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Marcos López de Prado is a principal at AQR Capital Management, and its head of machine learning. Before AQR, he founded and led Guggenheim Partners’ Quantitative Investment Strategies (QIS) business, where he developed high-capacity machine learning strategies that consistently delivered superior risk-adjusted returns, 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).
Marcos earned a PhD in financial economics (2003), a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (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. Marcos has an Erdős #2 and an Einstein #4 according to the American Mathematical Society.