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Marcos López de Prado is a hedge fund manager, entrepreneur, inventor, and professor. He has helped modernize finance for the past 25 years, by pioneering machine learning and supercomputing methods, 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 Researcher of the Year Award (2019) by The Journal of Portfolio Management, and the Buy-Side Quant of the Year Award (2021) by Risk.net. For five consecutive years, SSRN has ranked him as the most-read author in Economics.
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 USD 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 partner 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 USD 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, and has testified before the U.S. Congress on AI policy. 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 professor. Marcos has an Erdős #2 (via Neil Calkin) and an Einstein #4.
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