Paris Dauphine – PSL × HEC Montréal
FAME advances the use of Generative AI and Large Language Models in financial analysis, portfolio management, and market supervision — bridging quantitative finance, econometrics, and state-of-the-art AI.
How generative AI is reshaping investors, markets, and the tools that supervise them.
How Generative AI changes the way investors process information and make decisions.
How AI-driven demand reshapes asset prices and market efficiency.
Adversarial manipulation of AI strategies and real-time tools for regulators.
Researchers in quantitative finance, econometrics, and machine learning across two institutions.
Popular-science articles and interviews from the FAME team.
On the risks and limits of AI in retail investment advice, drawing on the FAME project's experimental work and the Nextwise game.
Introduces the dossier's five contributions: AI as a stress-test of the system's fragilities that reshuffles positions among market participants.
Presents the FAME research program and the Nextwise game, which confronts LLM-driven strategies with human investors in a rigorous experimental setting.
A theoretical model showing AI productivity gains accrue unevenly — "human with machine" consistently outperforms "machine without human."
How Dauphine-PSL's finance curricula integrate machine learning and programming to train professionals who can critically assess AI's limits.
How close university–industry collaboration keeps curricula adapted to rapid AI evolution, illustrated by the ISF Master program.
A stocktake of real AI risks in finance — hallucinations, data poisoning, algorithmic monoculture, systemic risk. AI assists experienced managers; it doesn't replace them.