Variational sensitivity analysis of parametric Markovian market models

Volume 83 / 2008

Norbert Hilber, Christoph Schwab, Christoph Winter Banach Center Publications 83 (2008), 85-106 MSC: Primary 60J25; Secondary 65M60, 65N30. DOI: 10.4064/bc83-0-6

Abstract

Parameter sensitivities of prices for derivative contracts play an important role in model calibration as well as in quantification of model risk. In this paper a unified approach to the efficient numerical computation of all sensitivities for Markovian market models is presented. Variational approximations of the integro-differential equations corresponding to the infinitesimal generators of the market model differentiated with respect to the model parameters are employed. Superconvergent approximations to second and higher derivatives of prices with respect to the price process' state variables are extracted from approximate, computed prices with low, $C^0$ regularity by postprocessing. The extracted numerical sensitivities are proved to converge with optimal rates as the mesh width tends to zero. Numerical experiments for uni- and multivariate models with sparse tensor product discretization confirm the theoretical results.

Authors

  • Norbert HilberSeminar for Applied Mathematics
    ETH Zürich
    Rämistrasse 101
    8092 Zürich, Switzerland
    e-mail
  • Christoph SchwabSeminar for Applied Mathematics
    ETH Zürich
    Rämistrasse 101
    8092 Zürich, Switzerland
    e-mail
  • Christoph WinterSeminar for Applied Mathematics
    ETH Zürich
    Rämistrasse 101
    8092 Zürich, Switzerland
    e-mail

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