Extreme M-quantiles as risk measures: from L1 to Lp optimization

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Extreme M-quantiles as risk measures: from L1 to Lp optimization

The class of quantiles lies at the heart of extreme-value theory and is one of the basic tools in risk management. The alternative family of expectiles is based on squared rather than absolute error loss minimization. It has recently been receiving a lot of attention in actuarial science, econometri...

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Bibliographic Details
Main Authors:	Daouia, Abdelaati, Girard, Stéphane, Stupfler, Gilles
Format:	Article
Published:	Bernoulli Society for Mathematical Statistics and Probability 2019
Subjects:	Asymptotic normality; Dependent observations; Expectiles; Extrapolation; Extreme values; Heavy tails; Lp optimization; Mixing; Quantiles; Tail risk
Online Access:	https://eprints.nottingham.ac.uk/45682/

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