IDEAS home Printed from https://ideas.repec.org/p/ecb/ecbwps/2002199.html
   My bibliography  Save this paper

Time variation in the tail behaviour of bunds futures returns

Author

Listed:
  • Upper, Christian
  • Werner, Thomas

Abstract

The present paper focuses on three questions: (i) Are heavy tails a relevant feature of the distribution of BUND futures returns? (ii) Is the tail behaviour constant over time? (iii) If it is not, can we use the tail index as an indicator for financial market risk and does it add value in addition to classical indicators? The answers to these questions are (i) yes, (ii) no, and (iii) yes. The tail index is on average around 3, implying the nonexistence of the fourth moments. A recently developed test for changes in the tail behaviour indicated several breaks in the degree of heaviness of the return tails. Interestingly, the tails of the return distribution do not move in parallel to realised volatility. This suggests that the tails of futures returns contain information for risk management that complements that gained from more standard statistical measures. JEL Classification: C14, G13

Suggested Citation

  • Upper, Christian & Werner, Thomas, 2002. "Time variation in the tail behaviour of bunds futures returns," Working Paper Series 199, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:2002199
    Note: 336092
    as

    Download full text from publisher

    File URL: https://www.ecb.europa.eu//pub/pdf/scpwps/ecbwp199.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Caers, Jef & Beirlant, Jan & Vynckier, Petra, 1998. "Bootstrap confidence intervals for tail indices," Computational Statistics & Data Analysis, Elsevier, vol. 26(3), pages 259-277, January.
    3. Thomas Lux, 2001. "The limiting extremal behaviour of speculative returns: an analysis of intra-daily data from the Frankfurt Stock Exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 11(3), pages 299-315.
    4. Chris Brooks, 2005. "Autoregressive Conditional Kurtosis," Journal of Financial Econometrics, Oxford University Press, vol. 3(3), pages 399-421.
    5. Cotter, John, 2001. "Margin exceedences for European stock index futures using extreme value theory," Journal of Banking & Finance, Elsevier, vol. 25(8), pages 1475-1502, August.
    6. Kim, Jeong-Ryeol, 2002. "The stable long-run CAPM and the cross-section of expected returns," Discussion Paper Series 1: Economic Studies 2002,05, Deutsche Bundesbank.
    7. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    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


    Cited by:

    1. Andria, Joseph & di Tollo, Giacomo & Kalda, Jaan, 2022. "The predictive power of power-laws: An empirical time-arrow based investigation," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    2. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    3. Onofrio Panzarino & Francesco Potente & Alfonso Puorro, 2016. "BTP futures and cash relationships: a high frequency data analysis," Temi di discussione (Economic working papers) 1083, Bank of Italy, Economic Research and International Relations Area.
    4. John Cotter & Kevin Dowd, 2010. "Estimating financial risk measures for futures positions: A nonparametric approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 30(7), pages 689-703, July.
    5. Lux, Thomas & Alfarano, Simone, 2016. "Financial power laws: Empirical evidence, models, and mechanisms," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 3-18.
    6. Straetmans, Stefan & Candelon, Bertrand, 2013. "Long-term asset tail risks in developed and emerging markets," Journal of Banking & Finance, Elsevier, vol. 37(6), pages 1832-1844.
    7. Demosthenes Tambakis, 2009. "Feedback trading and intermittent market turbulence," Quantitative Finance, Taylor & Francis Journals, vol. 9(4), pages 477-489.
    8. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    9. Fendel, Ralf & Neumann, Christian, 2021. "Tail risk in the European sovereign bond market during the financial crises: Detecting the influence of the European Central Bank," Global Finance Journal, Elsevier, vol. 50(C).

    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. Thomas Werner & Christian Upper, 2004. "Time variation in the tail behavior of Bund future returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(4), pages 387-398, April.
    2. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    3. Grobys, Klaus, 2023. "Correlation versus co-fractality: Evidence from foreign-exchange-rate variances," International Review of Financial Analysis, Elsevier, vol. 86(C).
    4. G. D. Gettinby & C. D. Sinclair & D. M. Power & R. A. Brown, 2004. "An Analysis of the Distribution of Extreme Share Returns in the UK from 1975 to 2000," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 607-646, June.
    5. Pierre Perron & Eduardo Zorita & Wen Cao & Clifford Hurvich & Philippe Soulier, 2017. "Drift in Transaction-Level Asset Price Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(5), pages 769-790, September.
    6. Harry-Paul Vander Elst, 2015. "FloGARCH: Realizing Long Memory and Asymmetries in Returns Valitility," Working Papers ECARES ECARES 2015-12, ULB -- Universite Libre de Bruxelles.
    7. Leopoldo Catania & Stefano Grassi, 2017. "Modelling Crypto-Currencies Financial Time-Series," CEIS Research Paper 417, Tor Vergata University, CEIS, revised 11 Dec 2017.
    8. Christensen, Kim & Oomen, Roel C.A. & Podolskij, Mark, 2014. "Fact or friction: Jumps at ultra high frequency," Journal of Financial Economics, Elsevier, vol. 114(3), pages 576-599.
    9. Novkovska, Blagica & Serafimovic, Gordana, 2018. "Recognizing The Vulnerability Of Generation Z To Economic And Social Risks," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 9(1), pages 29-37.
    10. Enrique Ter Horst & Abel Rodriguez & Henryk Gzyl & German Molina, 2012. "Stochastic volatility models including open, close, high and low prices," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 199-212, May.
    11. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    12. Nakovski, Dejan & Milenkovski, Ace & Gjorgievski, Mijalce, 2018. "Indicators For Defining The Emitting Areas In Tourism," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 9(1), pages 39-48.
    13. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
    14. Ramazan Gencay & Nikola Gradojevic & Faruk Selcuk & Brandon Whitcher, 2010. "Asymmetry of information flow between volatilities across time scales," Quantitative Finance, Taylor & Francis Journals, vol. 10(8), pages 895-915.
    15. Gordon V. Chavez, 2019. "Dynamic tail inference with log-Laplace volatility," Papers 1901.02419, arXiv.org, revised Jul 2019.
    16. Sylvia J. Soltyk & Felix Chan, 2023. "Modeling time‐varying higher‐order conditional moments: A survey," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 33-57, February.
    17. Eom, Cheoljun & Kaizoji, Taisei & Scalas, Enrico, 2019. "Fat tails in financial return distributions revisited: Evidence from the Korean stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    18. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    19. En-Der Su & Feng-Jeng Lin, 2012. "Two-State Volatility Transition Pricing and Hedging of TXO Options," Computational Economics, Springer;Society for Computational Economics, vol. 39(3), pages 259-287, March.
    20. John Cotter, 2004. "Minimum capital requirement calculations for UK futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 24(2), pages 193-220, February.

    More about this item

    Keywords

    Extreme value theory; futures returns; risk management; Tail index;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

    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:ecb:ecbwps:2002199. 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: Official Publications (email available below). General contact details of provider: https://edirc.repec.org/data/emieude.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.