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Simulated Swaption Delta–Hedging In The Lognormal Forward Libor Model

Author

Listed:
  • TIM DUN

    (Department of Chemical Engineering, University of Sydney, NSW 2006, Australia)

  • GEOFF BARTON

    (Department of Chemical Engineering, University of Sydney, NSW 2006, Australia)

  • ERIK SCHLÖGL

    (School of Finance and Economics, University of Technology, Sydney, NSW 2007, Australia)

Abstract

Alternative approaches to hedging swaptions are explored and tested by simulation. Hedging methods implied by the Black swaption formula are compared with a lognormal forward LIBOR model approach encompassing all the relevant forward rates. The simulation is undertaken within the LIBOR model framework for a range of swaptions and volatility structures. Despite incompatibilities with the model assumptions, the Black method performs equally well as the LIBOR method, yielding very similar distributions for the hedging profit and loss — even at high rehedging frequencies. This result demonstrates the robustness of the Black hedging technique and implies that — being simpler and generally better understood by financial practitioners — it would be the preferred method in practice.

Suggested Citation

  • Tim Dun & Geoff Barton & Erik Schlögl, 2001. "Simulated Swaption Delta–Hedging In The Lognormal Forward Libor Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 4(04), pages 677-709.
    • Handle: RePEc:wsi:ijtafx:v:04:y:2001:i:04:n:s0219024901001127
    DOI: 10.1142/S0219024901001127
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    References listed on IDEAS

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    1. Miltersen, Kristian R & Sandmann, Klaus & Sondermann, Dieter, 1997. "Closed Form Solutions for Term Structure Derivatives with Log-Normal Interest Rates," Journal of Finance, American Finance Association, vol. 52(1), pages 409-430, March.
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    3. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    4. Antje Dudenhausen & Erik Schlögl & Lutz Schlögl, 1999. "Robustness of Gaussian Hedges and the Hedging of Fixed Income Derivatives," Research Paper Series 19, Quantitative Finance Research Centre, University of Technology, Sydney.
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    Cited by:

    1. Jacques Van Appel & Thomas A. Mcwalter, 2018. "Efficient Long-Dated Swaption Volatility Approximation In The Forward-Libor Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-26, June.
    2. Erik Schlögl, 2001. "Arbitrage-Free Interpolation in Models of Market Observable Interest Rates," Research Paper Series 71, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. Antonis Papapantoleon & John Schoenmakers & David Skovmand, 2011. "Efficient and accurate log-L\'evy approximations to L\'evy driven LIBOR models," Papers 1106.0866, arXiv.org, revised Jan 2012.
    4. Antonis Papapantoleon & John Schoenmakers & David Skovmand, 2011. "Efficient and accurate log-Lévi approximations to Lévi driven LIBOR models," CREATES Research Papers 2011-22, Department of Economics and Business Economics, Aarhus University.
    5. Antonis Papapantoleon & David Skovmand, 2010. "Picard Approximation of Stochastic Differential Equations and Application to Libor Models," CREATES Research Papers 2010-40, Department of Economics and Business Economics, Aarhus University.
    6. Maria Siopacha & Josef Teichmann, 2010. "Weak and strong Taylor methods for numerical solutions of stochastic differential equations," Quantitative Finance, Taylor & Francis Journals, vol. 11(4), pages 517-528.
    7. Antonis Papapantoleon & Maria Siopacha, 2009. "Strong Taylor approximation of stochastic differential equations and application to the L\'evy LIBOR model," Papers 0906.5581, arXiv.org, revised Oct 2010.
    8. Erik Schlögl, 2002. "Extracting the Joint Volatility Structure of Foreign Exchange and Interest Rates from Option Prices," Research Paper Series 79, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Antonis Papapantoleon & David Skovmand, 2010. "Picard approximation of stochastic differential equations and application to LIBOR models," Papers 1007.3362, arXiv.org, revised Jul 2011.

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