Category Archives: Research

Méthodes de prévision en finance (et copules)

Le livre Méthodes de prévision en finance est sorti, en France, cette semaine. L’application que je propose pour montrer la modélisation par copules (par opposition aux modèles GARCH multivariés en particulier) est basée sur un vieux billet sur le blog (ou les codes permettent de reproduire l’analyse que j’en fait), remis en forme dans un court article, Prévision avec des copules en finance

Machine Learning in Actuarial Science and Insurance

This week is organized the summer school on machine learning for economists and applied social scientists. I will be giving an (online) lecture this Thursday, on Machine Learning in Actuarial Science & Insurance, with a great program,

  • 10am – 10:55am : Juri Marcucci: Machine Learning in Macroeconomics
  • 11am – 11:55am : Arthur Charpentier: Machine Learning in Actuarial Science & Insurance
  • 12pm – 12:55pm : Arthur Spirling : Machine Learning in Embeddings Representations
  • 1pm – 1:55pm : Kathy Baylis: Machine Learning in Agricultural Economics
  • 2pm – 2:55pm : Stefan Wager : Machine Learning in Causal Inference
  • 10am – 10:55am : Stan Matwin : Machine Learning and Data Privacy
  • 11am – 11:55am : Mehmet Caner : Machine Learning in Econometrics
  • 12pm – 12:55pm : Anders Bredahl Kock : Machine Learning in Model Selection
  • 1pm – 1:55pm : Dario Sansone: Machine Learning in Education and Development Economics
  • 2pm – 2:55pm: Patrick Baylis :Temperature and Temperament: Evidence from Twitter

My slides are now online,

Personalization as a promise: Can Big Data change the practice of insurance?

Our recent article, “Personalization as a Promise: Can Big Data Change the Practice of Insurance?” with Larence Barry just got published in “Big Data & Society” (but a working paper version is still available online)

The purpose of this paper is to measure the impact of technologies from the Big Bang. data on thehe pricing ofhe products car insurance. The first part describes how the aggregated view buildsuit by statistics enables highlighting invisible regularities at the individual level. Despite a very granular segmentations in automobile insurance, the approach remained classificatory, hypothesizing the risk identity of individuals from the same class. The second part highlights the reversal of big data-induced perspective in the’analysis ofgiven ; awith theur volume and the new algorithms, the aggregate viewpoint is questioned.. The hypothesis of class homogeneity is becoming increasingly difficult to test. maintain, especially since predictive analysis boasts the ability to predict the rs results at the individual level. The third part is studying the’influence of telematics boxes able to import the new pinsurance aradigm automobile. However, a reading of the most recent research articles on a pricing automobile including this new monter that the epistemological leap, at least for now, has not taken place.

COVID19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability

After almost two months, with Romuald Elie, Chi (Tran Viet Chi) and Mathieu Laurière, we finally have a draft of the paper related to our recent work, entitled COVID-19 pandemic control: balancing detection policy and lockdown intervention under ICU sustainability” (available on HAL ArXiv and MedrXiv)

Our model is an extention of the classical SIR model, but more realistic for the COVID-19 (pronounded “cider”)

We use scenarios to see the impact on various quantities

but also optimal control to see the best strategy, when it comes to lockdown, and testing. All comments are welcome…