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Analysis of drawdowns and drawups in the US$ interest-rate market

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  • Riccardo Rebonato
  • Valerio Gaspari

Abstract

We investigate the statistical properties of drawdowns and drawups in interest rates (US$) using over 10 years' worth of daily data. We analyse the nature of the drawdowns in terms of length of runs, magnitude of the individual price moves and coincidence of their occurrence across the maturity spectrum. We document significant positive autocorrelation for several holding periods, pronounced term structure effects and an unexpectedly low degree of coincidence in the occurrence of drawdowns across the maturity spectrum (despite high correlation in daily moves). By drawing on previous work by Rebonato et al. (2005) we try to provide a coherent explanation for a complex set of empirical observations. An essential ingredient of this explanation appears to be the existence of at least two distinct types (normal and excited) of price dynamics, with different serial correlation properties. We concur with the results by Sornette and Johansen (Significance of log-periodic precursors to financial crashes. Quant. Finance, 2001, 1, 452-471) for different asset classes that very large drawdowns belong to the 'undemocratic' case, and may therefore result from an amplification mechanism.

Suggested Citation

  • Riccardo Rebonato & Valerio Gaspari, 2006. "Analysis of drawdowns and drawups in the US$ interest-rate market," Quantitative Finance, Taylor & Francis Journals, vol. 6(4), pages 297-326.
    • Handle: RePEc:taf:quantf:v:6:y:2006:i:4:p:297-326
    DOI: 10.1080/14697680600680555
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    References listed on IDEAS

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    1. Qiao, Hongzhu & Tsokos, Chris P., 1994. "Parameter estimation of the Weibull probability distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 37(1), pages 47-55.
    2. D. Sornette & A. Johansen, 2001. "Significance of log-periodic precursors to financial crashes," Quantitative Finance, Taylor & Francis Journals, vol. 1(4), pages 452-471.
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    10. Riccardo Rebonato & Dherminder Kainth, 2004. "A Two-Regime, Stochastic-Volatility Extension Of The Libor Market Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(05), pages 555-575.
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    Cited by:

    1. Hongzhong Zhang, 2018. "Stochastic Drawdowns," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 10078, August.
    2. Ren, Fei & Zhong, Li-Xin, 2012. "The price impact asymmetry of institutional trading in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2667-2677.
    3. Zhang, Hongzhong & Leung, Tim & Hadjiliadis, Olympia, 2013. "Stochastic modeling and fair valuation of drawdown insurance," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 840-850.
    4. Mendes, Beatriz Vaz de Melo & Lavrado, Rafael Coelho, 2017. "Implementing and testing the Maximum Drawdown at Risk," Finance Research Letters, Elsevier, vol. 22(C), pages 95-100.
    5. Fei Ren & Li-Xin Zhong, 2011. "Price impact asymmetry of institutional trading in Chinese stock market," Papers 1110.3133, arXiv.org.
    6. Riccardo Rebonato & Jian Chen, 2009. "Evidence for state transition and altered serial codependence in US$ interest rates," Quantitative Finance, Taylor & Francis Journals, vol. 9(3), pages 259-278.

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