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
Quants look to language models to predict market impact
Oxford-Man Institute says LLM-type engine that ‘reads’ order-book messages could help improve execution
The IMD Wrap: Talkin’ ’bout my generation
As a Gen-Xer, Max tells GenAI to get off his lawn—after it's mowed it, watered it and trimmed the shrubs so he can sit back and enjoy it.
This Week: Delta Capita/SSimple, BNY Mellon, DTCC, Broadridge, and more
A summary of the latest financial technology news.
Waters Wavelength Podcast: The issue with corporate actions
Yogita Mehta from SIX joins to discuss the biggest challenges firms face when dealing with corporate actions.
LSEG-Microsoft products on track for 2024 release
The exchange’s to-do list includes embedding its data, analytics, and workflows in the Microsoft Teams and productivity suite.
Data catalog competition heats up as spending cools
Data catalogs represent a big step toward a shopping experience in the style of Amazon.com or iTunes for market data management and procurement. Here, we take a look at the key players in this space, old and new.
Harnessing generative AI to address security settlement challenges
A new paper from IBM researchers explores settlement challenges and looks at how generative AI can, among other things, identify the underlying cause of an issue and rectify the errors.
The causal AI wave could be the next to hit
As LLMs and generative AI grab headlines, another AI subset is gaining ground—and it might solve what generative AI can’t.
