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Time variation in the tail behaviour of bunds futures returns


  • Upper, Christian
  • Werner, Thomas


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 0199, European Central Bank.
  • Handle: RePEc:ecb:ecbwps:20020199

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    References listed on IDEAS

    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. 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.
    4. 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.
    5. Chris Brooks, 2005. "Autoregressive Conditional Kurtosis," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 3(3), pages 399-421.
    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.
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    Cited by:

    1. 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.
    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. Demosthenes Tambakis, 2009. "Feedback trading and intermittent market turbulence," Quantitative Finance, Taylor & Francis Journals, vol. 9(4), pages 477-489.
    4. 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.
    5. 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.

    More about this item


    extreme value theory; futures returns; risk management; Tail index;

    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


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