- FR
- EN
Former student of ENS Lyon, Pierre Brugière has obtained the Agrégation de Mathématiques in 1987 and then joined the ENSAE and the DEA MASE of Dauphine. He completed his Phd in 1992 before turning Associate Professor. Between 1992 and 2015, he worked for various financial institutions ( CPR Paris, Natwest Securities, Bankers Trust, Deutsche Bank, BNPP).
Brugiere P., Turinici G. (2023), Deep learning of value at risk through generative neural network models: The case of the Variational auto encoder, MethodsX, vol. 10, p. 102192 
Brugiere P. (2020), Quantitative Portfolio Management. with Applications in Python Springer, XII-205 p.
Brugiere P., Turinici G. (2022), A few key issues in finance that machine learning is helping solve, JP Morgan Global Machine Learning Conference, Paris, France
Brugiere P., Turinici G. (2024), Transformer for Times Series: an Application to the S&P500, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 19 p.
Brugiere P., Turinici G. (2023), Onflow: an online portfolio allocation algorithm, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 20 p.
Brugiere P., Turinici G. (2022), Deep learning of Value at Risk through generative neural network models : the case of the Variational Auto Encoder, Paris, Cahier de recherche CEREMADE, Université Paris Dauphine-PSL, 4 p.
