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### 非线性GARCH族的模型平均估计方法

• 出版日期:2018-05-25 发布日期:2018-05-25

### Model Averaging Estimation Method for Nonlinear GARCH Family

Yao Qingsong et al.

• Online:2018-05-25 Published:2018-05-25

Abstract: This paper uses the model averaging estimation for nonlinear GARCH family. As the optional model set contains nonlinear GARCH families with different functional forms, this paper constructs model averaging estimators with the nonlinear GARCH family, and presents a criterion for choosing the corresponding weights. Under certain canonical conditions, this paper proves the optimality of the above-mentioned model averaging estimators, i.e., asymptotically achieving the minimum of KL divergence. Monte Carlo simulation results indicate that under most of the situations, the model averaging estimators achieves smaller KL divergence in comparison with the existing model selection and averaging methods. In an empirical study with this method, based on the estimation done on the daily volatility of Shanghai Composite Index from June 1st 2016 to June 1st 2017, the model averaging estimators proposed in this paper have produced much accurate results than those from the other available model averaging estimation methods.