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Approximating Value at Risk in Conditional Gaussian Models
Year Of Publication: 2002
Month Of Publication: July
Pages: 31
Download Count: 14
View Count: 2413
Comment Num: 0
Language: English
Who Can Read: Free
Date: 5-30-2010
Publisher: Administrator
Financial institutions are facing the important task of estimating and controlling
their exposure to market risk, which is caused by changes in prices of
equities, commodities, exchange rates and interest rates. A new chapter of risk
management was opened when the Basel Committee on Banking Supervision
proposed that banks may use internal models for estimating their market risk
(Basel Committee on Banking Supervision, 1995). Its implementation into national
laws around 1998 allowed banks to not only compete in the innovation
of financial products but also in the innovation of risk management methodology.
Measurement of market risk has focused on a metric called Value at Risk
(VaR). VaR quantifies the maximal amount that may be lost in a portfolio over
a given period of time, at a certain confidence level. Statistically speaking, the
VaR of a portfolio is the quantile of the distribution of that portfolio's loss over
a speci ed time interval, at a given probability level.
Jaschke, Stefan R. Sign in to follow this author
Jiang, Yuze Sign in to follow this author
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