Sponsorship page

Prof. Marcos López de Prado is the CIO of True Positive Technologies (TPT), and Professor of Practice at Cornell University’s School of Engineering. He has over 20 years of experience developing investment strategies with the help of machine learning algorithms and supercomputers. Marcos launched 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 is currently 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 investments, 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 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), 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 is a faculty member. Marcos has an Erdős #2 according to the American Mathematical Society, and in 2019, he received the ‘Quant of the Year Award’ from The Journal of Portfolio Management.

Fabio is global head of Quantitative Analytics at Bloomberg LP, New York. His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA valuations and credit and market risk. Fabio is also adjunct professor at NYU, and a former CME risk committee member. He has jointly authored the book 'Interest rate models: theory and practice' and published extensively in books and international journals, including 16 cutting-edge articles in Risk Magazine. Fabio holds a BSc in Applied Mathematics from the University of Padua, Italy, and a PhD in Mathematical Finance from the Erasmus University of Rotterdam, The Netherlands

Tony is a Managing Director in Nomura’s Global Markets Research team, based in London. He heads the Quantitative Strategies (QS) team, which clients rank as one of the leading groups of its kind in the industry. QS focuses on objective measurement of fundamental economic and market dynamics around the world. Grounded in these measurements, QS makes recommendations that a number of internal and external clients track. Asset classes covered include interest rates, commodities, currencies, credit and equities. The team’s combined portfolio has outperformed relevant hedge fund benchmarks. Tony holds a PhD in financial economics from New York University and a BA from Dartmouth College, where he earned a place in the Phi Beta Kappa academic honour society

Michael is the global head of Quantitative Execution Services at Goldman Sachs. He is responsible for the research, development and implementation of quantitative processes for portfolio and electronic trading, as well as the management of the firm's relationships with the quantitative client-base across regions. Michael manages a variety of teams globally, spanning algorithmic research, portfolio quants, client solutions, analytics and quantitative content generation. He joined the firm as a managing director in 2017.

Prior to this, Michael spent eight years at Bank of America Merrill Lynch in a variety of senior roles in London and New York, including the centralisation of risk for the bank’s equities flow, quantitative liquidity management processes and in the last few years running the global agency portfolio trading and quantitative equity businesses. Earlier in his career, he spent more than a decade on the buy-side (most notably BGI and Winton) building quant stock-selection models and managing global market neutral equity portfolios. Before that, Michael was a Financial Econometrics lecturer at City University (CASS) Business School in London. He has a wide range of academic, peer-reviewed and practitioner journal and book publications on a host of finance topics, as well as numerous presentations in global quant and industry conferences.

Michael received a bachelor's degree in Economics & Econometrics from the University of Nottingham, a master's degree in Finance and a PhD in Behavioural Finance from City University (CASS) Business School in London.

Nick Baltas, Ph.D., is a managing director and head of R&D of the Systematic Trading Strategies (STS) Group at Goldman Sachs. He is responsible for providing thought leadership in the space of factor and risk premia investing, portfolio construction, and strategy design. Alongside, he maintains a visiting academic position at Imperial College Business School and has been appointed as the co-executive editor of the newly launched Journal of Systematic Investing.

Prior to joining Goldman Sachs in 2017, Nick was an executive director in the quantitative research unit of UBS. Previously, he was a Lecturer in Finance at Imperial College Business School, a visiting Lecturer at Queen Mary University of London, as well as a risk manager in a London-based hedge fund. He has received several teaching awards and his research has been awarded with numerous grants and prizes, has been published in academic finance journals and practitioner books, and has been quoted by the financial press. Most recently he was the recipient of the 2019 EQDerivatives Best Academic Research Paper Award in Alternative Risk Premia (joint with Bernd Scherer).

Nick holds a DEng in electrical and computer engineering from the National Technical University of Athens, an MSc in communications & signal processing from Imperial College London and a PhD in financial economics from Imperial College Business School.

Rohini Grover is an FX strategist at Deutsche Bank in London. Her areas of interest and research include FX volatility modelling and forecasting, and market microstructure.   She holds a PhD and a masters in economics from Indira Gandhi Institute of Development Research (IGIDR), Mumbai.