A robust VaR model under different time periods and weighting schemes

被引：27
作者：
Angelidis T. [1 ]
Benos A. [2 ]
Degiannakis S. [3 ]
机构：
[1] Department of Financial and Management Engineering, Aegean University, 82100 Chios, 31, Fostini Street
[2] Group Risk Management, National Bank of Greece, Athens
[3] Department of Statistics, Athens University of Economics and Business, 10434 Athens, 76, Patission Street
来源：
Review of Quantitative Finance and Accounting | 2007年 / 28卷 / 2期
关键词：
Asymmetric power ARCH; Backtesting; Extreme value theory; Filtered historical simulation; Value-at-risk;
D O I：
10.1007/s11156-006-0010-y
中图分类号：
学科分类号：
摘要：
This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable. © Springer Science+Business Media, LLC 2007.
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页码：187 / 201
页数：14
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