6 citations · 8 across the 7 of their papers we have counts for
7 papers
Morillas-type transformations of copulas and stable tail dependence functions
Klaus Herrmann, Marius Hofert, Mélina Mailhot +1
A stochastic representation and sampling algorithm for Morillas-type copula-to-copula transformations and related distortions of multivariate distribution functions is derived, res…
Probabilistic Crop Yields Forecasts With Spatio-Temporal Conditional Copula Using Extreme Weather Covariates
Marie Michaelides, Mélina Mailhot, Yongkun Li
We introduce a novel forecasting model for crop yields that explicitly accounts for spatio-temporal dependence and the influence of extreme weather and climatic events. Our approac…
Deviance Voronoi Residuals for Space-Time Point Process Models: An Application to Earthquake Insurance Risk
Roba Bairakdar, Debbie Dupuis, Melina Mailhot
Insurance risk arising from catastrophes such as earthquakes a component of the Minimum Capital Test for federally regulated property and casualty insurance companies. Analyzing ea…
Uncertainty Propagation and Dynamic Robust Risk Measures
Marlon Moresco, Mélina Mailhot, Silvana M. Pesenti
We introduce a framework for quantifying propagation of uncertainty arising in a dynamic setting. Specifically, we define dynamic uncertainty sets designed explicitly for discrete…
Modeling and measuring incurred claims risk liabilities for a multi-line property and casualty insurer
Carlos Andrés Araiza Iturria, Frédéric Godin, Mélina Mailhot
We propose a stochastic model allowing property and casualty insurers with multiple business lines to measure their liabilities for incurred claims risk and calculate associated ca…
Range Value-at-Risk: Multivariate and Extreme Values
Roba Bairakdar, Lu Cao, Melina Mailhot
The concept of univariate Range Value-at-Risk, presented by Cont et al. (2010), is extended in the multidimensional setting. Traditional risk measures are not well suited when deal…
Multivariate Geometric Expectiles
Klaus Herrmann, Marius Hofert, Melina Mailhot
A generalization of expectiles for d-dimensional multivariate distribution functions is introduced. The resulting geometric expectiles are unique solutions to a convex risk minimiz…