23 citations · 29 across the 9 of their papers we have counts for
10 papers
Gradient boosting for extremes: sampling theory and application to insurance
Stéphane Lhaut, Olivier Lopez
We develop a statistical learning theory for gradient boosting applied to the estimation of covariate-dependent Generalized Pareto (GP) distributions in the context of Peaks-over-T…
A stochastic SIR model for cyber contagion: application to granular growth of firms and to insurance portfolio
Caroline Hillairet, Olivier Lopez, Lionel Sopgoui
This work evaluates the impact of contagious cyber-events, over a finite horizon, on firms' financial health and on a cyber insurance portfolio. Our approach builds on key empirica…
WTNN: Weibull-Tailored Neural Networks for survival analysis
Gabrielle Rives, Olivier Lopez, Nicolas Bousquet
The Weibull distribution is a commonly adopted choice for modeling the survival of systems subject to maintenance over time. When only proxy indicators and censored observations ar…
Parametric insurance for extreme risks: the challenge of properly covering severe claims
Olivier Lopez, Maud Thomas
Parametric insurance has emerged as a practical way to cover risks that may be difficult to assess. By introducing a parameter that triggers compensation and allows the insurer to…
Generalized Pareto Regression Trees for extreme events analysis
Sébastien Farkas, Antoine Heranval, Olivier Lopez +1
In this paper, we provide finite sample results to assess the consistency of Generalized Pareto regression trees, as tools to perform extreme value regression. The results that we…
Single-index copulae
Jean-David Fermanian, Olivier Lopez
We introduce so-called "single-index copulae". They are semi-parametric conditional copulae whose parameter is an unknown "link" function of a univariate index only. We provide est…