Marcos López de Prado
20 years of experience
less than a year at AQR
Ph.D. (2), Universidad Complutense de Madrid
B.Sc., M.Sc., Universidad de Santiago de Compostela
Marcos López de Prado is a Principal and Head of Machine Learning at AQR Capital Management. In this role, he leads a team responsible for analyzing complex data for strategy development and a variety of applications across the firm. Prior to joining AQR, he founded and led Guggenheim Partners’ Quantitative Investment Strategies (QIS) business, where he developed high-capacity machine learning strategies, receiving up to $13 billion in assets. Concurrently with the management of investments, between 2011 and 2018, Marcos was also a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). He has published dozens of scientific articles on machine learning and supercomputing in the leading academic journals, and SSRN ranks him as one of the most-read authors in Economics. Among several monographs, he is the author of the graduate textbook Advances in Financial Machine Learning (Wiley, 2018). In 2019, Marcos received the "Quant of the Year Award" from The Journal of Portfolio Management. Marcos earned a B.Sc. and M.Sc. in econometrics and quantitative economics from Universidad de Santiago de Compostela, a Ph.D. in financial economics and a Ph.D. in mathematical finance, both from Universidad Complutense de Madrid, and was a recipient of Spain's National Award for Academic Excellence in 1999. He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a financial machine learning course at the School of Engineering.
Quant of the Year 2019, The Journal of Portfolio Management.
Author, Advances in Financial Machine Learning (Wiley, 2018).
Member of the advisory board, Journal of Portfolio Management.
Co-editor, Journal of Financial Data Science.
Member of the board of directors, International Association for Quantitative Finance.
Adjunct professor, Cornell University, Special Topics in Financial Engineering V (ORIE 5256).
Over 50 peer-reviewed publications in scientific journals, including Notices of the American Mathematical Society, Journal of Financial Economics, Review of Financial Studies, IEEE Journal of Selected Topics in Signal Processing, Mathematical Finance, Journal of Financial Markets, Quantitative Finance, Journal of Computational Finance, Journal of Portfolio Management, Journal of Risk, etc.