EFFICIENT COMPUTATION OF EXPOSURE PROFILES FOR COUNTERPARTY CREDIT RISK

Cornelis S. L. de Graaf (), Qian Feng (), Drona Kandhai () and Cornelis Oosterlee
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Cornelis S. L. de Graaf: Computational Science, University of Amsterdam, Science Park 904, Amsterdam, 1098 XH, The Netherlands
Qian Feng: CWI – The Center for Mathematics and Computer Science, Science Park 123, Amsterdam, 1098 XG, The Netherlands
Drona Kandhai: Quantitative Analytics, ING Bank, Bijlmerdreef 98, Amsterdam, 1102 CT, The Netherlands;

International Journal of Theoretical and Applied Finance (IJTAF), 2014, vol. 17, issue 04, 1-23

Abstract: Three computational techniques for approximation of counterparty exposure for financial derivatives are presented. The exposure can be used to quantify so-called Credit Valuation Adjustment (CVA) and Potential Future Exposure (PFE), which are of utmost importance for modern risk management in the financial industry, especially since the recent credit crisis. The three techniques all involve a Monte Carlo path discretization and simulation of the underlying entities. Along the generated paths, the corresponding values and distributions are computed during the entire lifetime of the option. Option values are computed by either the finite difference method for the corresponding partial differential equations, or the simulation-based Stochastic Grid Bundling Method (SGBM), or by the COS method, based on Fourier-cosine expansions. In this research, numerical results are presented for early-exercise options. The underlying asset dynamics are given by either the Black–Scholes or the Heston stochastic volatility model.

Keywords: Expected exposure; potential future exposure; Bermudan options; Heston; numerical computation; finite differences; stochastic grid bundling method (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (14)

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DOI: 10.1142/S0219024914500241

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