University of Cambridge > Talks.cam > Computer Laboratory Systems Research Group Seminar > In-Network Machine Learning for Market Prediction Using Limit Order Books

  Browse A-Z

Log in

Cambridge users (raven)details Other usersdetails No account?details

Information on

Subscribing to talksdetails Finding a talkdetails Adding a talkdetails Disseminating talksdetails Help and Documentationdetails

In-Network Machine Learning for Market Prediction Using Limit Order Books

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Ryan Gibb.

Abstract: Machine learning (ML) is driving the evolution of algorithmic trading, but conflicts with the demand for fast execution speed. Although both aim to drive higher profitability, embedding more powerful ML approaches and lowering trading latencies are hard to achieve simultaneously. Offloading ML inference to programmable network devices, also called in-network ML, provides a delicate balance between the two ends of this trade-off. In this talk, I present LOBIN , providing ML-based market movement prediction using high-frequency market data feeds. LOBIN builds limit order books and conducts ML-based inference within programmable switches. This talk describes our solution to the challenging task of mapping LOB constructs and suitable ML models to a commodity switch. Compared with existing solutions, LOBIN predicts stock price movements with lower latency, higher throughput, and a minor impact on ML performance.

Bio: Xinpeng Hong is a second-year DPhil student in the Computing Infrastructure Group at the University of Oxford. His research interest lies in time-sensitive applications of in-network ML.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

Other lists

CMS Special Lectures The obesity epidemic: Discussing the global health crisis Cambridge University Women in Science Society

Other talks

The light observation set and applications CaMeL Talk: Cambridge Metabolomics and Lipidomics Competition at the front of expanding populations The formation of intermediate-mass and upper mass gap black holes in dense star clusters with up to 1 million stars Epigenome Function: from molecular mechanisms to intergenerational inheritance When the chips are down… how Meteor Inkjet beat the 2022 chip supply crisis
 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity