Calibration of Multicurrency LIBOR Market Models
This paper presents a methodf or calibrating a multi currency lognormal LIBOR Market Model to market data of at-the-money caps, swaptions and FX options. By exploiting the fact that multivariate normal distributions are invariant under orthonormal transformations, the calibration problem is decomposed into manageable stages, while maintaining the ability to achieve realistic correlation structures between all modelled market variables.
|Date of creation:||01 Dec 2010|
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- Erik Schlögl, 1999.
"A Multicurrency Extension of the Lognormal Interest Rate Market Models,"
Research Paper Series
20, Quantitative Finance Research Centre, University of Technology, Sydney.
- Erik Schlögl, 2002. "A multicurrency extension of the lognormal interest rate Market Models," Finance and Stochastics, Springer, vol. 6(2), pages 173-196.
- Kay Pilz & Erik Schlogl, 2009. "A Hybrid Commodity and Interest Rate," Research Paper Series 261, Quantitative Finance Research Centre, University of Technology, Sydney.
- 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 409-30, March.
- Miltersen, K. & K. Sandmann & D. Sondermann, 1994. "Closed Form Solutions for Term Structure Derivatives with Log-Normal Interest Rates," Discussion Paper Serie B 308, University of Bonn, Germany.
- Bruce Choy & Tim Dun & Erik Schlögl, 2003. "Correlating Market Models," Research Paper Series 105, Quantitative Finance Research Centre, University of Technology, Sydney.
- Farshid Jamshidian, 1997. "LIBOR and swap market models and measures (*)," Finance and Stochastics, Springer, vol. 1(4), pages 293-330.
- Black, Fischer, 1976. "The pricing of commodity contracts," Journal of Financial Economics, Elsevier, vol. 3(1-2), pages 167-179.
- 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.
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