QUASI-INDIRECT INFERENCE FOR DIFFUSION PROCESSES
针对连续时间模型基于固定时间间隔离散采样数据，提出一种准间接推断估计方法，通过模拟离散化模型进行估计，并研究其渐近性质和有限样本表现。
We discuss an estimation procedure for continuous-time models based on discrete sampled data with a fixed unit of time between two consecutive observations. Because in general the conditional likelihood of the model cannot be derived, an indirect inference procedure following Gouriéroux, Monfort, and Renault (1993, Journal of Applied Econometrics 8, 85–118) is developed. It is based on simulations of a discretized model. We study the asymptotic properties of this “quasi”-indirect estimator and examine some particular cases. Because this method critically depends on simulations, we pay particular attention to the appropriate choice of the simulation step. Finally, finite-sample properties are studied through Monte Carlo experiments.