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Implications For Hedging Of The Choice Of Driving Process For One-Factor Markov-Functional Models

Author

Listed:
  • JOANNE E. KENNEDY

    (Department of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom)

  • DUY PHAM

    (Department of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom)

Abstract

In this paper, we study the implications for hedging Bermudan swaptions of the choice of the instantaneous volatility for the driving Markov process of the one-dimensional swap Markov-functional model. We find that there is a strong evidence in favor of what we term "parametrization by time" as opposed to "parametrization by expiry". We further propose a new parametrization by time for the driving process which takes as inputs into the model the market correlations of relevant swap rates. We show that the new driving process enables a very effective vega-delta hedge with a much more stable gamma profile for the hedging portfolio compared with the existing ones.

Suggested Citation

  • Joanne E. Kennedy & Duy Pham, 2013. "Implications For Hedging Of The Choice Of Driving Process For One-Factor Markov-Functional Models," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1-51.
    • Handle: RePEc:wsi:ijtafx:v:16:y:2013:i:05:n:s0219024913500301
    DOI: 10.1142/S0219024913500301
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