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Time variation in the tail behaviour of bunds futures returns

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  • 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

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 0199.

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Date of creation: Dec 2002
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Handle: RePEc:ecb:ecbwps:20020199

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

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References

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  1. 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.
  2. 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.
  3. Cotter, John, 2000. "Margin Exceedences for European Stock Index Futures using Extreme Value Theory," MPRA Paper 3534, University Library of Munich, Germany, revised 2001.
  4. 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.
  5. Chris Brooks & Simon P. Burke & Gita Persand, 2002. "Augoregressive Conditional Kurtosis," ICMA Centre Discussion Papers in Finance icma-dp2002-05, Henley Business School, Reading University.
  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, Research Centre.
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Cited by:
  1. Demosthenes Tambakis, 2009. "Feedback trading and intermittent market turbulence," Quantitative Finance, Taylor & Francis Journals, vol. 9(4), pages 477-489.
  2. john cotter & kevin dowd, 2011. "Estimating financial risk measures for futures positions: a non-parametric approach," Papers 1103.5666, arXiv.org.
  3. 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.
  4. 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.

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