Estimating and forecasting portfolio's Value-at-Risk with wavelet-based extreme value theory: Evidence from crude oil prices and US exchange rates

被引：12
|
作者：
Jammazi, Rania [1 ]
Duc Khuong Nguyen [2 ]
机构：
[1] Univ Sousse, Int Finance Grp Tunisia, BP 307, Cite Erriadh 4023, Sousse, Tunisia
[2] IPAG Business Sch, 184 Blvd St Germain, F-75006 Paris, France
来源：
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY | 2017年 / 68卷 / 11期
关键词：
stochastic processes; wavelet analysis; extreme value theory; VaR; oil-exchange rate portfolios; MARKET; TIME;
D O I：
10.1057/s41274-016-0133-z
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
This article proposes a wavelet-based extreme value theory (W-EVT) approach to estimate and forecast portfolio's Value-at-Risk (VaR) given the stylized facts and complex structure of financial data. Our empirical application to portfolios of crude oil prices and US dollar exchange rates shows that the W-EVT models provide an effective and powerful tool for gauging extreme moments and improving the accuracy of portfolio's VaR estimates and forecasts after noise is removed from the original data.
引用
收藏
页码：1352 / 1362
页数：11
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