Patrimony
The Louis Bachelier Group's patrimony has been defined as all the publications produced by academic researchers thanks to Group funding (ILB, FdR, IEF, Labex) or via the use of EquipEx data (BEDOFIH, EUROFIDAI).
An empirical analysis of systemic risk in commodity futures markets.
Commodities, Financialization, Financiarisation, Grande dimension, Graph, Graphe, High dimension, Matières premières, Risque systémique, Systemic risk
Variable selection for unsupervised high-dimensional classification.
Classification non supervisée, Clustering, Critère de sélection de modèle non asymptotique, Data-driven non-asymptotic model selection criterion, Finite Gaussian mixture models, Grande dimension, High dimension, Inégalités oracle, L1-regularization, Lasso, Modèles de mélange gaussien, Oracle inequalities, Régularisation l1, Sélection de variables, Variable selection
An empirical analysis of systemic risk in commodity futures markets.
Commodities, Financialization, Financiarisation, Grande dimension, Graph, Graphe, High dimension, Matières premières, Risque systémique, Systemic risk
Vibrato and Automatic Differentiation for High Order Derivatives and Sensitivities of Financial Options.
Automatic Differentiation, Euler Scheme, Greeks, High Dimension, High Order Derivative, Monte Carlo Method, Option Pricing, Path-Dependent Option, Vibrato
On unsupervised learning in high dimension.
Aggregation, Agr?gation, Clustering, Density estimation, Estimation de densit?, Gaussian mixtures, Grande dimension, High dimension, M?lange de gaussiennes
Nonparametric estimation of conditional densities: high dimensionality, parsimony and gluttonous algorithms.
Algorithmes gloutons, Conditional density, Densité conditionnelle, Estimateurs à noyau, Estimation non paramétrique, Grande dimension, Greedy algorithms, High dimension, Kernel density estimators, Nonparametric estimation, Parcimonie, Sparsity
Adaptive greedy algorithm for moderately large dimensions in kernel conditional density estimation.
Conditional density, Greedy algorithm, High dimension, Kernel density estima- tors, Minimax rates, Nonparametric inference, Sparsity