The aim of the summer school is to review some aspects of quantitative methods applied to economics and finance. 

Particular emphasis will be placed on:

• methods that make use of massive or high-dimensional data. 
• applications to energy issues, in line with the research themes of the FiME laboratory.

Three themes will be highlighted, all of which are particularly relevant to today's world and pose crucial challenges.

High Dimensional Econometrics: Applications of high-dimensional statistics and machine learning methods in econometrics are increasingly popular. This course will cover the theoretical foundations and present practical applications. The main topics to be reviewed include variable selection, inference with high-dimensional nuisance parameters in different settings, heterogeneity, treatment allocation, policy evaluation, networks and text data.

Differential Privacy: Data privacy protection is a major issue for our society nowadays due to the massive amounts of data collected and stored by many electronic devices at all times, on social networks, in medecine, in finance and so on. Privacy preserving mechanisms have to be applied to the data before their public release which implies to quantify the amount of privacy, but also to make inference on the underlying population from the publicly available information. We shall discuss nonparametric estimation of the probability density, of some functionals of the density and variable selection.

Market Microstructure: The goal of this course is to give an introduction to the key statistical modelling questions at stake at the level of the microstructure of financial markets. We will show that using advanced tools from stochastic processes theory, statistics of random processes and machine learning we are able to solve important issues related to statistical estimation for high frequency data, order book modelling, algorithmic trading and financial regulation. We will also make the connection between market microstructure and the low frequency behavior of the volatility of financial assets.

The summer school is primarily aimed at PhD students in economics and finance (in mathematics applied to these fields). The courses offered at the school can be validated as part of their PhD training, subject to the agreement of their institution. PhD students will also be invited to present their research in a poster session. 

It is also open to academic and industrial researchers interested in these subjects who can propose contributions (presentations of research work) in line with the theme of the school and / or the research areas of the FiME Laboratory

Three courses will be held:

• A course on High Dimensional Econometrics (4h30) - by Pr. Christophe Gaillac (Oxford U.) & Pr. Jérémy L'hour (INSEE, CREST)
• A course on Differential Privacy (4h30), by Pr. Cristina Butucea (ENSAE)
• A course on Market Microstructure (4h30), by Pr. Mathieu Rosenbaum (CMAP, Ecole Polytechnique)

The program will also include some spare time to allow the participants to discuss / advance their own research.

The FiME Laboratory is a joint structure of EDF, the University of Paris-Dauphine, CREST and the Ecole Polytechnique where academic and industrial researchers from these institutions meet. Administratively, it is hosted by the Europlace Institute of Finance Foundation, which is part of the Louis Bachelier Group. 

https://www.fime-lab.org