Estimation for drift parameters of CIR model from discrete observations

This paper investigates the estimation problem for drift parameters of a special short-term rate model called CIR model. The parameter in diffusion item is set for a constant. Euler-Maruyama scheme and iterative method are applied to get the joint conditional probability density function. The maximum likelihood estimation is employed to obtain the parameter estimators and the explicit expressions of the error of estimation for the parameters are given. The consistency properties of the parameter estimators are proved with the help of the law of large numbers for martingale. Simulation of the absolute error between estimators and true values is given to verify the effectiveness of the estimation approach used in this paper.