093: Arthur Charpentier on Freakonometrics, Machine Learning and Big Data
Arthur Charpentier is currently Assistant Professor at the Faculty of Economics at Université de Rennes I.
Professor Charpentier’s teaching activities include Economics of Uncertainty, Modelling Natural Catastrophes, Nonlinear Econometrics, Multivariate Data Analysis, Advanced Techniques in Portfolio Management and Probability and Statistics.
Arthur’s research interests include copula theory, extreme values with applications in finance and insurance, option pricing, actuarial science and statistics of insurance, risk measures, capital allocation and diversification.
Arthur describes his blog ‘freakonometrics’ as an open lab-notebook experiment which can be found at freakonometrics.hypotheses.org/
Arthur completed a PhD Thesis in Mathematics (Statistics) at University of Leuven and a Masters degree in Mathematics applied to economics at University Paris IX Dauphine.
In this episode, Arthur mentions: econometrics, significance tests, t-tests, p-value, confidence level, variables, big data, in-sample tests, out 0f sample tests, copula theory, linear models, non-linear models, machine learning and artificial intelligence.
In this episode, Arthur mentions: Josh Angrist and Steve Pischke.
- Freakonometrics: www.freakonometrics.hypothesis.org
- Tensorflow: www.tensorflow.org
- Journal of Machine Learning Research: www.jmlr.org
- Mastering ‘Metrics: The Path from Cause to Effect by Josh Angrist and Steve Pishcke
- Mostly Harmless Econometrics by Josh Angrist and Steve Pishcke
- Mathématiques De L’assurance Non-Vie by Arthur Charpentier
- Computational Actuarial Science with R by Arthur Charpentier