利率期限结构模型估计结果影响因素经验研究  

An Empirical Study on Factors Affecting Estimation Results of Term Structure of Interest Rate Model

作　　者：戴国强[1] 李良松[2] 

机构地区：[1]上海财经大学MBA院,上海200433 [2]中国人民银行上海总部,上海200120

出　　处：《中国管理科学》2010年第1期9-17,共9页Chinese Journal of Management Science

基　　金：教育部人文社会科学研究2006年度规划项目(06JA790070);上海财经大学研究生科研创新基金项目(CXJJ2008331)

摘　　要：本文首先将利率期限结构模型分成了四类,并总结了国内外利率期限结构模型的估计方法。作者利用中美利率数据证明了利率市场的有效性,估计方法和数值优化算法都会对模型估计结果产生影响。实证结果表明,利用所有市场利率数据的新估计方法得到的参数会更加准确,可以消除利率市场的套利机会;遗传算法的估计结果不太稳定,单纯形法估计结果对初始值比较敏感,而矩形分割法的估计结果最为稳健。The paper classif the term structure of interest rate models into four categories and summarizes the estimation methods for interest rate models. The paper uses interest rate data of China and USA to demonstrate that the weak efficiency of interest rate market, and that estimation methods and numerical optimization methods affect the estimation results. Empirical results indicate that the new estimation method, which takes advantage of all information in all market interest rates data, can get the more accurate parameters and eliminate arbitrage in interest rate market. It also indicates that genetic method is not very stable; nelder-mead method is sensitive to initial value of these parameters and, divided rectangles method can get the most robust estimation results.

关 键 词：利率期限结构 鞅差分 遗传算法 矩形分割法 广义距估计 

分 类 号：F830.9[经济管理—金融学]