A LOW-BIAS SIMULATION SCHEME FOR THE SABR STOCHASTIC VOLATILITY MODEL

Bin Chen (), Cornelis Oosterlee and Hans van der Weide
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Bin Chen: CWI, Center for Mathematics and Computer Science, Amsterdam, The Netherlands;
Hans van der Weide: Faculty of Electrical Engineering, Mathematics and Computer Science, TU Delft, The Netherlands

International Journal of Theoretical and Applied Finance (IJTAF), 2012, vol. 15, issue 02, 1-37

Abstract: The Stochastic Alpha Beta Rho Stochastic Volatility (SABR-SV) model is widely used in the financial industry for the pricing of fixed income instruments. In this paper we develop a low-bias simulation scheme for the SABR-SV model, which deals efficiently with (undesired) possible negative values in the asset price process, the martingale property of the discrete scheme and the discretization bias of commonly used Euler discretization schemes. The proposed algorithm is based the analytic properties of the governing distribution. Experiments with realistic model parameters show that this scheme is robust for interest rate valuation.

Keywords: Discretization scheme; SABR model; small noise expansion; Monte Carlo; square Bessel process; integrated variance (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (14)

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DOI: 10.1142/S0219024912500161

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