Who says Machine Learning and computer/algorithmic investing can‘t be exciting?
Prof Marcos Lopez de Prado in September 2018 joined AQR as their Head of Machine Learning/Principal with his team. „Our foundation in applied academia and our culture of intellectual curiosity mean we are always relentlessly looking for new data, signals and techniques to strengthen our investment process and build long-term persistent strategies. Our continued investment in machine learning will further advance these efforts.” said AQR’s CIO and Managing Principal, Cliff Asness.
Lopez de Prado had previously worked at Guggenheim Investments, founding and building the QIS team (quantitative investment strategies) from scratch four years ago. He developed high-capacity ML strategies for IG bond portfolios and his outperformance in a few years resulted in a $13 billion book of business, managed by him and his team.
While managing QIS, Lopez de Prado also was a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science), publishing dozens of scientific articles on machine learning and supercomputing.
In 2018, he authored the graduate textbook “Advances in Financial Machine Learning (Wiley, 2018)”. He holds two PhDs (financial economics and mathematical finance) from Madrid University and did his post-doc research at Harvard and Cornell, where he teaches a financial machine learning course at the School of Engineering.
After leaving Guggenheim in January, he filed a lawsuit against the firm „over the ownership of certain IP“ and, settling out of court, Guggenheim transferred ownership of the unit to him.
To read the full case study of the QIS investment process, the team and the business model, please click here.