Enterprise Risk Management Slides

Market Risk [10]

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Bullet points include: Estimate appropriate parametric loss distribution and set VaR equal to (1-alpha)-quantile. E.g. multi-variate normal (i.e. Gaussian) benchmark case. Time series of, say, daily returns (/losses) on the portfolio, might assume i.i.d. normal. VaR then estimated as follows (where N-1(x) is inverse normal distribution):

Bullet points include: Estimate appropriate parametric loss distribution and set VaR equal to (1-alpha)-quantile. E.g. multi-variate normal (i.e. Gaussian) benchmark case. Time series of, say, daily returns (/losses) on the portfolio, might assume i.i.d. normal. VaR then estimated as follows (where N-1(x) is inverse normal distribution):

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