592 citations · 615 across the 23 of their papers we have counts for
16 papers · 1 filter
Accurate Bayesian inference for tail risk extrapolation in time series
David L. Carl, Simone A. Padoan, Stefano Rizzelli
Accurately quantifying tail risks-rare but high-impact events such as financial crashes or extreme weather-is a central challenge in risk management, with serially dependent data.…
Modeling extremal dependence in multivariate and spatial problems: a practical perspective
Boris Beranger, Simone A. Padoan
From environmental sciences to finance, there is a growing demand for methods that can assess the risks of extreme events beyond those observed in available data. Extrapolating ext…
Empirical Bayes inference for the block maxima method
Simone A Padoan, Stefano Rizzelli
The block maxima method is one of the most popular approaches for extreme value analysis with independent and identically distributed observations in the domain of attraction of an…
Joint inference on extreme expectiles for multivariate heavy-tailed distributions
Simone A. Padoan, Gilles Stupfler
The notion of expectiles, originally introduced in the context of testing for homoscedasticity and conditional symmetry of the error distribution in linear regression, induces a la…
Tail risk inference via expectiles in heavy-tailed time series
Anthony C. Davison, Simone A. Padoan, Gilles Stupfler
Expectiles define the only law-invariant, coherent and elicitable risk measure apart from the expectation. The popularity of expectile-based risk measures is steadily growing and t…
Estimation and uncertainty quantification for extreme quantile regions
Boris Beranger, Simone A. Padoan, Scott A. Sisson
Estimation of extreme quantile regions, spaces in which future extreme events can occur with a given low probability, even beyond the range of the observed data, is an important ta…