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Operator splitting methods for pricing American options under stochastic volatility, (2009)

by S Ikonen, J Toivanen
Venue:Numer. Math.
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Componentwise splitting methods for pricing American options under stochastic volatility

by Jari Toivanen - Int. J. Theor. Appl. Finance , 2007
"... Abstract A linear complementarity problem (LCP) is formulated for the price of American options under the Bates model which combines the Heston stochastic volatility model and the Merton jump-diffusion model. A finite difference discretization is described for the partial derivatives and a simple qu ..."
Abstract - Cited by 12 (1 self) - Add to MetaCart
Abstract A linear complementarity problem (LCP) is formulated for the price of American options under the Bates model which combines the Heston stochastic volatility model and the Merton jump-diffusion model. A finite difference discretization is described for the partial derivatives and a simple quadrature is used for the integral term due to jumps. A componentwise splitting method is generalized for the Bates model. It is leads to solution of sequence of one-dimensional LCPs which can be solved very efficiently using the Brennan and Schwartz algorithm. The numerical experiments demonstrate the componentwise splitting method to be essentially as accurate as the PSOR method, but order of magnitude faster. Furthermore, pricing under the Bates model is less than twice more expensive computationally than under the Heston model in the experiments. 1
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...n fluid dynamics; see [14] and references therein. The ADI and operator splitting methods have been applied also to the option pricing and, for example, the books [6], [10], and [34] discuss this. In =-=[18]-=- an operator splitting method for pricing American options under stochastic volatility is proposed. It decouples the convection diffusion operator and the early exercise constraint to separate fractio...

Pricing American Options Using a Space-time Adaptive Finite Difference Method

by Jonas Persson
"... American options are priced numerically using a space- and timeadaptive finite difference method. The generalized Black-Scholes operator is discretized on a Cartesian structured but non-equidistant grid in space. The space- and time-discretizations are adjusted such that a predefined tolerance level ..."
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American options are priced numerically using a space- and timeadaptive finite difference method. The generalized Black-Scholes operator is discretized on a Cartesian structured but non-equidistant grid in space. The space- and time-discretizations are adjusted such that a predefined tolerance level on the local discretization error is met. An operator splitting technique is used to separately handle the early exercise constraint and the solution of linear systems of equations from the finite difference discretization of the linear complementarity problem. In numerical experiments three variants of the adaptive time-stepping algorithm with and without local time-stepping are compared.
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...plitting technique to solve the LCP. This technique has been used in other numerical fields and was implemented for financial problems by Ikonen and Toivanen in several articles and reports (see e.g. =-=[12, 13]-=-). This method is built upon a finite difference discretization (though it could be used also for other discretizations) and separates the solution of the linear systems of equations from the enforcin...

An iterative method for pricing American options under jump-diffusion models,

by Santtu Salmi , Jari Toivanen , Lina Von Sydow - Appl. Numer. Math. , 2011
"... Abstract We consider the numerical pricing of American options under the Bates model which adds log-normally distributed jumps for the asset value to the Heston stochastic volatility model. A linear complementarity problem (LCP) is formulated where partial derivatives are discretized using finite d ..."
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Abstract We consider the numerical pricing of American options under the Bates model which adds log-normally distributed jumps for the asset value to the Heston stochastic volatility model. A linear complementarity problem (LCP) is formulated where partial derivatives are discretized using finite differences and the integral resulting from the jumps is evaluated using simple quadrature. A rapidly converging fixed point iteration is described for the LCP, where each iterate requires the solution of an LCP. These are easily solved using a projected algebraic multigrid (PAMG) method. The numerical experiments demonstrate the efficiency of the proposed approach. Furthermore, they show that the PAMG method leads to better scalability than the projected SOR (PSOR) method when the discretization is refined.
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...6]. With a well designed multigrid method, the number of iterations does not grow with refined discretizations. For extensive literature on this see, the book [32], for example. For solving LCPs Brandt and Cryer introduced a projected full approximation scheme (PFAS) multigrid method in [33]. Another multigrid method for similar problems was described in [34]. The PFAS method was used to price American options under stochastic volatility by Clarke and Parrott in [9], and Oosterlee in [13]. Some alternative approaches employing multigrid methods for option pricing have been considered in [35], [36], [37]. Reisinger and Wittum described a projected multigrid (PMG) method for LCPs which resembles more closely a classical multigrid method for linear problems in [38]. This method has been used to price American options in [38], [11]. The above mentioned methods are so-called geometrical multigrid methods which means that the spatial operators are discretized on sequence of grids. Furthermore, transfer operators between grids need to be implemented. S. Salmi, J. Toivanen, L. von Sydow / Procedia Computer Science 00 (2013) 000–000 The geometrical multigrid method can be implemented with some ...

On the use of policy iteration as an easy way of pricing American options

by C. Reisinger, J. H. Witte - SIAM Journal on Financial Mathematics
"... Abstract. In this paper, we demonstrate that policy iteration, introduced in the context of HJB equations in [10], is an extremely simple generic algorithm for solving linear complementarity problems resulting from the finite differ-ence and finite element approximation of American options. We show ..."
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Abstract. In this paper, we demonstrate that policy iteration, introduced in the context of HJB equations in [10], is an extremely simple generic algorithm for solving linear complementarity problems resulting from the finite differ-ence and finite element approximation of American options. We show that, in general, O(N) is an upper and lower bound on the number of iterations needed to solve a discrete LCP of size N. If embedded in a class of standard discretisations with M time steps, the overall complexity of American option pricing is indeed only O(N(M +N)), and, therefore, for M ∼ N, identical to the pricing of European options, which is O(MN). We also discuss the numer-ical properties and robustness with respect to model parameters in relation to penalty and projected relaxation methods.
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... a more sophisticated splitting of the operators, which approximate the continuous LCP by a sequence of simpler problems in every time step, rather than solving the discretised LCP directly, e.g. see =-=[18, 19]-=- and references therein; these methods are typically efficient if the underlying splitting for the European counterpart is accurate. However, with these approaches, there is no sense of solving a disc...

