Chapter 7 Variational Methods in Derivatives Pricing

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Chapter 7
Variational Methods in Derivatives Pricing
Liming Feng
Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign, 117 Transportation Building MC-238, 104 South Mathews Avenue, Urbana, IL 61801, USA E-mail: fenglm@
Abstract When underlying financial variables follow a Markov jump-diffusion process, the value function of a derivative security satisfies a partial integro-differential equation (PIDE) for European-style exercise or a partial integro-differential variational inequality (PIDVI) for American-style exercise. Unless the Markov process has a special structure, analytical solutions are generally not available, and it is necessary to solve the PIDE or the PIDVI numerically. In this chapter we briefly survey a computational method for the valuation of options in jump-diffusion models based on: (1) converting the PIDE or PIDVI to a variational (weak) form; (2) discretizing the weak formulation spatially by the Galerkin finite element method to obtain a system of ODEs; and (3) integrating the resulting system of ODEs in time. To introduce the method, we start with the basic examples of European, barrier, and American
Michael Marcozzi
Department of Mathematical Sciences, University of Nevada Las Vegas, 4505 Maryland Parkway, Box 454020, Las Vegas, NV 89154-4020, USA E-mail: marcozzi@
J.R. Birge and V. Linetsky (Eds.), Handbooks in OR & MS, Vol. 15 Copyright © 2008 Elsevier B.V. All rights reserved DOI: 10.1016/S0927-0507(07)15007-6
This research was supported by the National Science Foundation under grants DMI-0422937 and DMI-0422985.
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L. Feng et al.
options in the Black–Scholes–Merton model, then describe the method in the general setting of multi-dimensional jump-diffusion processes, and conclude with a range of examples, including Merton’s and Kou’s one-dimensional jump-diffusion models, Duffie–Pan–Singleton two-dimensional model with stochastic volatility and jumps in the asset price and its volatility, and multi-asset American options.
Department of Industrial Engineering and Management Sciences, McCormick School of Engineering and Applied Sciences, Northwestern University, 2145 Sheridan Road, Evanston, IL 60208, USA E-mail: linetsky@ url: /~linetsky
Pavlo Kovalov
Quantitative Risk Management, Inc., 181 West Madison Street, 41st Floor, Chicago, Illinois 60602, USA E-mail: pavlo.kovalov@
Vadim Linetsky
1 Introduction When underlying financial variables follow a Markov jump-diffusion process, the value function of a derivative security satisfies a partial integro-differential equation (PIDE) for European-style exercise or a partial integro-differential variational inequality (PIDVI) for American-style exercise. Unless the Markov process has a special structure (as discussed in the previous chapter), analytical solutions are generally not available, and it is necessary to solve the PIDE or the PIDVI numerically. Numerical solution of initial and boundary value problems for partial differential equations (PDE) of diffusion-convection-reaction type (the type arising in Markov process models when the underlying state variable follows a diffusion process with drift and killing or discounting) on bounded domains is standard in two and three spatial dimensions. Such PDE problems arise in a wide variety of applications in physics, chemistry, and various branches of engineering. A variety of standard (both free and commercial) software implementations are available for this purpose. However, PDE problems that arise in finance in the context of derivatives pricing in Markov process models have a number of complications: (1) diffusion models often have more than three state variables, resulting in multidimensional PDE formulations; (2) Markov process often has a jump component in addition to the diffusion component, resulting in a nonlocal integral term in the evolution equation (making it into a partial integro-differential equation (PIDE)); (3) the state space is often an unbounded domain in Rn , resulting in PDE and PIDE problems on unbounded domains, which need to be localized to bounded domains in order to be solved numerically; (4) Americanstyle early exercise is often permitted (early exercise in American options, conversion and call features in convertible bonds, etc.), leading to free-boundary problems that can be formulated as partial differential (or integro-differential if jumps are present) variational inequalities (PDVI or PIDVI); (5) payoffs are often nonsmooth (e.g., call and put option payoffs have a kink, digital option payoffs have discontinuities), creating additional challenges for numerical solution methods. In this chapter we briefly survey a general computational method for the valuation of derivative securities in jump-diffusion models. The method is based on: (1) converting the PIDE or PIDVI to a variational (weak) form; (2) discretizing the weak formulation spatially by the Galerkin finite element