Computing MVA via Regression and Principal Component Analysis

19 Pages Posted: 18 Jul 2017 Last revised: 18 Dec 2017

Date Written: December 17, 2017

Abstract

MVA is today’s price of the future costs generated by future initial margin postings. Computing MVA requires long-term risk neutral simulations of future initial margin amounts. The ISDA SIMM computes initial margin based on the portfolio’s sensitivity with respect to a high-dimensional vector of risk factors. In this note, we describe a way to approximate future SIMM based initial margin amounts in terms of regression functions with respect to a small number of explanatory variables. Our method uses principal components analysis, and it fits in naturally with American Monte Carlo techniques.

Keywords: MVA, initial margin, ISDA SIMM, AMC

Suggested Citation

Kappen, Christian, Computing MVA via Regression and Principal Component Analysis (December 17, 2017). Available at SSRN: https://ssrn.com/abstract=3001424 or http://dx.doi.org/10.2139/ssrn.3001424

Christian Kappen (Contact Author)

d-fine GmbH ( email )

An der Hauptwache 7
Frankfurt, 60313
Germany

HOME PAGE: http://www.d-fine.de

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