IMPLICATIONS FOR HEDGING OF THE CHOICE OF DRIVING PROCESS FOR ONE-FACTOR MARKOV-FUNCTIONAL MODELS

Joanne E. Kennedy and Duy Pham ()
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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

International Journal of Theoretical and Applied Finance (IJTAF), 2013, vol. 16, issue 05, 1-51

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.

Keywords: One-dimensional swap Markov-functional model; Bermudan swaption; correlation; hedging; vega; gamma; parametrization by time and by expiry (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1142/S0219024913500301

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