Using Particle Swarm Optimization Algorithm to Calibrate the Term Structure Model

Author:

Zhou Yanli1ORCID,Liu Shican2,Tian Tianhai3ORCID,He Qi4ORCID,Ge Xiangyu5ORCID

Affiliation:

1. School of Finance, Zhongnan University of Economics and Law, Wuhan 430073, China

2. School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan 430073, China

3. School of Mathematical Sciences, Monash University, Melbourne, VIC 3800, Australia

4. Brandeis International Business School, Brandeis University, Waltham,MA 02453, USA

5. Department of Finance, Wuhan Technology and Business University, Wuhan 430065, China

Abstract

One of the advantages of stochastic differential equations (SDE) is that they can follow a variety of different trends so that they can establish complex dynamic systems in the economic and financial fields. Although some estimation methods have been proposed to identify the unknown parameters in virtue of the results in the SDE model to speed up the process, these solutions only focus on using explicit approach to solve SDEs, and therefore they are not reliable to deal with data source merged being large and varied. Thus, this study makes progress in creating a new implicit way to fill in the gaps of accurately calibrating the unknown parameters in the SDE model. Essentially, the primary goal of the article is to generate rigid SDE simulation. Meanwhile, the particle swarm optimization method serves a purpose to search and simultaneously obtain the optimal estimation of the model unknown parameters in the complicated experiment of parameter space in an effective way. Finally, in an interest rate term structure model, it is verified that the method effectively deals with parameter estimation in the SDE model.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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