Empirical likelihood intervals for conditional Value-at-Risk in ARCH/GARCH models

被引：4

作者：

Gong, Yun

Li, Zhouping ^{[2
]}

Peng, Liang ^{[1
]}

机构：

[1] Georgia Inst Technol, Sch Math, Atlanta, GA 30332 USA

[2] Lanzhou Univ, Lanzhou 730000, Peoples R China

来源：

JOURNAL OF TIME SERIES ANALYSIS | 2010年 / 31卷 / 02期

关键词：

ARCH; GARCH model; empirical likelihood; Value-at-Risk; SQUARED RESIDUAL CORRELATIONS; GARCH MODELS; CONFIDENCE-INTERVALS; ARCH; ERRORS;

D O I：

10.1111/j.1467-9892.2009.00644.x

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Value-at-Risk (VaR) is a simple, but useful measure in risk management. When some volatility model is employed, conditional VaR is of importance. As autoregressive conditional heteroscedastic (ARCH) and generalized ARCH (GARCH) models are widely used in modelling volatilities, in this article, we propose empirical likelihood methods to obtain an interval estimation for the conditional VaR with the volatility model being an ARCH/GARCH model.

引用

页码：65 / 75

页数：11

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