Prof. López de Prado's department is tasked with applying a systematic, science-based approach to developing and implementing investment strategies. This multi-disciplinary team will draw on the... Read more about Professor López de Prado Appointed Global Head of Quantitative Research and Development
Marcos López de Prado is a Visiting Professor at Cornell University's College of Engineering. He has helped modernize finance for the past 20 years, by popularizing the use 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, one of the largest sovereign wealth funds. Before that, he founded True Positive Technologies LP (TPT) after he sold some of his patents to AQR Capital Management, where he was a principal and AQR's first head of machine learning. TPT has been engaged by clients with a combined AUM in excess of $1 trillion. Marcos 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 economics (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.
Advances in Financial Machine Learning