The workshop is organized by:
The Data Science Institute (DSI) at Columbia University and Bloomberg are pleased to announce the 5th annual workshop on “Machine Learning in Finance.” The workshop will be held at Columbia University under the auspices of the Financial and Business Analytics Center, one of the constituent centers in the DSI, and the Center for Financial Engineering.
Date: Friday, May 17, 2019
Location: Lerner Hall (2920 Broadway, New York, NY 10027)
The following is the 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)
Title: Redefining NYC neighborhoods using open data and machine learning
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
Online registration is now available.
Early registration is available until April 26th after which regular registration rates will apply. The early (regular) registration rates are:
Corporate delegates: $150 ($200)
Academics & Non-Columbia students*: $40 ($50)
Columbia students*: $30 ($40)
*Those availing of student rates will be required to show valid student ID at the event.
Please contact Professor Ali Hirsa for further details.
**Deadline to request a refund is Friday, May 3, 2019 at 12 PM EDT.