Abstract
The term calibration used in the chapter’s title is the term used in finance for root finding or finding an optimal in the least-square sense. The type of problem encountered can be summarized in the following way. A certain number of financial market information, called market quotes, are available. This is for example the par rates of swaps, the prices of futures, the yields of bonds, or the prices of options. We want to use a specific model to compute the present value of other instruments, similar to the original ones, or to compute the risks associated to them. The model is based on a certain number of parameters. Those parameters can be the zero-coupon rates of a curve, the Black implied volatilities, or the volatility parameters of a Libor Market Model.
What we need is implicit – The fast lane to calibration.
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Notes
- 1.
The implementation we used is the OpenGamma Strata 1.0 library. It is open source and available on GitHub at https://github.com/OpenGamma/Strata
- 2.
The implementations used for the performance figures are those in the OpenGamma analytics library. The computations are done on a Mac Pro 3.2Â GHz Quad-core.
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Henrard, M. (2017). Calibration. In: Algorithmic Differentiation in Finance Explained . Financial Engineering Explained. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-53979-9_6
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DOI: https://doi.org/10.1007/978-3-319-53979-9_6
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