UBS & CFEM AI, Data & Analytics Speaker Series with Ernest Chan (Predictnow.ai)

Description

The next guest speaker in the UBS & CFEM Seminar Series is Ernest Chan! Ernest (Ernie) Chan is the founder and CEO of Predictnow.ai, and he will discuss "How to Use Machine Learning for Optimization." Join us on Tuesday, February 28th, from 5:30pm to 6:30pm ET for a lively and educational talk!

This webinar is free and open to all. Registration is required (please RSVP here). You will receive the webinar link and dial-in info upon registration (the confirmation email will come from no-reply@zoom.us). 

Abstract:  Conditional Portfolio Optimization is a portfolio optimization technique that adapts to market regimes via machine learning. Traditional portfolio optimization methods take summary statistics of historical constituent returns as input and produce a portfolio that was optimal in the past, but may not be optimal going forward. Machine learning can condition the optimization on a large number of market features and propose a portfolio that is currently optimal. We call this Conditional Portfolio Optimization (CPO). Applications on portfolios in vastly different markets suggest that CPO can outperform traditional optimization methods under varying market regimes.

Speaker Bio:  Ernest Chan (Ernie) is the founder and CEO of Predictnow.ai, a machine learning SaaS. He started his career as a machine learning researcher at IBM's T.J. Watson Research Center's Human Language Technologies group, which produced some of the best-known quant fund managers. He later joined Morgan Stanley's Data Mining and Artificial Intelligence group. He is the founder and non-executive chairman of QTS Capital Management, a quantitative CPO/CTA. He received his Ph.D. in physics from Cornell University and his B.Sc. in physics from the University of Toronto.