A robust VaR model under different time periods and weighting schemes

Timotheos Angelidis, Alexandros Benos () and Stavros Degiannakis

Review of Quantitative Finance and Accounting, 2007, vol. 28, issue 2, 187-201

Abstract: 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. Copyright Springer Science+Business Media, LLC 2007

Keywords: Asymmetric power ARCH; Backtesting; Extreme value theory; Filtered historical simulation; Value-at-risk (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11156-006-0010-y (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: A Robust VaR Model under Different Time Periods and Weighting Schemes (2007)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:rqfnac:v:28:y:2007:i:2:p:187-201

Ordering information: This journal article can be ordered from
http://www.springer.com/finance/journal/11156/PS2

DOI: 10.1007/s11156-006-0010-y

Access Statistics for this article

Review of Quantitative Finance and Accounting is currently edited by Cheng-Few Lee

More articles in Review of Quantitative Finance and Accounting from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().