Wells Fargo uses machine learning for performance attribution

Rob Mannix
@RobMannix
10 Feb 2020

Tweet
Facebook
LinkedIn
Save this article
Send to
Print this page

Quants at Wells Fargo Asset Management have built a machine learning model to explain why their strategies are winning or losing.

The project uses clustering algorithms to automate grunt work that has been traditionally given over to junior analysts – assessing day to day why some portfolios are performing differently from others.

“If you have a portfolio within a group of strategies that’s experiencing differential performance, you can feed the weights and your entire factor library into this

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 [email protected] or view our subscription options here: http://subscriptions.risk.net/subscribe

You are currently unable to print this content. Please contact [email protected] to find out more.

You are currently unable to copy this content. Please contact [email protected] to find out more.

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 [email protected]

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 [email protected]

You already have an account with us*. Sign in below to continue.