Marcos López de Prado is Professor of Practice at Cornell University’s School of Engineering. He has helped modernize finance for the past 20 years, by advancing the adoption of machine learning and supercomputing, and by developing statistical tests that identify false investment strategies (false positives). In recognition of this work, Marcos has received various scientific awards, including the National Award for Academic Excellence (1999) by the Kingdom of Spain, the Quant of the Year Award (2019) by The Journal of Portfolio Management, and the Buy-Side Quant of the Year Award (2021) by Risk.
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. 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, and has licensed and sold several patents to some of the largest investment funds in 8-figure dollar deals. Before TPT, Marcos was a principal and the first head of machine learning at AQR Capital Management. He also founded and led Guggenheim Partners’ Quantitative Investment Strategies business, where he managed up to $13 billion 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 dozens of scientific articles on machine learning and supercomputing in the leading academic journals, is a founding co-editor of The Journal of Financial Data Science, has testified before the U.S. Congress on AI policy, and SSRN ranks him as the most-read author in economics. Marcos is the author of several popular graduate textbooks, including Advances in Financial Machine Learning (Wiley, 2018) and Machine Learning for Asset Managers (Cambridge University Press, 2020). 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 faculty member. Marcos has an Erdős #2 and an Einstein #4 according to the American Mathematical Society.
RECENT ACADEMIC CONTRIBUTIONS
Machine Learning for Asset Managers
(Cambridge University Press, 2020). Translated to
Chinese and Japanese.
Author, Advances in Financial Machine Learning (Wiley, 2018). Translated to Chinese, Russian, Japanese, Korean and Polish.
Inventor, U.S. Patent # 11,410,240: Tactical investment algorithms through monte carlo backtesting (Exp. 09/15/2040)
Member of the advisory board, The Journal of Portfolio Management.
Founding co-editor, The Journal of Financial Data Science.
Member of the board of directors, International Association for Quantitative Finance.
Professor of Practice, Cornell University, School of Engineering. Special Topics in Financial Engineering V (ORIE 5256).
Over 70 peer-reviewed publications in scientific journals, including:
Notices of the
American Mathematical Society
Journal of Financial Economics (JCR 5Y IF: 7.513)
Review of Financial Studies (JCR 5Y IF: 5.864)
IEEE Journal of Selected Topics in Signal Processing (JCR IF: 4.361)
Mathematical Finance (JCR IF: 2.714)
Journal of Financial Markets (JCR 5Y IF: 2.234)
Quantitative Finance (JCR IF: 1.170)
Journal of Computational Finance (JCR 5Y IF: 0.831)
Journal of Portfolio Management (JCR IF: 0.812)
Journal of Risk (JCR IF: 0.627)
American Mathematical Monthly (JCR IF: 0.361)