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http://dx.doi.org/10.5351/KJAS.2016.29.4.689

Vector at Risk and alternative Value at Risk  

Honga, C.S. (Department of Statistics, Sungkyunkwan University)
Han, S.J. (Department of Statistics, Sungkyunkwan University)
Lee, G.P. (Department of Statistics, Sungkyunkwan University)
Publication Information
The Korean Journal of Applied Statistics / v.29, no.4, 2016 , pp. 689-697 More about this Journal
Abstract
The most useful method for financial market risk management may be Value at Risk (VaR) which estimates the maximum loss amount statistically. The VaR is used as a risk measure for one industry. Many real cases estimate VaRs for many industries or nationwide industries; consequently, it is necessary to estimate the VaR for multivariate distributions when a specific portfolio is established. In this paper, the multivariate quantile vector is proposed to estimate VaR for multivariate distribution, and the Vector at Risk for multivariate space is defined based on the quantile vector. When a weight vector for a specific portfolio is given, one point among Vector at Risk could be found as the best VaR which is called as an alternative VaR. The alternative VaR proposed in this work is compared with the VaR of Morgan with bivariate and trivariate examples; in addition, some properties of the alternative VaR are also explored.
Keywords
loss; portfolio; quantile; risk; weight;
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Times Cited By KSCI : 8  (Citation Analysis)
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