A Generalized Extreme Value Approach to Financial Risk Measurement

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Financial Risk Measurement and Prediction Modelling for Sustainable Development of Business Entities Using Regression Analysis (2018, background): “Except for well-known risk measures, including value at risk [6] or coherent and convex risk measures [7], there are many others methods that authors use to measure financial risks.”
Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets (2012, background): “Bali (2007) and Straetmans, Verschoor, and Wolff (2008) find that the EVT models perform better estimations in an extreme volatile market than the standard approach that assumes the normal distribution.”
Does Systemic Risk in the Financial Sector Predict Future Economic Downturns (2012, background): “Bali (2003, 2007) shows that the GPD distribution yields a closed form solution for VaR: ϑGPD = µ+ ( σ ξ )[( αN n )−ξ −1 ] , (2) where n and N are the number of extremes and the number of total data points, respectively.”
Extreme Value Theory for Finance: A Survey (2012, methodology): “For example, Bali (2007) uses daily index levels of the Dow Jones Industrial Average (DJIA) from May 26, 1896 through December 29, 2000 (more than 28 thousand observations).”