Analysis of Parameter Sensitivity for the NSS Model of Term Structure Based on the Genetic Algorithm

被引：0

作者：

Zhou Rongxi ^{[1
]}

Liu Hanzhang ^{[1
]}

Zou Lin ^{[2
]}

机构：

[1] Univ Int Business & Econ, Sch Finance, Beijing 100029, Peoples R China

[2] Renmin Univ China, Sch Econ, Beijing 100872, Peoples R China

来源：

2017 29TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2017年

关键词：

Term Structure of Interest Rate; Nelson-Siegel Model; Genetic Algorithm; Sensitivity Analysis; NELSON-SIEGEL MODEL; INTEREST-RATES;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The term structure of interest rate is an important foundation for studies such as asset pricing and risk management. In this paper, the sensitivity of parameters in the NSS model of the yield curve is studied with the help of genetic algorithm, and the impact of the relevant parameter setting on the fitting precision of the model is also discussed. Based on the positive analysis of Chinese Treasury Bonds data, it is found that the parameter setting in the model has a significant effect on the fitting precision, but the effect varies due to different parameters. It also leads methodological support to precisely and conveniently employ the NSS model.

引用

页码：3262 / 3265

页数：4

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