Adjoint-based Monte Carlo calibration of financial market models |
| |
Authors: | C Kaebe J H Maruhn E W Sachs |
| |
Institution: | (1) FB 4—Department of Mathematics, University of Trier, 54286 Trier, Germany;(2) UniCredit Markets & Investment Banking, Financial Engineering Equities, Commodities and Funds, Bayerische Hypo- und Vereinsbank, 81925 Munich, Germany;(3) Department of Mathematics, Virginia Tech, Blacksburg, VA 24060, USA |
| |
Abstract: | Adjoint methods have recently gained considerable importance in the finance sector, because they allow to quickly compute
option sensitivities with respect to a large number of model parameters. In this paper we investigate how the efficiency of
adjoint methods can be exploited to speed up the Monte Carlo-based calibration of financial market models. After analyzing
the calibration problem both theoretically and numerically, we derive the associated adjoint equation and propose its application
in combination with a multi-layer method, for which we prove convergence to a stationary point of the underlying optimization
problem. Detailed numerical examples illustrate the performance of the method. In particular, the proposed algorithm reduces
the calibration time for a typical equity market model with time-dependent model parameters from over three hours to less
than ten minutes on a usual desktop PC.
|
| |
Keywords: | Adjoint equation Monte Carlo calibration Multi-layer method |
本文献已被 SpringerLink 等数据库收录! |
|