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Overview
In recent years the topics of Data Science, Artificial Intelligence, Machine Learning, and Big Data have become increasingly popular. This growth has been fueled by the collection and availability of new data; increasing processing power and storage, and the open-source movement continue to make tools more widely available. As a result, we have already witnessed profound changes to how we work, rest, and play… and this trend will only continue. How has the world of finance, and investment managers in particular, been impacted by this trend? Join us to explore what Data Science means for finance professionals.
Presented in conjunction with The Society of Quantitative Analysts (SQA) and the Quantitative Investing Group.
Agenda
8:30 AM | REGISTRATION
8:55 AM | INTRODUCTION
9:00 AM | NEW NEWS IS BAD NEWS
Speaker
Harry Mamaysky, Professor of Professional Practice, Columbia Business School
Discussant
TBD
10:00 AM | DOES OVERNIGHT NEWS EXPLAIN OVERNIGHT RETURNS?
Speaker
Paul Glasserman, Professor, Columbia Business School
Discussant
Yin Luo, CFA, CPA, CGMA, Vice Chairman, Wolfe Research
11:00 AM | COFFEE BREAK
11:15 AM | A SURVEY ON QUANTUM MACHINE LEARNING: CURRENT TRENDS, CHALLENGES, OPPORTUNITIES, AND THE ROAD AHEAD
Speaker
Alberto Marchisio, Research Group Leader, New York University (Abu Dhabi)
Discussant
TBD
12:15 PM | LUNCH
1:15 PM | A UNIFIED FRAMEWORK FOR FAST LARGE-SCALE PORTFOLIO OPTIMIZATION (NEW RESULTS)
Speaker
TBD
Discussant
Reha Tutuncu, Head of Portfolio Research, Point72 Asset Management
2:15 PM | LEVERAGING ALTERNATIVE DATA AND DATA SCIENCE
Speaker
Irene Aldridge, CEO, AbleMarkets
Jonathan Berkow, CFA, Director of Quant and Data Science, Alliance Bernstein
Dan Duggan, PhD, VP, Goldman Sachs Investment Research, Goldman Sachs & Co. LLC
Sameer Gupta, Head of Generative AI Shared Services & Data Engineering, Point72
Discussant
Ingrid Tierens, PhD, CFA, Head of Data Strategy, Global Investment Research (GIR), Goldman Sachs & Co. LLC
3:15 PM | COFFEE BREAK
3:30 PM | ASSESSING LABOR MARKET INEQUALITY & DISCRIMINATION IN FINANCE THROUGH BIG DATA
Speaker
Kriste Krstovski, Associate Research Scientist & Adjunct Professor, Columbia Business School
Discussant
Carole Crawford, CFA, NACD.DC, Managing Partner, fincap360
4:30 PM | NETWORKING RECEPTION
Additional Details
Learning Outcomes
- Gain an understanding of various big data techniques;
- Learn new algorithms for investment analysis;
- Review how data science is applied in various industries.
Who would be interested in this event:
Analysts, Portfolio Managers and other practitioners interested in how machine learning, artificial intelligence, and other data science techniques can be used in financial and other sectors.