Advanced Search
MyIDEAS: Login to save this paper or follow this series

Realized Copula

Contents:

Author Info

  • Fengler, Matthias

    ()

  • Okhrin, Ostap

    ()

Abstract

We introduce the notion of realized copula. Based on assumptions of the marginal distributions of daily stock returns and a copula family, realized copula is defined as the copula structure materialized in realized covariance estimated from within-day highfrequency data. Copula parameters are estimated in a method-of-moments type of fashion through Höffding's lemma. Applying this procedure day by day gives rise to a time series of copula parameters that is suitably approximated by an autoregressive time series model. This allows us to capture time-varying dependency in our framework. Studying a portfolio riskmanagement application, we find that time-varying realized copula is superior to standard benchmark models in the literature.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://www1.vwa.unisg.ch/RePEc/usg/econwp/EWP-1214.pdf
Download Restriction: no

Bibliographic Info

Paper provided by University of St. Gallen, School of Economics and Political Science in its series Economics Working Paper Series with number 1214.

as in new window
Length: 34 pages
Date of creation: May 2012
Date of revision:
Handle: RePEc:usg:econwp:2012:14

Contact details of provider:
Postal: Dufourstrasse 50, CH - 9000 St.Gallen
Phone: +41 71 224 23 25
Fax: +41 71 224 31 35
Email:
Web page: http://www.seps.unisg.ch/
More information through EDIRC

Related research

Keywords: Realized variance; realized covariance; realized copula; multivariate dependence;

Other versions of this item:

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Ying Chen & Wolfgang Härdle & Uta Pigorsch, 2009. "Localized Realized Volatility Modelling," SFB 649 Discussion Papers SFB649DP2009-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Joan Jasiak & R. Sufana & C. Gourieroux, 2005. "The Wishart Autoregressive Process of Multivariate Stochastic Volatility," Working Papers, York University, Department of Economics 2005_2, York University, Department of Economics.
  3. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2009. "Multivariate Realised Kernels: Consistent Positive Semi-Definite Estimators of the Covariation of Equity Prices with Noise and Non-Synchronous Trading," Global COE Hi-Stat Discussion Paper Series, Institute of Economic Research, Hitotsubashi University gd08-037, Institute of Economic Research, Hitotsubashi University.
  4. Diaa Noureldin & Neil Shephard & Kevin Sheppard, 2011. "Multivariate High-Frequency-Based Volatility (HEAVY) Models," Economics Papers 2011-W01, Economics Group, Nuffield College, University of Oxford.
  5. Andersen, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Ebens, Heiko, 2001. "The distribution of realized stock return volatility," Journal of Financial Economics, Elsevier, Elsevier, vol. 61(1), pages 43-76, July.
  6. Ying Chen & Wolfgang Härdle & Seok-Oh Jeong, 2004. "Nonparametric Risk Management with Generalized Hyperbolic Distributions," SFB 649 Discussion Papers SFB649DP2005-001, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany, revised Aug 2005.
  7. Anderson, Torben G. & Bollerslev, Tim & Diebold, Francis X. & Labys, Paul, 2002. "Modeling and Forecasting Realized Volatility," Working Papers, Duke University, Department of Economics 02-12, Duke University, Department of Economics.
  8. D. Guegan & J. Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 10(4), pages 421-430.
  9. Fulvio Corsi & Davide Pirino & Roberto Renò, 2010. "Threshold bipower variation and the impact of jumps on volatility forecasting," Post-Print, HAL peer-00741630, HAL.
  10. Nikolaus Hautsch & Lada M. Kyj & Roel C.A. Oomen, 2009. "A blocking and regularization approach to high dimensional realized covariance estimation," SFB 649 Discussion Papers SFB649DP2009-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  11. Giacomini, Enzo & Härdle, Wolfgang & Spokoiny, Vladimir, 2009. "Inhomogeneous Dependence Modeling with Time-Varying Copulae," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 27(2), pages 224-234.
  12. Xin Jin & John M. Maheu, 2013. "Modeling Realized Covariances and Returns," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 11(2), pages 335-369, March.
  13. Fulvio Corsi & Stefan Mittnik & Christian Pigorsch & Uta Pigorsch, 2008. "The Volatility of Realized Volatility," Econometric Reviews, Taylor & Francis Journals, Taylor & Francis Journals, vol. 27(1-3), pages 46-78.
  14. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, 05.
  15. repec:hal:journl:halshs-00368334 is not listed on IDEAS
  16. Roxana Halbleib & Valerie Voev, 2010. "Forecasting Multivariate Volatility Using the VARFIMA Model on Realized Covariance Cholesky Factors," Working Papers ECARES, ULB -- Universite Libre de Bruxelles ECARES 2010-041, ULB -- Universite Libre de Bruxelles.
  17. Eric Ghysels & Pedro Santa-Clara & Rossen Valkanov, 2004. "Predicting Volatility: Getting the Most out of Return Data Sampled at Different Frequencies," NBER Working Papers 10914, National Bureau of Economic Research, Inc.
  18. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, Elsevier, vol. 25(5), pages 827-853, August.
  19. M. Bonato & M. Caporin & A. Ranaldo, 2012. "A forecast-based comparison of restricted Wishart autoregressive models for realized covariance matrices," The European Journal of Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 18(9), pages 761-774, October.
  20. Gregory H. Bauer & Keith Vorkink, 2007. "Multivariate Realized Stock Market Volatility," Working Papers, Bank of Canada 07-20, Bank of Canada.
  21. Corsi, Fulvio & Peluso, Stefano & Audrino, Francesco, 2012. "Missing in Asynchronicity: A Kalman-EM Approach for Multivariate Realized Covariance Estimation," Economics Working Paper Series 1202, University of St. Gallen, School of Economics and Political Science.
  22. repec:wop:humbsf:1998-1 is not listed on IDEAS
  23. Andrew J. Patton, 2002. "On the out-of-sample importance of skewness and asymetric dependence for asset allocation," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library 24951, London School of Economics and Political Science, LSE Library.
  24. Giot,Pierre & Laurent,Sebastien, 2001. "Modelling daily value-at-risk using realized volatility and arch type models," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  25. repec:sae:ecolab:v:16:y:2006:i:2:p:1-2 is not listed on IDEAS
  26. Robert F. Engle & Giampiero M. Gallo, 2003. "A Multiple Indicators Model for Volatility Using Intra-Daily Data," NBER Working Papers 10117, National Bureau of Economic Research, Inc.
  27. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, Elsevier, vol. 74(1), pages 3-30, September.
