IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb649/sfb649dp2006-086.html
   My bibliography  Save this paper

Overreaction and multiple tail dependence at the high-frequency level: The copula rose

Author

Listed:
  • Ng, Wing Lon

Abstract

This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price movements is not always negatively correlated as assumed in the stylized facts in the finance literature. Depending on the sampling frequency, the estimated copulas exhibit some kind of overreaction phenomena and multiple tail dependence, revealing patterns similar to the compass rose.

Suggested Citation

  • Ng, Wing Lon, 2006. "Overreaction and multiple tail dependence at the high-frequency level: The copula rose," SFB 649 Discussion Papers 2006-086, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    • Handle: RePEc:zbw:sfb649:sfb649dp2006-086
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/25169/1/522656870.PDF
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    2. Cornelia Savu & Wing Lon Ng, 2005. "The SCoD Model: Analyzing Durations with a Semiparametric Copula Approach," International Review of Finance, International Review of Finance Ltd., vol. 5(1‐2), pages 55-74, March.
    3. Szpiro, George G., 1998. "Tick size, the compass rose and market nanostructure," Journal of Banking & Finance, Elsevier, vol. 22(12), pages 1559-1569, December.
    4. Joseph Zeira, 2000. "Informational overshooting, booms and crashes," Proceedings, Federal Reserve Bank of San Francisco, issue Apr.
    5. Torben G. Andersen & Tim Bollerslev & Nour Meddahi, 2005. "Correcting the Errors: Volatility Forecast Evaluation Using High-Frequency Data and Realized Volatilities," Econometrica, Econometric Society, vol. 73(1), pages 279-296, January.
    6. Andrew J. Patton, 2006. "Estimation of multivariate models for time series of possibly different lengths," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(2), pages 147-173, March.
    7. Fermanian, Jean-David & Scaillet, Olivier, 2003. "Nonparametric estimation of copulas for time series," Working Papers unige:41797, University of Geneva, Geneva School of Economics and Management.
    8. Kramer, Walter & Runde, Ralf, 1997. "Chaos and the compass rose," Economics Letters, Elsevier, vol. 54(2), pages 113-118, February.
    9. Neville Francis & Valerie A. Ramey, 2006. "The Source of Historical Economic Fluctuations: An Analysis Using Long-Run Restrictions," NBER Chapters, in: NBER International Seminar on Macroeconomics 2004, pages 17-73, National Bureau of Economic Research, Inc.
    10. Huang, Roger D & Stoll, Hans R, 1994. "Market Microstructure and Stock Return Predictions," The Review of Financial Studies, Society for Financial Studies, vol. 7(1), pages 179-213.
    11. Wang, Eliza & Hudson, Robert & Keasey, Kevin, 2000. "Tick size and the compass rose: further insights," Economics Letters, Elsevier, vol. 68(2), pages 119-125, August.
    12. Wang, Huaiqing & Wang, Chen, 2002. "Visibility of the compass rose in financial asset returns: A quantitative study," Journal of Banking & Finance, Elsevier, vol. 26(6), pages 1099-1111, June.
    13. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    14. Chen, Song Xi, 1999. "Beta kernel estimators for density functions," Computational Statistics & Data Analysis, Elsevier, vol. 31(2), pages 131-145, August.
    15. Porter, David & Smith, Vernon L., 2008. "Price Bubbles," Handbook of Experimental Economics Results, in: Charles R. Plott & Vernon L. Smith (ed.), Handbook of Experimental Economics Results, edition 1, volume 1, chapter 30, pages 247-255, Elsevier.
    16. Charlie Cai & Robert Hudson & Kevin Keasey, 2003. "Trading frequency and the compass rose," Applied Economics Letters, Taylor & Francis Journals, vol. 10(8), pages 511-517.
    17. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation and model selection of semiparametric copula-based multivariate dynamic models under copula misspecification," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 125-154.
    18. Meddahi, Nour & Mykland, Per & Shephard, Neil, 2011. "Realized Volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 1-1, January.
    19. Crack, Timothy Falcon & Ledoit, Olivier, 1996. "Robust Structure without Predictability: The "Compass Rose" Pattern of the Stock Market," Journal of Finance, American Finance Association, vol. 51(2), pages 751-762, June.
