Abstract
We compare single factor Markov-functional and multi factor market models and the impact of their correlation structures on the hedging performance of Bermudan swaptions. We show that hedging performance of both models is comparable, thereby supporting the claim that Bermudan swaptions can be adequately risk-managed with single factor models. Moreover, we show that the impact of smile can be much larger than the impact of correlation. We use the constant exercise method for calculating risk sensitivities of callable products in market models, which is a modification of the least-squares Monte Carlo method. The hedge results show the constant exercise method enables proper functioning of market models as risk-management tools.
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We are grateful to ABN AMRO Bank for supplying market data. We are also grateful for the comments of Nevena Šelić and seminar participants at the RODEO Research Forum, Antwerp, Belgium. We thank the two anonymous referees for excellent suggestions.
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Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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Pietersz, R., Pelsser, A. A comparison of single factor Markov-functional and multi factor market models. Rev Deriv Res 13, 245–272 (2010). https://doi.org/10.1007/s11147-009-9050-5
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DOI: https://doi.org/10.1007/s11147-009-9050-5
Keywords
- Markov-functional model
- Market model
- Bermudan swaption
- Terminal correlation
- Hedging
- Greeks for callable products
- Smile