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Asymptotic Optimality of Estimating Function Estimator for CHARN Model

机译:CHARN模型的估计函数估计器的渐近最优性

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摘要

CHARN model is a famous and important model in the finance, which includes many financial time series models and can be assumed as the return processes of assets. One of the most fundamental estimators for financial time series models is the conditional least squares (CL) estimator. However, recently, it was shown that the optimal estimating function estimator (G estimator) is better than CL estimator for some time series models in the sense of efficiency. In this paper, we examine efficiencies of CL and G estimators for CHARN model and derive the condition that G estimator is asymptotically optimal.
机译:CHARN模型是金融领域一个著名且重要的模型,它包括许多金融时间序列模型,可以假定为资产的收益过程。金融时间序列模型的最基本估计器之一是条件最小二乘(CL)估计器。但是,最近发现,在效率方面,对于某些时间序列模型,最佳估计函数估计器(G估计器)优于CL估计器。在本文中,我们检查了CHARN模型的CL和G估计量的效率,并得出G估计量渐近最优的条件。

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