A Robust VaR Model under Different Time Periods and Weighting Schemes

Timotheos Angelidis, Alexandros Benos and Stavros Degiannakis

MPRA Paper from University Library of Munich, Germany

Abstract: This paper analyses several volatility models by examining their ability to forecast the 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.

Keywords: Asymmetric Power ARCH; Backtesting; Extreme Value Theory; Filtered Historical Simulation; Value-at-Risk. (search for similar items in EconPapers)
JEL-codes: C22 C52 C53 G15 (search for similar items in EconPapers)
Date: 2007
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Citations: View citations in EconPapers (29)

Published in Review of Quantitative Finance and Accounting 28.2(2007): pp. 187-201

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Journal Article: A robust VaR model under different time periods and weighting schemes (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:80466

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