Since Louis Bachelier's thesis in 1900 — a theory of Brownian motion 5 years before Einstein — our understanding of financial markets has progressed reasonably. Over the past few decades, financial engineering has grown considerably and has unfortunately gone beyond our comprehension. The inadequacy of the models used to describe financial markets may have contributed to financial crises that have a significant impact on our economy. From a physicist's perspective, understanding the formation of prices in financial markets — how markets absorb and process information from thousands of individual agents to arrive at a “fair” price — is a fascinating challenge. Statistical physics has taught us that systems made up of a large number of individual entities can have robust (often unexpected) patterns that exceed individual behaviors or, as P. W. Anderson says, “More is different” (Science 177, 1972). Understanding the destabilization mechanisms inherent in the criticality of financial markets is a question of undeniable economic and societal importance. We want to promote the sharing of knowledge and exchanges between the professional world and the scientific community in the microstructure of financial markets, and more generally on issues relating to complex economic and social systems.

Training:

25 theses, 10 post-docs and around fifty M2 trainees, i.e. more than 80 students trained to date.

Scientific production:

More than 60 publications on the themes of the program.

Main objective:

Understand complex socioeconomic systems using statistical physics tools.

In detail: model the dynamics of systems composed of numerous agents (traders, households, businesses, banks) by taking into account their interactions, heterogeneities, and memory, as for physical systems such as molecules, schools of fish or flocks of birds.

Recent applications:

Analysis of price impact and cross-impact on financial markets.

Study of liquidity crises and order book instabilities.

Use of machine learning for financial time series analysis.

Modeling firm networks to understand macroeconomic fluctuations.

Optimization of agricultural land by taking into account the links between biodiversity and economic profitability.

Ongoing studies on the effects of wealth inequalities on the energy transition.

Teaching:

Creation of 3 courses in econophysics (2 at ENSAE in 1A and 3A, 1 at École Polytechnique in 3A).

Diversity and inclusion:

Launch of the CFM WIQF (Women in Quant Finance) scholarship to encourage young women to pursue careers in a field that is still under-represented. The 5th winner starts this week.

Partnerships:

Collaboration with the NAEC (New Approaches to Economic Challenges) division of the OECD.

Popularization:

Creation of the YouTube series “Econophysix Lab in a Nutshell”, where students share their work via educational videos.

Website:

Don't forget to visit Www.econophysix.com

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