    20. Bollerslev, Tim & Domowitz, Ian, 1993. "Trading Patterns and Prices in the Interbank Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 48(4), pages 1421-1443, September.
    21. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    22. Russell, Jeffrey R. & Engle, Robert F., 2005. "A Discrete-State Continuous-Time Model of Financial Transactions Prices and Times: The Autoregressive Conditional Multinomial-Autoregressive Conditional Duration Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 166-180, April.
    23. Goodhart, C. A. E. & Figliuoli, L., 1991. "Every minute counts in financial markets," Journal of International Money and Finance, Elsevier, vol. 10(1), pages 23-52, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:hum:wpaper:sfb649dp2006-086 is not listed on IDEAS
    2. Chun Lee & Ike Mathur & Kimberly Gleason, 2005. "The tick/volatility ratio as a determinant of the compass rose pattern," The European Journal of Finance, Taylor & Francis Journals, vol. 11(2), pages 93-109.
    3. Mitchell, Heather & McKenzie, Michael D., 2006. "A note on the Wang and Wang measure of the quality of the compass rose," Journal of Banking & Finance, Elsevier, vol. 30(12), pages 3519-3524, December.
    4. 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.
    5. Antonios Antoniou & Constantinos E. Vorlow, 2004. "Price Clustering and Discreteness: Is there Chaos behind the Noise?," Papers cond-mat/0407471, arXiv.org.
    6. Manner, H., 2007. "Estimation and model selection of copulas with an application to exchange rates," Research Memorandum 056, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    7. Costanza Naguib & Patrick Gagliardini, 2023. "A Semi-nonparametric Copula Model for Earnings Mobility," Diskussionsschriften dp2302, Universitaet Bern, Departement Volkswirtschaft.
    8. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    9. Wang, Huaiqing & Wang, Chen, 2002. "Visibility of the compass rose in financial asset returns: A quantitative study," Journal of Banking & Finance, Elsevier, vol. 26(6), pages 1099-1111, June.
    10. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    11. Lee, Tae-Hwy & Yang, Weiping, 2014. "Granger-causality in quantiles between financial markets: Using copula approach," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 70-78.
    12. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2011. "An inflated multivariate integer count hurdle model: an application to bid and ask quote dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(4), pages 669-707, June.
    13. Alexander Mende, 2006. "09/11 on the USD/EUR foreign exchange market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(3), pages 213-222.
    14. Katarzyna Bien & Ingmar Nolte & Winfried Pohlmeier, 2008. "A multivariate integer count hurdle model: theory and application to exchange rate dynamics," Studies in Empirical Economics, in: Luc Bauwens & Winfried Pohlmeier & David Veredas (ed.), High Frequency Financial Econometrics, pages 31-48, Springer.
    15. Julien Chevallier & Benoît Sévi, 2011. "On the realized volatility of the ECX CO 2 emissions 2008 futures contract: distribution, dynamics and forecasting," Annals of Finance, Springer, vol. 7(1), pages 1-29, February.
    16. Huang, Hongming & Kao, Chihwa & Urga, Giovanni, 2008. "Copula-based tests for cross-sectional independence in panel models," Economics Letters, Elsevier, vol. 100(2), pages 224-228, August.
    17. Ole E. Barndorff-Nielsen & Neil Shephard, 2005. "Variation, jumps, market frictions and high frequency data in financial econometrics," OFRC Working Papers Series 2005fe08, Oxford Financial Research Centre.
    18. Constantinos E. Vorlow, 2004. "Stock Price Clustering and Discreteness: The "Compass Rose" and Predictability," Papers cond-mat/0408013, arXiv.org.
    19. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    20. Sylwia Nowak, 2008. "How Do Public Announcements Affect The Frequency Of Trading In U.S. Airline Stocks?," CAMA Working Papers 2008-38, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    21. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.

    More about this item

    Keywords

    high frequency data; non- and semiparametric copulas; overreaction; tail dependence; compass rose;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:zbw:sfb649:sfb649dp2006-086. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/sohubde.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.