Research on the Construction of Financial Computing Model Based on BSDE Algorithm

Abstract

Economic and social development has made financial engineering an increasingly important research area, and more and more financial problems cannot be solved directly by analytical formulas. In view of this, algorithms that apply computer technology to financial engineering have emerged. In this study, the Backward Stochastic Differential Equation (BSDE) algorithm is used to investigate and analyse the problem of option pricing calculation in finance. In the research process, GBSDE-Theta parallel algorithm composed of BSDE-Theta algorithm and GPU algorithm uses the new algorithm to establish a computing model in the financial engineering field, which applies to the calculation of enterprise option pricing. The research results show that compared with the basic algorithm, the actual option values of the option pricing data obtained by using the GBSDE-Theta parallel algorithm are more closely matched. The computational model can achieve a speedup ratio of about 230 times of the serial version with the number of time steps [Formula: see text] and the number of simulated paths 80,000. About the relative error of the GBSDE-Theta algorithm, there are 80 points within 3% and only 16 points over 3.00%, which is a relatively small error. The above results show that the financial computing system obtained in this study is highly feasible and effective, and can provide a new research idea for the progress and development of other computations in the financial field.