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A General Computation Scheme for a High-Order Asymptotic Expansion Method (Revised in July 2011; Revised as CARF-F-272)

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Abstract

This paper presents a new computational scheme for an asymptotic expansion method of an arbitrary order.The asymptotic expansion method in finance initiated by Kunitomo and Takahashi [9], Yoshida [34] and Takahashi [20], [21] is a widely applicable methodology for an analytic approximation of expectation of a certain functional of diffusion processes. Hence, not only academic researchers but also many practitioners have used the methodology for a variety of financial issues such as pricing or hedging complex derivatives under high-dimensional underlying stochastic environments. In practical applications of the expansion, a crucial step is calculation of conditional expectations for a certain kind of Wiener functionals. [20], [21] and Takahashi and Takehara [23] provided explicit formulas for those conditional expectations necessary for the asymptotic expansion up to the third order.This paper presents the new method for computing an arbitrary-order expansion in a general diffusion-type stochastic environment, which is powerful especially for high-order expansions: We develops a new calculation algorithm for computing coefficients of the expansion through solving a system of ordinary differential equations that is equivalent to computing the conditional expectations directly. To demonstrate its effectiveness, the paper gives numerical examples of the approximation for a Lambda-SABR model up to the fifth order and a cross-currency Libor market model with a general stochastic volatility model of the spot foreign exchange rate up to the fourth order.
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