Pladifes aims to facilitate research in traditional finance, as well as in green and sustainable finance. This is partly enabled by the access for academics to financial and soon extra-financial data on the Eurofidai website. Anoher lever is the ILB Pladifes Teams, providing custom sustainable finance data creation services and privileged access to ESG databases (to come in 2023). They are also the main craftsmen of the ESG data cartography.
Led by the Institut Louis Bachelier, in partnership with the EUROFIDAI UAR CNRS 3390 laboratory, ESSEC, IFA and the finance innovation competitiveness cluster, the Plate-Forme De Calcul Numérique, Intelligence Artificielle et Base Internationale de Données Environnementales, Financières et Sociétales à Fréquence Elevée (Equipex PLADIFES) has been selected within the framework of the Investissements d’avenir 2021 (ANR-21-ESRE-0036).
The creation of the EUROFIDAI daily and BEDOFIH high frequency financial databases was the first phase of this innovative research project. Academics benefit fully from these financial databases for the European markets, in the same spirit as those of CRSP for the US market. The Equipex PLADIFES represents phase II of this research project. The objective is to develop these two financial databases by merging them into a single platform, extending their coverage to other countries outside Europe and adding extra-financial “ESG” data using modern artificial intelligence techniques.
The Equipex PLADIFES is a player in the digital revolution in the field of finance and its contributions will be numerous:
- The merger of the existing projects of EUROFIDAI (Daily-ESSEC et BEDOFIH), Green Value AI, and the Pierre-Louis-Lions research group (specialised in mathematics and AI) within the ILB.
- Collaboration and sharing of resources between researchers in mathematics, AI, finance and computer science from several institutions (EUROFIDAI (CNRS), ESSEC (ESSEC-Amundi Chair), Institut Louis Bachelier and Pierre-Louis-Lions’ research group in mathematics and artificial intelligence).
- The improvement of existing databases by adding high value-added extra-financial ESG criteria.
- Extending the scope of the current databases to countries outside Europe, more specifically to Asia, Australia, the Middle East, etc.
- The development, improvement and implementation of new numerical algorithms and techniques in artificial intelligence (text and image analysis, synthetic data production).
- Advancing fundamental mathematical research on mean-field games, optimal transport and deep learning.
- Providing solutions to societal problems and providing significant support to international academic research in mathematics, statistics, econometrics and finance.
- Providing high quality financial services to investment managers, financial institutions and securities regulators.
- By creating this new platform for research in numerical computation and artificial intelligence, using high-frequency financial and ESG data, we will provide useful tools not only for researchers in applied mathematics and finance, but also for researchers in statistics, computer science, economics, climatology and the environmental field. This platform, which has no equivalent in the academic world, will also allow companies and regulatory bodies to check the relevance of their models, to help them make decisions and develop sustainable investment projects.
Scientific and technical leader of the project: Pierre Louis LIONS, Scientific Director of the ILB and Professor at the Collège de France
Coordinating institution: Institut Louis Bachelier
Heads of Axis:
Axis 1 – Computational Mathematics – AI – Green Value: Pierre-Louis Lions and Peter Tankov (ILB)
Axis 2 – Daily financial and ESG data: Jocelyn Martel (ESSEC)
Axis 3 – High frequency financial and extra financial data: Patrice Fontaine (EUROFIDAI CNRS)
Axis 4 – Valuation: Dominique Leblanc (IFA – PFI)
Partner institutions: ILB, ESSEC, CNRS and the Finance Innovation competitiveness cluster,
Information Finance Agency for industrial valorisation in the future.