Mesh Free Methods for Differential Models in Financial Mathematics

by Abdelmgid Osman, Mohammed Sidahmed, Supervisor Prof, Kailash C. Patidar, A. O. M. Sidahmed , 2011
"... ..."
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...13, 15, 16, 21, 27, 30, 39, 52, 55, 57, 65, 72, 75, 79, 81, 88, 87, 104, 111, 114, 115, 116], exotic options[11, 14, 22, 33, 36, 41, 43, 50, 82, 86, 93, 94, 95, 102, 105, 118] and multi-asset options =-=[20, 40, 45, 62, 83, 88, 103, 117]-=-. Some of the books that are dealing with various issues (including options) in finanCHAPTER 1. GENERAL INTRODUCTION 35 cial mathematics are [8, 25, 60, 96]. It should be noted that there are many oth...

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by Jonas Persson , 2006
"... ���������������������� � ����������������������������������������������������� � Think different, think finite differences. From Sloganizer.netList of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I J. Persson and L. von Sydow (2003). ..."
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���������������������� � ����������������������������������������������������� � Think different, think finite differences. From Sloganizer.netList of Papers This thesis is based on the following papers, which are referred to in the text by their Roman numerals. I J. Persson and L. von Sydow (2003). Pricing European Multiasset
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....5 Operator splitting The operator splitting technique for solving the LCP problem will here be explained in short. The technique was introduced in a series of papers by Ikonen and Toivanen, see e.g. =-=[25, 26]-=-. Let us assume that we have the LCP problem formulated as in (3.7). The operator splitting is then based on a reformulation of the problem using an auxiliary variable λ = λ(x, t). ( ) ∂ − L F (x, t) ...

Numerical Solution of Discretised HJB Equations with Applications in Finance

by Jan Hendrik Witte
"... tesis no hubiese sido posible. Muchísimas gracias, amigo. Simplicity is the keynote of all true elegance. ..."
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tesis no hubiese sido posible. Muchísimas gracias, amigo. Simplicity is the keynote of all true elegance.
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...sive over-relaxation method (PSOR) – introduced in [20] – the most widely used approach in practice for finite difference matrices (cf. [23, 60, 67]), in spite of its relatively slow convergence (cf. =-=[38]-=-); see also Section 1.2.3, where an outline of PSOR has been given. We aim to demonstrate that the method of policy iteration, developed in [28] for the numerical solution of HJB equations, yields a p...

Original cover figures c○

by Pekka Neittaanmäki, Jacques Periaux, Leila Puska, Peter Råback, Rolf Stenberg, A J. Hämäläinen, A E. Parkinson, H. Garcin, B K. Morgan, B M. Lyly, B H. Kawarada, H. Suito, Picaset Oy
"... CSC – Scientific Computing Ltd. is a non-profit organization for high-performance computing and networking in Finland. CSC is owned by the Ministry of Education. CSC provides crossdisciplinary expertise, computational resources and fast network connections for computational science and engineering. ..."
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CSC – Scientific Computing Ltd. is a non-profit organization for high-performance computing and networking in Finland. CSC is owned by the Ministry of Education. CSC provides crossdisciplinary expertise, computational resources and fast network connections for computational science and engineering. c ○ Authors and

AMERICAN OPTION PRICING UNDER STOCHASTIC VOLATILITY: A SIMULATION-BASED APPROACH

by S. G. Henderson, B. Biller, M. -h. Hsieh, J. Shortle, J. D. Tew, R. R. Barton, Arunachalam Chockalingam, Kumar Muthuraman
"... We consider the problem of pricing American options when the volatility of the underlying asset price is stochastic. No specific stochastic volatility model is assumed for the stochastic process. We propose a simulation-based approach to pricing such options. Iteratively, the method determines the o ..."
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We consider the problem of pricing American options when the volatility of the underlying asset price is stochastic. No specific stochastic volatility model is assumed for the stochastic process. We propose a simulation-based approach to pricing such options. Iteratively, the method determines the optimal exercise boundary and the associated price function for a general stochastic volatility model. Given an initial guess of the optimal exercise boundary, the Retrospective Approximation (RA) technique is used to calculate the associated value function. Using this function, the exercise boundary is improved and the process repeated till convergence. This method is a simulation based variant of the exercise-policy improvement scheme developed in Chockalingam and Muthuraman (2007). An illustration of the method is provided when using the Heston (1993) model to represent the dynamics of the volatility, together with comparisons against existing methods to validate our numerical results. 1

Alexander Lipton

by Andrey Gal, Bank America, Merrill Lynch, Andris Lasis, Bank America, Merrill Lynch , 2013
"... Pricing of vanilla and first generation exotic options in the local stochastic volatility framework: survey and new results ..."
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Pricing of vanilla and first generation exotic options in the local stochastic volatility framework: survey and new results
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