Risk management with expectiles

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Elicitability and backtesting: Perspectives for banking regulation (2016, background): “975 under the standard normal distribution; see Bellini and Bernardino [2015]. The paper is organized as follows. Section 2 contains the theoretical discussion of backtesting risk measures. In Section 2.1 we define the notion of elicitability, introduce identifiability and review characterizations o”
Estimation of tail risk based on extreme expectiles (2016, unknown): “Bellini and Di Bernardino (2017) have already suggested to pick out τ 1 n which satisﬁes ξ τ 1 n ” q α n , but for a normally distributed Y .”
Extreme M-quantiles as risk measures: From $L^{1}$ to $L^{p}$ optimization (2019, unknown): ““ arg min uPR ψnpu; pq (4) where ψnpu; pq :“ 1 prqτnppqs n”