Estimation in the Cox-Ingersoll-Ross Model
研究了从等距时间点观测数据中估计Cox-Ingersoll-Ross模型参数的方法，包括条件最小二乘、加权条件最小二乘和极大似然估计，并比较了它们的渐近性质和模拟表现。
The Cox-Ingersoll-Ross model is a diffusion process suitable for modeling the term structure of interest rates. In this paper, we consider estimation of the parameters of this process from observations at equidistant time points. We study two estimators based on conditional least squares as well as a one-step improvement of these, two weighted conditional least-squares estimators, and the maximum likelihood estimator. Asymptotic properties of the various estimators are discussed, and we also compare their performance in a simulation study.