JP Morgan is testing quantum deep hedging

Researchers say the timeline has shortened for the use of models in production.

Quantum computing could nearly double the effectiveness of machine learning-based hedging strategies, according to researchers at JP Morgan.

The US bank worked with quantum software company QC Ware to complete a study of quantum deep hedging detailed in a new paper, Quantum Deep Hedging, released March 30.

“Now we actually have a solution that gives us confidence that in the future this work will be usable in production,” says Marco Pistoia, head of global technology applied research at JP

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 copy this content. Please contact info@waterstechnology.com to find out more.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Waterstechnology? View our subscription options

Interoperability is not AI

Dan Schleifer, co-founder of Interop.io, explains how desktop interoperability underpins new AI developments.

You need to sign in to use this feature. If you don’t have a WatersTechnology account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here