Evaluating and improving GARCH-based volatility forecasts with range-based estimators

被引：12

作者：

Hung, Jui-Cheng ^{[1
]}

Lou, Tien-Wei ^{[1
]}

Wang, Yi-Hsien ^{[1
]}

Lee, Jun-De ^{[2
]}

机构：

[1] Chinese Culture Univ, Dept Banking & Finance, Taipei 11114, Taiwan

[2] Ming Hsin Univ Sci & Technol, Dept Int Business, Hsinchu, Taiwan

来源：

APPLIED ECONOMICS | 2013年 / 45卷 / 28期

关键词：

range-based estimators; GARCH-based volatility forecasts; SPA test; C52; C53; MODELS; PERFORMANCE; VARIANCE; INDEX;

D O I：

10.1080/00036846.2012.748179

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This article investigates the feasibility of using range-based estimators to evaluate and improve Generalized Autoregressive Conditional Heteroscedasticity (GARCH)-based volatility forecasts due to their computational simplicity and readily availability. The empirical results show that daily range-based estimators are sound alternatives for true volatility proxies when using Superior Predictive Ability (SPA) test of Hansen (2005) to assess GARCH-based volatility forecasts. In addition, the inclusion of the range-based estimator of Garman and Klass (1980) can significantly improve the forecasting performance of GARCH-t model.

引用

页码：4041 / 4049

页数：9

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