Time-dependent diffusion models for term structure dynamics

被引:4
作者
Fan, J [1 ]
Jiang, JC
Zhang, CM
Zhou, ZW
机构
[1] Chinese Univ Hong Kong, Dept Stat, Shatin, Hong Kong, Peoples R China
[2] Beijing Univ, Dept Stat & Probabil, Beijing 100871, Peoples R China
[3] Univ Wisconsin, Dept Stat, Madison, WI 53706 USA
[4] Univ Calif Los Angeles, Dept Stat, Los Angeles, CA 90095 USA
关键词
diffusion model; kernel regression; nonparametric goodness-of-fit;
D O I
暂无
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In an effort to capture the time variation on the instantaneous return and volatility functions, a family of time-dependent diffusion processes is introduced to model the term structure dynamics. This allows one to examine how the instantaneous return and price volatility change over time and price level. Nonparametric techniques, based on kernel regression, are used to estimate the time-varying coefficient functions in the drift and diffusion. The newly proposed semiparametric model includes most of the well-known short-term interest rate models, such as those proposed by Cox, Ingersoll and Ross (1985) and Chan, Karolyi, Longstaff and Sanders (1992). It can be used to test the goodness-of-fit of these famous time-homogeneous short rate models. The newly proposed method complements the time-homogeneous nonparametric estimation techniques of Stanton (1997) and Fan and Yao (1998), and is shown through simulations to truly capture the heteroscedasticity and time-inhomogeneous structure in volatility. A family of new statistics is introduced to test whether the time-homogeneous models adequately fit interest rates for certain periods of the economy. We illustrate the new methods by using weekly three-month treasury bill data.
引用
收藏
页码:965 / 992
页数:28
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