 (2010)
    Issue (Month): 1 (April)
    Pages: 1-22

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    Handle: RePEc:ijb:journl:v:9:y:2010:i:1:p:1-22

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    Related research

    Keywords: realized volatility; jumps; bipower variation; stock market indexes;

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    References

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    1. Torben G. Andersen & Tim Bollerslev, 1998. "Deutsche Mark-Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies," Journal of Finance, American Finance Association, vol. 53(1), pages 219-265, 02.
    2. 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.
    3. Fulvio Corsi & Davide Pirino & Roberto Reno, 2009. "Volatility Forecasting: The Jumps Do Matter," Global COE Hi-Stat Discussion Paper Series gd08-036, Institute of Economic Research, Hitotsubashi University.
    4. Darrell Duffie & Jun Pan & Kenneth Singleton, 1999. "Transform Analysis and Asset Pricing for Affine Jump-Diffusions," NBER Working Papers 7105, National Bureau of Economic Research, Inc.
    5. Torben G. Andersen & Tim Bollerslev & Per Frederiksen & Morten Ørregaard Nielsen, 2008. "Continuous-Time Models, Realized Volatilities, and Testable Distributional Implications for Daily Stock Returns," Working Papers 1173, Queen's University, Department of Economics.
    6. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    7. Ole E. Barndorff-Nielsen & Neil Shephard, 2003. "Power and bipower variation with stochastic volatility and jumps," Economics Papers 2003-W17, Economics Group, Nuffield College, University of Oxford.
    8. Merton, Robert C., 1976. "Option pricing when underlying stock returns are discontinuous," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 125-144.
    9. Torben G. Andersen & Dobrislav Dobrev & Ernst Schaumburg, 2009. "Jump-Robust Volatility Estimation using Nearest Neighbor Truncation," NBER Working Papers 15533, National Bureau of Economic Research, Inc.
    10. Song Chen, 2000. "Probability Density Function Estimation Using Gamma Kernels," Annals of the Institute of Statistical Mathematics, Springer, vol. 52(3), pages 471-480, September.
    11. Neil Shephard & Ole E. Barndorff-Nielsen, 2003. "Impact of jumps on returns and realised variances: econometric analysis of time-deformed Levy processes," Economics Series Working Papers 2003-W12, University of Oxford, Department of Economics.
    12. Xin Huang & George Tauchen, 2005. "The Relative Contribution of Jumps to Total Price Variance," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(4), pages 456-499.
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    Cited by:
    1. Maciej Kostrzewski, 2014. "Bayesian DEJD model and detection of asymmetric jumps," Papers 1404.2050, arXiv.org.

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