Deep Learning and Quantitative Finance

Of special interest, plan to attend:  

March 16 Talk, "Deep Learning for Sequences in Quantitative Finance" with David Kriegman

Register now (and more info)    for the next free ACM TechTalk, "Deep Learning for Sequences in Quantitative Finance," presented on Wednesday, March 16 at 12:00 PM ET/17:00 PM UTC by David Kriegman, Professor of Computer Science & Engineering at the University of California, San Diego. Andrew Rosenfeld, Senior Vice President at Two Sigma, will moderate the questions and answers session following the talk.

Leave your comments and questions with our speaker now and any time before the live event on ACM's Discourse Page. And check out the page after the webcast for extended discussion with your peers in the computing community, as well as further resources on deep learning, machine learning, and more.

(If you'd like to attend but can't make it to the virtual event, you still need to register to receive a recording of the TechTalk when it becomes available.)

Note: You can stream this and all ACM TechTalks on your mobile device, including smartphones and tablets.

The quantitative investment process can be viewed as one that takes in raw data at one end and executes trades that buy and sell financial instruments at the other end. The process naturally decomposes into steps of feature extraction, forecasting the returns of individual instruments, portfolio allocation to decide quantities to trade, and trading execution. Many of the steps in this process are readily expressed as machine learning problems that can be addressed using deep learning sequence methods. This talk will provide an overview of this pipeline and deep learning for sequences. No background knowledge in finance or deep learning is required. .... '