Machine Learning in Portfolio Construction
28 May 2020, 5:00 pm - 5:45 pm BSTRegister
In this interactive webinar, Professor Lopez de Prado will discuss convex optimization solutions in the context of signal-induced and noise-induced instabilities, identifying machine learning methods that improve investment performance.
Hosted by CFA Institute
Financial markets have become increasingly complex. Machine learning offers powerful tools for portfolio construction that complement and overcome some of the limitations of classical statistical methods. Join Professor Marcos Lopez de Prado of Cornell University to discuss effective processes for analyzing data and testing investment strategies. In this interactive webinar, Professor Lopez de Prado will discuss convex optimization solutions in the context of signal-induced and noise-induced instabilities, identifying machine learning methods that improve investment performance.
CFA Institute members can claim PL credit by providing their CFA Institute ID number when registering.
About the Speaker(s)
Marcos Lopez de Prado is the CIO of True Positive Technologies (TPT) and professor of practice at the Cornell University School of Engineering. He has over 20 years of experience developing investment strategies using machine learning algorithms and supercomputers. Professor Lopez de Prado launched TPT after selling some of his patents to AQR Capital Management, where he was a principal and the firm’s first head of machine learning. He also founded and led Guggenheim Partners’ Quantitative Investment Strategies business. Professor Lopez de Prado is a research fellow at Lawrence Berkeley National Laboratory and has published dozens of scientific articles in leading academic journals. He is a founding co-editor of the Journal of Financial Data Science, has testified before the US Congress on artificial intelligence policy, and is ranked by SSRN as the most-read author in economics. Professor Lopez de Prado has written several graduate textbooks, has an Erdős #2 according to the American Mathematical Society, and received Spain’s National Award for Academic Excellence and the Quant of the Year Award from the Journal of Portfolio Management. He earned a PhD in financial economics and a PhD in mathematical finance from Universidad Complutense de Madrid and completed his post-doctoral research at Harvard University and Cornell University.
Rani Piputri, CFA, is the head of Automated Intelligence Investing at NN Investment Partners. The Automated Intelligence Investing team focuses on extracting behavioural premiums from financial markets by implementing data-driven strategies, largely based on factor approach and artificial intelligence technologies. Previously, she worked at Aspect Capital, a London-based quantitative multi-asset solution provider. Ms. Piputri has also served as a partner and portfolio manager at Saemor Capital and as a European equity portfolio manager at Aegon Asset Management. She started her career as an investment consultant at Ortec Finance. Ms. Piputri has served as a board member of CFA Society Netherlands and is a member of the CFA Institute Annual Conference Advisory Group. She holds the CAIA designation and earned an MSc degree in financial econometrics from Erasmus University Rotterdam.