Paris Dauphine – PSL × HEC Montréal × Université d'Orléans
FAME studies how generative AI changes investor behaviour, price formation, and market integrity — combining financial economics, econometrics, and experimental evidence.
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.
Underpinning this work is a hand-annotated gold-standard news–firm dataset, built with students of the Dauphine Tunis campus and coordinated across Paris, Montréal, and Tunis.
Researchers in financial economics, econometrics, and machine learning across three 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 Next Challenge.
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 Next Challenge, 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.