  28. Spokoiny, Vladimir G., 1998. "Estimation of a function with discontinuities via local polynomial fit with an adaptive window choice," SFB 373 Discussion Papers 1998,1, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  29. Neil Shephard & Kevin Sheppard, 2009. "Realising the future: forecasting with high frequency based volatility (HEAVY) models," OFRC Working Papers Series, Oxford Financial Research Centre 2009fe02, Oxford Financial Research Centre.
  30. W. Breymann & A. Dias & P. Embrechts, 2003. "Dependence structures for multivariate high-frequency data in finance," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 3(1), pages 1-14.
  31. Peter R. Hansen & Asger Lunde & Valeri Voev, 2010. "Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility," CREATES Research Papers 2010-74, School of Economics and Management, University of Aarhus.
  32. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, Elsevier, vol. 73(1), pages 5-59, July.
  33. Nikolaus Hautsch & Lada M. Kyj & Peter Malec, 2011. "The Merit of High-Frequency Data in Portfolio Allocation," SFB 649 Discussion Papers SFB649DP2011-059, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  34. Cizek, P. & Haerdle, W. & Spokoiny, V., 2007. "Adaptive Pointwise Estimation in Time-Inhomogeneous Time-Series Models," Discussion Paper, Tilburg University, Center for Economic Research 2007-35, Tilburg University, Center for Economic Research.
  35. 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, American Statistical Association, vol. 96, pages 42-55, March.
  36. Peter Reinhard Hansen & Zhuo Huang & Howard Howan Shek, 2012. "Realized GARCH: a joint model for returns and realized measures of volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 877-906, 09.
  37. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(2), pages 174-196, Spring.
  38. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers, Duke University, Department of Economics 10-06, Duke University, Department of Economics.
  39. Wolfgang Härdle & Ostap Okhrin & Yarema Okhrin, 2008. "Modeling Dependencies in Finance using Copulae," SFB 649 Discussion Papers SFB649DP2008-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  40. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
  41. Audrino, Francesco & Hu, Yujia, 2011. "Volatility Forecasting: Downside Risk, Jumps and Leverage Effect," Economics Working Paper Series 1138, University of St. Gallen, School of Economics and Political Science.
  42. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold, 2007. "Roughing It Up: Including Jump Components in the Measurement, Modeling and Forecasting of Return Volatility," CREATES Research Papers 2007-18, School of Economics and Management, University of Aarhus.
  43. Niall Whelan, 2004. "Sampling from Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 4(3), pages 339-352.
  44. Roxana Chiriac & Valeri Voev, 2008. "Modelling and Forecasting Multivariate Realized Volatility," CREATES Research Papers 2008-39, School of Economics and Management, University of Aarhus.
  45. deB. Harris, Frederick H. & McInish, Thomas H. & Shoesmith, Gary L. & Wood, Robert A., 1995. "Cointegration, Error Correction, and Price Discovery on Informationally Linked Security Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, Cambridge University Press, vol. 30(04), pages 563-579, December.
  46. O. E. Barndorff-Nielsen & P. Reinhard Hansen & A. Lunde & N. Shephard, 2009. "Realized kernels in practice: trades and quotes," Econometrics Journal, Royal Economic Society, Royal Economic Society, vol. 12(3), pages C1-C32, November.
  47. Peter Reinhard Hansen & Zhuo (Albert) Huang & Howard Howan Shek, . "Realized GARCH: A Complete Model of Returns and Realized Measures of Volatility," CREATES Research Papers 2010-13, School of Economics and Management, University of Aarhus.
  48. Cornelia Savu & Mark Trede, 2010. "Hierarchies of Archimedean copulas," Quantitative Finance, Taylor & Francis Journals, Taylor & Francis Journals, vol. 10(3), pages 295-304.
  49. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification," Journal of Econometrics, Elsevier, Elsevier, vol. 135(1-2), pages 125-154.
  50. P. Č�žek & W. H�rdle & V. Spokoiny, 2009. "Adaptive pointwise estimation in time-inhomogeneous conditional heteroscedasticity models," Econometrics Journal, Royal Economic Society, Royal Economic Society, vol. 12(2), pages 248-271, 07.
  51. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, Elsevier, vol. 160(1), pages 93-101, January.
  52. Jeremy Berkowitz & James O'Brien, 2002. "How Accurate Are Value-at-Risk Models at Commercial Banks?," Journal of Finance, American Finance Association, American Finance Association, vol. 57(3), pages 1093-1111, 06.
  53. Wolfgang Karl Härdle & Ostap Okhrin & Yarema Okhrin, 2010. "Time varying Hierarchical Archimedean Copulae," SFB 649 Discussion Papers SFB649DP2010-018, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  54. Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.) 95-24, Board of Governors of the Federal Reserve System (U.S.).
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 in new window

Cited by:
  1. Thorsten Dickhaus & Jakob Gierl, 2012. "Simultaneous test procedures in terms of p-value copulae," SFB 649 Discussion Papers SFB649DP2012-049, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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:usg:econwp:2012:14. 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: (Martina Flockerzi).

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.