JP Morgan pulls plug on deep learning model for FX algos
The bank has turned to less complex models that are easier to explain to clients.
JP Morgan has phased out a model that leverages machine learning technology for foreign exchange algorithmic execution, citing issues with data interpretation and the complexity involved.
The US bank had implemented what it calls a deep neural network for algo execution (DNA), which uses a machine learning framework to optimize order placement and execution styles to minimize market impact.
Launched in 2019, JP Morgan said at the time that the move would replicate reinforcement learning
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: http://subscriptions.waterstechnology.com/subscribe
You are currently unable to print this content. Please contact info@waterstechnology.com to find out more.
You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@waterstechnology.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@waterstechnology.com
More on Emerging Technologies
This Week: ION/LuxSE, BNY Mellon, Nasdaq, and more
A summary of the latest financial technology news.
Nasdaq to market new options strike listing tech to other exchanges
The exchange operator is experimenting with emerging technologies to determine which options strike prices belong in a crowded market, with hopes to sell the tech to its peers.
Former Goldman analyst aims to blend GenAI and synthetic data with start-up
Synthera.ai is taking a novel approach to calculating risk. While promising, industry observers are skeptical.
Waters Wavelength Podcast: Bloomberg’s Tony McManus
Tony McManus, global head of enterprise data division at Bloomberg, joins the podcast to talk about the importance of data in the context of AI and GenAI.
Devil’s Bargain: Closed architecture systems will derail AI ambitions
Rob Flatley explains why closed-off systems will fall flat when it comes to AI adoption.
This Week: First Trust/Bloomberg/New Constructs, Cboe/Metaurus, LTX/MultiLynq, and more
A summary of the latest financial technology news.
Waters Wavelength Podcast: S&P’s CTO on AI, data, and the future of datacenters
Frank Tarsillo, CTO at S&P Global Market Intelligence, joins the podcast to discuss the firm’s approach to AI, the importance of data, and what might be in store for datacenters in the coming years.
BMO’s cloud migration strategy eases AI adoption
The Canadian bank is embracing a more digital future as its cloud strategy makes gains and it looks to both traditional machine learning and generative AI for further augmentation.
Most read
- Waters Wavelength Podcast: Bloomberg’s Tony McManus
- IMD & IRD Awards 2024: All the winners
- Waters Wavelength Podcast: S&P’s CTO on AI, data, and the future of datacenters