Global Head - Quantitative R&D at ABU DHABI INVESTMENT AUTHORITY (ADIA), Professor of Practice at CORNELL UNIVERSITY
Legendary professor Frank Fabozzi recently interviewed me for The Journal of Financial Data Science. The open-access article is available here: https://lnkd.in/dEFWNCZk In this conversation, I share my views on the evolving landscape of financial data science, highlighting the integration of advanced machine learning techniques and the critical need to bridge the gap between academic research and industry applications. I also discuss key challenges and future directions in the field, offering perspectives for professionals and researchers exploring the role of data science in finance.
Håkon Kavli
1w
Marcos Lopez de Prado This is a great interview. Excellent questions from Prof Frank Fabozzi and, as always, thought provoking insights from you. I do hope your critique of back testing will get broader traction in the world of quant based asset management. We are in the early stages of developing a framework for tactical data driven strategies at Reitan Kapital. And just like we did when researching portfolio optimisation, we once again find your work to be the best source of tools and methods to ensure robust analysis. Thank you!
Marcos Lopez de Prado amazing career trajectory! Well done!
“López de Prado: Black-box machine learning models tend to be overfitted to a very particular associational pattern in the data, which is not understood by the researcher (hence the black box). This associational pattern may not occur out of sample, or it may cease to occur at a random time, which is again unpredictable given the opacity of the model. In particular, black-box machine learning methods are not robust to parameter shifts. Thus, they are generally unsuitable for modeling complex dynamic systems like financial markets. Robustness is a virtue of causality, and economists are best positioned to identify and explain the causal mechanisms responsible for the observed associations. Furthermore, in a recent paper, I have shown that causal modeling is a necessary condition for portfolio efficiency.” 👏🏻👏🏻👏🏻
Nicholas Fok
17h
Great insights, Marcos! I’m curious about your thoughts on the future role of machine learning in finance. How do you see its evolution impacting the balance between academic research and industry? Would love to hear more about any exciting applications you've encountered recently.
"Legendary" is 100% right! Go Professor Frank Fabozzi! The Johns Hopkins University - Carey Business School The Wall Street Journal
D. Langston
4d
Your insights on bridging academic research with industry applications are crucial. How do you see machine learning reshaping the finance sector?
Why am I hearing about this only now Marcos! That's amazing. I'm sure you add value, as you always do.
I have read most of his books.. Mr fixed income!! Congrats!!
Angel Serrat sharing the love for causality. Ramon Verastegui
Global Head - Quantitative R&D at ABU DHABI INVESTMENT AUTHORITY (ADIA), Professor of Practice at CORNELL UNIVERSITY
1wDaniel Nehren Lars Boyde Jean-Francois Perreton Emilio Said Yuri Taranenko Silviu VLASCEANU Angelo P. Dmitry Muravey Arthur Maghakian Ricardo Laiseca LUCÍA SALA SILVEIRA Luis Seco Santiago Carrillo Menendez Rogelio Sanchez Ramo Gilbert Mateu Fernando Bolivar Almela Mauro Cesa Justina Lee Francisco Herrera Enrique Herrera-Viedma Magnus Reitan Håkon Kavli Kristina Jacobsen Emilio Said Katie Martin Robin Wigglesworth Angel Serrat Michael Steliaros Dhaen Al Hameli Mohamed Al Hajeri Khadem AlRemeithi Dr. Ebrahim Alhajri Jean-Paul Villain Matar Almazrouei Anders Svennesen Pascal Blanqué Naveed Malik Carlo Teufel Valerie Hawley Antoine Delcourt Robert Lauer Lorenzo Fanara Bayan Sharif Joseph Simonian, Ph.D. Dr Miquel Noguer i Alonso Pablo Casas Noguerol Dr Bernd Scherer Justina Lee Mimi Duff Óscar García Oltra Anne Forbes Luis Garcia-Feijoo, Ph.D., CFA Allison Adams Dragan Sestovic Gautier Marti Dushyant Sharma Tomas Thornquist Vincent Zoonekynd Jean François (JF) Ruhashyankiko, PhD Sergei Ryshkevich Huang Huang Dr. Mohamed Abolfadl Ibrahim Karolis Jankauskas, PhD Thibaut Montes, Ph.D Amine R. Sébastien Andler Sébastien Fries Antoine Arnoud Kamran Javid Kristof Juhasz Kriton Konstantinidis Alexis Marchal