Machine learning study identifies eight risk factors in private equity

Allocators may be unwittingly concentrating their bets in private equity funds, research suggests

building-blocks-factor.jpg

A first-of-its-kind study that used machine learning to identify eight distinct risk factors in private equity has cast doubt on the diversification strategies currently employed by asset allocators.

The yet-to-be-published research suggests investors that spread allocations across conventional ‘classifications’ of private equity strategies, such as buyout, infrastructure and venture capital funds, are unknowingly concentrating their bets.

The notion of risk factors, or varying sources of

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@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe

You are currently unable to copy this content. Please contact info@risk.net 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 Risk.net? View our subscription options

Register

Want to know what’s included in our free membership? Click here

This address will be used to create your account

You need to sign in to use this feature. If you don’t have a Risk.net 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