Agostino Capponi 

&

Charles-Albert Lehalle

January 9th


Title: Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices

Date/Time: Tuesday, 01/09, 7pm CET (10am PST, 1pm EST)

Abstract: We provide an overview of the recently published book "Machine Learning and Data Science for Financial Markets: A Guide to Contemporary Practices', co-edited by Agostino Capponi and Charles-Albert Lehalle. We begin by discussing robo-advising and automated wealth management, together with its role in guiding investors allocation and consumption decisions. We then discuss the role of machine learning in risk intermediation, including derivative hedging, portfolio construction, market making, as well the interplay of reinforcement learning and mean-field games. We then discuss the role of modern data science techniques such as nowcasting and alternative data structures, the ethics of algorithms, and regulatory aspects of artificial intelligence in finance. Along the way, we provide key examples and illustrations to accompany concepts with use cases and financial engineering problems.

Speaker: Agostino Capponi (Columbia University)

Bio: Agostino Capponi is a Professor in the Department of Industrial Engineering and Operations Research at Columbia University, where he is also the founding director of the Columbia Center for Digital Finance and Technology. Agostino earned his PhD degree in Computer Science and Applied Mathematics from the California Institute of Technology. 

His current research interests are in financial technology, market microstructure, AI and machine learning in finance, systemic and liquidity risk, and economic networks. Agostino’s research has been recognized with the 2018 NSF CAREER award and with a JP Morgan AI Research Faculty award, and funded by major agencies, including NSF, DARPA, DOE, IBM, Ripple, and the Ethereum foundation. His research has also been covered by various media outlets, including Bloomberg, the Financial Times, VoX, and Politico. 

Agostino is a fellow of the crypto and blockchain economics research forum and an academic fellow of Alibaba's Luohan academy. He serves as an editor of Management Science in the Finance Department, editor of Operations Research in the Financial Engineering Department, and co-editor of Mathematics and Financial Economics. He serves or has served as an associate editor of major journals in his field, including Operations Research, the SIAM Journal on Financial Mathematics, Finance and Stochastics, Mathematical Finance, and Stochastic Systems.  Agostino is a past Chair of the SIAG/FME Activity Group and of the INFORMS Finance Section, and currently serves as a council member of the Bachelier Finance Society. Agostino is co-editor of the book Machine Learning and Data Sciences for Financial Markets: A Guide to Contemporary Practices, published by the Cambridge University press.

Speaker: Charles-Albert Lehalle (ADIA & Imperial College London)

Bio: Pr. Charles-Albert Lehalle is Global Head, Quantitative Research & Development, at ADIA. He started his career managing AI projects at the Renault research center and moved to the financial industry with the emergence of automated trading in 2005. He was Global Head of Quantitative Research at Crédit Agricole Cheuvreux, and Head of Quantitative Research on Market Microstructure at Crédit Agricole Corporate Investment Bank, before moving to Capital Fund Management. 

On the academic side, Pr. Lehalle received the 2016 Best Paper Award in Finance from Europlace Institute for Finance (EIF) and has published more than eighty academic papers and book chapters. He co-authored the books "Market Microstructure in Practice" (World Scientific Publisher, 2nd edition 2018), analyzing the main features of modern markets; and "Financial Markets in Practice" (World Scientific Publisher 2022), explaining how the connected network of intermediaries that makes the financial system is shaping prices formation; he co-edited with Pr Agostino Capponi the book "Machine Learning and Data Sciences for Financial Markets A Guide to Contemporary Practices" (Cambridge University Press, 2023). Pr. Lehalle studied machine learning for stochastic control during his PhD on nonlinear control and artificial neural networks. His “Habilitation à Diriger les Recherches” topics were mathematical models to study and control the price formation process. 

Pr. Lehalle is also a member of the Scientific Directory of the Louis Bachelier Institute, Lecturer at UC Berkeley and Paris 6 Sorbonne Université and Ecole Polytechnique “Probability and Finance” Master.