Design of high performance financial modeling environment Export

@article{citeulike:3208055, abstract = {The aim of our system is to generate solution code from a high level specication of a nancial instrument. Solution code calculates prices and hedge ratios which are partial derivatives of the price with respect to various parameters. The user manipulates a representation of the problem at the domain level, with the complexities of the computer implementation hidden. As many of the problems have no analytical solution, symbolic transformations manipulate the equations specifying the stochastic model and instrument into forms that can be solved numerically. Techniques such as nite dierences, spectral methods and Monte Carlo simulation are provided in sequential and parallel versions. The mathematical correctness of the transformation steps is examinable as is the degree of error introduced by approximating transformations. We include examples for the Black-Scholes model and for the Hull White stochastic volatility model. A Linux cluster is used to price an Asian option using the Hull White SV model. Key words: derivative securities, nancial modeling, problem solving}, author = {Bunnin, F. O. and Guo, Y. and Ren, Y. and Darlington, J.}, citeulike-article-id = {3208055}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.6106}, journal = {Parallel Computing}, keywords = {finance, simulation}, pages = {200--0}, posted-at = {2008-09-09 06:55:07}, priority = {2}, title = {Design of high performance financial modeling environment}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.6106}, volume = {26}, year = {2000} }

TY - JOUR ID - citeulike:3208055 L3 - citeulike-article-id:3208055 N2 - The aim of our system is to generate solution code from a high level specication of a nancial instrument. Solution code calculates prices and hedge ratios which are partial derivatives of the price with respect to various parameters. The user manipulates a representation of the problem at the domain level, with the complexities of the computer implementation hidden. As many of the problems have no analytical solution, symbolic transformations manipulate the equations specifying the stochastic model and instrument into forms that can be solved numerically. Techniques such as nite dierences, spectral methods and Monte Carlo simulation are provided in sequential and parallel versions. The mathematical correctness of the transformation steps is examinable as is the degree of error introduced by approximating transformations. We include examples for the Black-Scholes model and for the Hull White stochastic volatility model. A Linux cluster is used to price an Asian option using the Hull White SV model. Key words: derivative securities, nancial modeling, problem solving JF - Parallel Computing EP - 0 TI - Design of high performance financial modeling environment VL - 26 SP - 200 KW - finance KW - simulation AU - Bunnin, FO AU - Guo, Y AU - Ren, Y AU - Darlington, J PY - 2000/// UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.23.6106 ER -