Parameter Estimation for Constantinides-Ingersoll Model from Discrete Observations  

作　　者：魏超 舒慧生 

机构地区：[1]School of lnformation Science and rechnotogy,Donghua University,Shanghai 201620,China [2]School of Science,Donghua University,Shanghai 201620,China

出　　处：《Journal of Donghua University(English Edition)》2016年第2期183-187,共5页东华大学学报（英文版）

基　　金：National Nature Science Foundation of China(No.60974030);the Chinese Universities Scientific Fund(No.CUSF-DH-D-2014059)

摘　　要：The parameter estimation problem for an economic model called Constantinides-Ingersoll model is investigated based on discrete observations. Euler-Maruyama scheme and iterative method are applied to getting the joint conditional probability density function. The maximum likelihood technique is employed for obtaining the parameter estimators and the explicit expressions of the estimation error are given. The strong consistency properties of the estimators are proved by using the law of large numbers for martingales and the strong law of large numbers. The asymptotic normality of the estimation error for the diffusion parameter is obtained with the help of the strong law of large numbers and central-limit theorem. The simulation for the absolute error between estimators and true values is given and the hypothesis testing is made to verify the effectiveness of the estimators.The parameter estimation problem for an economic model called Constantinides-Ingersoll model is investigated based on discrete observations. Euler-Maruyama scheme and iterative method are applied to getting the joint conditional probability density function. The maximum likelihood technique is employed for obtaining the parameter estimators and the explicit expressions of the estimation error are given. The strong consistency properties of the estimators are proved by using the law of large numbers for martingales and the strong law of large numbers. The asymptotic normality of the estimation error for the diffusion parameter is obtained with the help of the strong law of large numbers and central-limit theorem. The simulation for the absolute error between estimators and true values is given and the hypothesis testing is made to verify the effectiveness of the estimators.

关 键 词：diffusion process maximum likelihood estimation(MLE) discrete observation CONSISTENCY asymptotic normality hypothesis testing 

分 类 号：O211.6[理学—概率论与数理统计] O211.9[理学—数学]