Machine Learning in Finance
Abstract
Machine learning is changing our world at an accelerating pace. In this talk we will discuss the recent developments in how machine learning and artificial intelligence are changing finance, from a perspective of a technology company which is a key participant in the financial markets. We will give an overview and discuss the evolution of selected flagship Bloomberg ML and AI projects, such as sentiment analysis, question answering, social media analysis, information extraction and prediction of market impact of news stories. We will discuss practical issues in delivering production machine learning solutions to problems of finance, highlighting issues such as interpretability, privacy and nonstationarity. We will also discuss current research
directions in machine learning for finance. We will conclude with a Q&A session.
Bio
Gary is the Head of Quant Technology Strategy in the Office of the CTO at Bloomberg. Prior to taking on this role, he created and headed the company’s Machine Learning Engineering group, leading projects at the intersection of computational linguistics, machine learning and finance, such as sentiment analysis of financial news, market impact indicators, statistical text classification, social media analytics, question answering, and predictive modeling of financial
markets. Prior to joining Bloomberg in 2007, Gary had earned degrees in physics, mathematics, and computer science from Boston University. He is engaged in advisory roles with FinTech and Machine Learning startups and has worked at a variety of technology and academic organizations over the last 20 years. In addition to speaking regularly at industry and academic events around the globe, he is a member of the KDD Data Science + Journalism workshop program committee and the advisory board for the AI & Data Science in Trading conference series. He is also a co-organizer of the annual Machine Learning in Finance conference (https://www.techatbloomberg.com/machine-learning-finance-workshop-
2019/) at Columbia University.
