The article contributes to the ongoing search for a market risk measure that is both coherent
and elicitable. We compare two traditional measures, namely Value-at-Risk and the …

Heavy tails (HT) arise in many applications and their presence can disrupt statistical
inference, yet the HT statistical literature requires a theoretical background most practicing …

Expectiles induce a law-invariant risk measure that has recently gained popularity in
actuarial and financial risk management applications. Unlike quantiles or the quantile-based …

A substantial body of work in the last 15 years has shown that expectiles constitute an
excellent candidate for becoming a standard tool in probabilistic and statistical modeling …

The value at risk based on expectile (EVaR) is a very useful method to measure financial
risk, especially in measuring extreme financial risk. The double-threshold autoregressive …

Expectile regression is a useful tool in modelling data with heterogeneous conditional
distributions. This paper introduces two new concepts, ie the expectile correlation and …

Premium calculation has been a popular topic in actuarial sciences over the decades.
Generally, a two-stage model is used to develop the premium calculation process. It can be …

In this paper, we introduce an efficient surrogate loss method for large-scale expectile
regression in non-randomly distributed scenarios. Specifically, a Poisson subsampling …

Quantiles are a fundamental concept in extreme value theory. They can be obtained from a
minimization framework using an asymmetric absolute error loss criterion. The companion …

In financial risk management, Value at Risk (VaR) is widely used to estimate potential
portfolio losses. VaR's limitation is its inability to account for the magnitude of losses beyond …