Forecasting Value-at-Risk using high frequency data: The realized range model

被引：17

作者：

Shao, Xi-Dong ^{[1
]}

Lian, Yu-Jun ^{[2
]}

Yin, Lian-Qian ^{[1
]}

机构：

[1] Xi An Jiao Tong Univ, Jinhe Ctr Econ Res, Xian, Shaanxi, Peoples R China

[2] Sun Yat Sen Univ, Lingnan Coll, Dept Finance, Guangzhou 510275, Guangdong, Peoples R China

来源：

GLOBAL FINANCE JOURNAL | 2009年 / 20卷 / 02期

关键词：

VaR; Realized range; High frequency data;

D O I：

10.1016/j.gfj.2008.11.003

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

Current studies on financial market risk measures usually use daily returns based on GARCH type models. This paper models realized range using intraday high frequency data based on CARR framework and apply it to VaR forecasting. Kupiec LR test and dynamic quantile test are used to compare the performance of VaR forecasting of realized range model with another intraday realized volatility model and daily GARCH type models. Empirical results of Chinese Stock Indices show that realized range model performs the same with realized volatility model, which performs much better than daily models. (C) 2009 Elsevier Inc. All rights reserved.

引用

页码：128 / 136

页数：9

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