{"id":13707479,"url":"https://github.com/gpitt71/gemact-code","last_synced_at":"2025-10-27T15:18:40.375Z","repository":{"id":47218129,"uuid":"486915400","full_name":"gpitt71/gemact-code","owner":"gpitt71","description":"Repository of GEMAct source code. 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M. (2024). GEMAct: a Python package for non-life (re)insurance modeling. Annals of Actuarial Science, 1–37. doi:10.1017/S1748499524000022\n```\n\nBibteX citation:\n\n```\n@article{Pittarello_Luini_Marchione_2024, \ntitle={GEMAct: a Python package for non-life (re)insurance modeling}, \nDOI={10.1017/S1748499524000022},\njournal={Annals of Actuarial Science}, \nauthor={Pittarello, Gabriele and Luini, Edoardo and Marchione, Manfred Marvin}, \nyear={2024}, \npages={1–37}} \n```\n\nThe manuscript pre-print is instead available at [ArXiV:2303.01129](https://arxiv.org/abs/2303.01129).\n\n# Future work\n\nPlease do not hesitate to contact us if you are interested in helping us in expanding our package, you can find our contact details [here](https://gem-analytics.github.io/gemact/gemanalytics.html). Possible future enhancements could involve the introduction of new probability distribution families, the implementation of supplementary methodologies for the approximation of quantiles of the sum of random variables, and the addition of costing procedures for exotic and nontraditional reinsurance solutions.\n\n# Acknowledgments\n\nPrevious versions were presented at the Mathematical and Statistical \nMethods for Actuarial Sciences and Finance 2022, and at the Actuarial Colloquia 2022, in the ASTIN section. \n\nWe want to especially thank the students in Statistica per le assicurazioni,\nM.Sc. in Economia e Finanza, at the University of Milano-Bicocca for having tested the package.\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgpitt71%2Fgemact-code","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgpitt71%2Fgemact-code","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgpitt71%2Fgemact-code/lists"}