592 citations · 615 across the 23 of their papers we have counts for
29 papers
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.…
Asymptotic theory for the likelihood-based block maxima method in time series
David L. Carl, Simone A. Padoan, Stefano Rizzelli
This paper develops a rigorous asymptotic framework for likelihood-based inference in the Block Maxima (BM) method for stationary time series. While Bayesian inference under the BM…
Predicting hazards of climate extremes: a statistical perspective
Carlotta Pacifici, Simone A. Padoan, Jaroslav Mysiak
Climate extremes such as floods, storms, and heatwaves have caused severe economic and human losses across Europe in recent decades. To support the European Union's climate resilie…
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…
Asymptotic theory for Bayesian inference and prediction: from the ordinary to a conditional Peaks-Over-Threshold method
Clément Dombry, Simone A. Padoan, Stefano Rizzelli
The Peaks Over Threshold (POT) method is the most popular statistical method for the analysis of univariate extremes. Even though there is a rich applied literature on Bayesian inf…
Marginal expected shortfall inference under multivariate regular variation
Simone A. Padoan, Stefano Rizzelli, Matteo Schiavone
Marginal expected shortfall is unquestionably one of the most popular systemic risk measures. Studying its extreme behaviour is particularly relevant for risk protection against se…