Marcos López de Prado

Marcos López de Prado is a hedge fund manager, entrepreneur, inventor, and Cornell professor. Over the past 25 years, Marcos has helped modernize finance by pioneering machine learning and statistical inference methods that are now widely adopted at some of the largest investment corporations. His contributions have earned him several scientific, state and industry awards, including the National Award for Academic Excellence (1999) by the Kingdom of Spain, the Quant Researcher of the Year Award (2019) by Portfolio Management Research, the Buy-Side Quant of the Year Award (2021) by Risk, and the Bernstein Fabozzi / Jacobs Levy Award (2024) by The Journal of Portfolio Management. The Social Science Research Network (SSRN) ranks him among the 10 most-read authors in Economics, and he has testified before the U.S. Congress on AI policy. In 2024, His Majesty King Felipe VI and the Government of Spain appointed him Knight Officer of the Royal Order of Civil Merit (OMC), "for distinguished services to science and the global investment industry." Marcos serves currently as global head of quantitative research and development at the Abu Dhabi Investment Authority (ADIA), one of the largest sovereign wealth funds, and is a founding board member of ADIA Lab, Abu Dhabi's center for research in data and computational sciences. Before ADIA, he founded True Positive Technologies LP (TPT), a firm that researches and develops investment IP. TPT has advised clients with a combined AUM in excess of 1 trillion US dollars, and has licensed and sold several patents to some of the largest investment funds in 8-figure dollar deals. Before TPT, Marcos was a partner and the first head of machine learning at AQR Capital Management. As a senior managing director at Guggenheim Partners, he also founded and led its Quantitative Investment Strategies business, where he managed 13 billion US dollars in assets, and delivered an audited risk-adjusted return (information ratio) of 2.3. Concurrently with the management of multibillion-dollar funds, since 2011 Marcos has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). He has published approximately 100 scientific articles on financial machine learning and statistical inference in the leading academic journals, is a founding co-editor of The Journal of Financial Data Science, and the author of several influential graduate textbooks, including Advances in Financial Machine Learning (Wiley, 2018), Machine Learning for Asset Managers (Cambridge University Press, 2020), and Causal Factor Investing (Cambridge University Press, 2023). Marcos earned a PhD in financial econometrics (2003), and a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid. He completed his post-doctoral research at Harvard University and Cornell University, where he is a professor. Marcos has an Erdős #2 (via Neil Calkin) and an Einstein #4 according to the American Mathematical Society.