Boxed lunches will be provided. There will also be regular coffee breaks throughout the day and a wine and cheese reception after the event.
The Center for Financial Engineering and the Financial Analytics Center at Columbia University
Organizer of Machine Learning in Finance Workshop 2019
The Center for Financial Engineering is an interdisciplinary research center established in 2007 to encourage research on financial engineering and mathematical modeling in finance. It aims at fostering research collaboration among Columbia faculty, graduate students and affiliates, facilitating their contacts with financial institutions and corporations and enhancing the visibility of Columbia as a center for research and innovation in financial engineering.
The Center’s research activities deal with the pricing and hedging of derivative securities, the statistical modeling of financial markets, computational methods in finance, risk management, asset allocation and portfolio optimization.
The Financial Analytics Center is one of the key centers at the Data Sciene Institute at Columbia University. It brings together expertise in finance theory, machine learning, statistics, signal processing, operations, and natural language processing, and supports collaborations with an appropriately trained student body as well as with the financial industry.
The following is a tentative schedule.
8:15 – 9:00 Registration
9:00 – 9:15 Introduction
9:15 – 9:55 Kay Giesecke (Stanford University, Advanced Financial Technologies Laboratory)
Title: Towards Explainable AI: Significance Tests for Neural Networks
9:55 – 10:35 Simona Abis (Columbia Business School)
Title: The Informational Content of Mutual Fund Prospectuses
10:35 – 11:15 Yange Leng (Massachusetts Institute of Technology)
Title: Learning strategic interaction from individual action: A game-theoretic approach
11:15 – 11:45 Break
11:45 – 12:25 Martin Haugh (Imperial College)
Title: How to Play Fantasy Sports Strategically (and Win)
12:25 – 13:05 Peter Decrem (Citi)
Title: Using AI Machine Learning to Explore Large Streaming Financial Data Sets to Improve Market Making
13:05 – 14:25 Lunch (A boxed lunch will be provided)
14:25 – 15:05 Darren Vengroff (Two-Sigma)
15:05 – 15:45 Amanda Stent (Bloomberg)
Title: Text Analytics in Finance
15:45 – 16:10 Break
16:10 – 16:50 Rama Cont (Oxford)
Title: Forecasting price moves from order flow: perspectives from Deep Learning
17:00 Wine reception – Lerner North Lobby
Data Science Institute