The workshop is organized by:
The Data Science Institute (DSI) at Columbia University and Bloomberg are pleased to announce the 7th annual workshop on “Machine Learning in Finance.”
Due to the current pandemic situation, the 7th annual Columbia-Bloomberg Machine Learning in Finance conference, which is held under the auspices of the Financial and Business Analytics Center, one of the constituent centers in the DSI, and the Center for Financial Engineering, will be conducted on Friday, September 17th, 2021, as follows:
- Talks will be pre-recorded and broadcast via Zoom on the day of the conference.
- The organizers will introduce the speaker before each talk.
- A Q&A session (10-15 min) will be conducted live via Zoom after each talk. The organizers will moderate the Q&A sessions.
The following is the schedule (all times in EDT):
9:00 – 9:50 Samuel N. Cohen (Oxford University)
Title: Model risk and Machine Learning for Finance
9:50 – 10:40 John C. Hull (University of Toronto)
Title: The Use of Synthetic Data to Determine Capital Adequacy
10:40 – 10:50 Break
10:50 – 11:40 Tomaso Aste (University College London)
Title: Deep learning the limit order book: what machines can learn and what can we learn from them?
11:40 – 12:30 Giovanni Faonte (RDE-CoreAI, Goldman Sachs)
Title: New frontiers in deep learning and quantitative finance: an overview
12:30 – 1:30 Lunch Break
1:30 – 2:20 Brian Healy (Stanford University)
Title: An Optimal Control Strategy for Execution of Large Stock Orders Using LSTMs
2:20 – 3:00 Branka Hadji Misheva (ZHAW Zurich University of Applied Sciences)
Title: eXplainable AI in Credit Risk Management
3:00 – 3:10 Break
3:10 – 4:00 Adam Rej (Capital Fund Management)
Title: Why and how systematic strategies decay
4:00 – 4:50 Andy Almonte (Bloomberg)
Title: Improving bond trading workflow by learning to rank RFQs
4:50 – 5:00 Break
5:00 – 5:50 Joerg Osterrieder (Zurich University of Applied Sciences, University of Twente)
Title: Generative Adversarial Networks and their applications in Finance
5:50 – 6:00 Closing Remarks
Please contact Professor Ali Hirsa for further details.