Bond pricing in APL2: A study in numerical solution of the Brennan and Schwartz bond pricing model using a vector processor

Foster, Garth H.

doi:10.1007/bf00436509

Cited by 5 publications

(2 citation statements)

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“…Examples can be found in Eydeland and Nagumey (1989), Foster, Foote, and Kreamer (1988), Foster (1989), Kokkelenberg (1988), and Petersen (1987). Performing optimal control experiments is one of the major fields of applications in economics.…”

Section: Introductionmentioning

confidence: 97%

Parallel Processing for Large-Scale Nonlinear Control Experiments in Economics

Amman

Kendrick

1991

The International Journal of Supercomputing Applications

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In general, the econometric models relevant for purposes of evaluating economic policy contain a large number of nonlinear equations. Therefore, in applying optimal control techniques, computational difficulties are encountered. This paper presents the most common algorithm for computing nonlinear control problems and investigates the degree to which vector processing and parallel processing can facilitate optimal control experiments.

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Section: Introductionmentioning

confidence: 97%

Parallel Processing for Large-Scale Nonlinear Control Experiments in Economics

Amman

Kendrick

1991

The International Journal of Supercomputing Applications

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“…For the case of contingent claims with two underlying state variables, the literature contains some examples of valuation by numerical methods (e.g., see Boyle (1988), Foster (1989), Hull and White (1990) or Jennergren and Ngslund (1990)). As for contingent claims with three underlying state variables, there is as far as this author has been able to ascertain only one journal article which contains examples of valuation by numerical methods.…”

Section: Introductionmentioning

confidence: 99%

Experiences in the pricing of trivariate contingent claims with finite difference methods on a massively parallel computer

Ekvall

1994

Comput Econ

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Abstract.Finite difference schemes have proved to be very flexible numerical methods for the pricing of contingent claims with one and two underlying state variables. This flexibility and the steady stream of new complex financial instruments imply that finite difference schemes for the valuation of contingent claims with three underlying state variables can supposedly be very useful. In this paper, two such schemes are developed and tested. For practical purposes, numerical valuation of contingent claims with three underlying state variables by means of finite difference methods is probably too laborious computationally to be performed on a single processor computer. Many calculations can, however, be performed in parallel. Therefore, the methods are well suited to be executed on a massively parallel computer, like the Connection Machine CM-200, which is used in this paper. The accuracy of the schemes proposed in this paper suggests that valuation of multivariate contingent claims with the help of finite difference methods on a massively parallel computer can be a useful approach for academics as well as practitioners.

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Chapter 13 Numerical methods for linear-quadratic models

Amman

1996

Handbook of Computational Economics

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Bond pricing in APL2: A study in numerical solution of the Brennan and Schwartz bond pricing model using a vector processor

Cited by 5 publications

References 5 publications

Parallel Processing for Large-Scale Nonlinear Control Experiments in Economics

Parallel Processing for Large-Scale Nonlinear Control Experiments in Economics

Experiences in the pricing of trivariate contingent claims with finite difference methods on a massively parallel computer

Chapter 13 Numerical methods for linear-quadratic models

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