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The document discusses coherent risk measures, which are weighted averages of quantiles based on individual risk aversion, with expected shortfall (ES) being a special case. It emphasizes the importance of estimating standard errors for risk measures to ensure precision and practical value, illustrating this with an example of constructing confidence intervals for value at risk (VaR). Additionally, it introduces quantile-quantile (QQ) plots as a method to visually assess how empirical data fits a theoretica

Author

Jinwin Josey

Language

EN