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1 Richardson Extrapolation Techniques for the Pricing of American-style Options Chuang-Chang Chang, San-Lin Chung 1 and Richard C. Stapleton 2 This Draft: March, 2002 1 Department of Finance, The Management School, National Central University, Chung-Li 320, Taiwan. Tel: 886-3-4227424, Fax: 886-3- 4252961, Email: chungs@mgt.ncu.edu.tw 2 Department of Accounting and Finance, Strathclyde University, United Kingdom. Email: rcs@staplet.demon.co.uk 1 Department of Finance, The Management School, National Central University, Chung-Li 320, Taiwan. Tel: 886-3-4227424, Fax: 886-3- 4252961, Email: chungs@mgt.ncu.edu.tw 2 Department of Accounting and Finance, Strathclyde University, United Kingdom. Email: rcs@staplet.demon.co.uk

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2 Introduction Among many analytical approximation methods, Geske and Johnson (1984) method is widely used in the literature. Geske and Johnson (1984) showed that it was possible to value an American-style option by using a series of options exercisable at one of a finite number of exercise points (known as Bermudan- style options). They employed Richardson extrapolation techniques to derive an efficient computational formula using the values of Bermudan options.

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3 Two problems in the Geske and Johnson (1984) method: the problem of non-uniform convergence it is difficult to determine the accuracy of the approximation

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4 Literature Review Geske and Johnson (1984) Geske and Johnson (1984) show that an American put option can be estimated with a high degree of accuracy using a Richardson approximation. If P(n) is the price of a Bermudan-style option exercisable at one of n equally-spaced exercise dates, then, for example, using P(1), P(2) and P(3), the price of the American put is estimated by

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5 where P(1,2,3) denotes the approximated value of the American option using the values of Bermudan options with 1, 2 and 3 possible exercise points. Omberg (1987) Omberg (1987) shows that there may be a problem of non-uniform convergence since P(2) in equation (1) is computed using exercise points at time T and T/2, where T is the time to maturity of option, and P(3) is computed using exercise points at time T/3, 2T/3, and T.

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6 Bunch and Johnson (1992) Bunch and Johnson (1992) suggest a modification of the Geske-Johnson method based on the use of an approximation: where P max (2) is the value of an option exercisable at two points at time, when the exercise points are chosen so as to maximize the option’s value.

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7 Broadie and Detemple (1996) Due to the uniform convergence property of the BBS method, Broadie and Detemple (1996) also suggest a method termed the Binomial Black and Scholes model with Richardson extrapolation (BBSR). In particular, the BBSR method with n steps computes the BBS prices corresponding to m=n/2 steps (say P m ) and n steps (say P n ) and then sets the BBSR price to P=2P n -P m.

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8 The Repeated-Richardson Extrapolation Algorithm Assume that with known exponents and, but unknown a 1, a 2, a 3, etc., where denotes a quantity whose size is proportional to, or possibly smaller. According to Schmidt (1968), we can establish the following algorithm when,.

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9 Algorithm: For i=1,2,3..., set A i,0 =F(h i ), and compute for m=1, 2, 3, …, k-1. where A i,m is an approximate value of a 0 obtained from an m times Repeated-Richardson extrapolation using step sizes of, and.

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10 The computations can be conveniently set up in the following scheme: The Geske-Johnson Formulae

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11 The Modified Geske-Johnson Formulae The Error Bounds and Predictive Intervals of American Option Values Schmidt’s Inequality Schmidt (1968) shows that it always holds that when i is sufficiently large

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12 Numerical Results

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Numerical Methods for derivatives pricing. 2 American Monte Carlo It’s difficult to price an option with early exercise using Monte Carlo But some options.

Numerical Methods for derivatives pricing. 2 American Monte Carlo It’s difficult to price an option with early exercise using Monte Carlo But some options.

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