Attracted by the potential for higher returns compared to public markets, a number of asset owners have progressively increased allocations to private market investments.
Despite this global trend, private assets continue to pose challenges for asset owners looking to use attribution models to improve their investment decision making process. Traditional attribution models can fail to provide meaningful analytics due to challenges with illiquidity, valuations, and benchmarking.
Can performance measurement and attribution frameworks be adapted to address these challenges?
Join us for this webinar, where Richard Griffiths and Arwel Lincoln from our Investment Performance Team will discuss the key considerations of private assets from a performance analysis perspective, including how their landscape affects performance metrics and fund-level allocations. He will explore:
- The challenges posed by illiquidity, and how data limitations further intensify them
- Suitable benchmarks and attribution models and how these differ from standard approaches
- How the results can be effectively integrated with public assets on total fund-level
Webinar details
| Date: | Wednesday October 8, 2025 |
| Time: | Session one - 9:00am – 9:30am (CEST) |
| (Two options available) |
Session two – 3:30pm – 4:00pm (CEST) |
Explore additional webinars on private asset investment decisions
Learn how to address private asset challenges across the investment decision-making process in other sessions from our five-part Private Assets in focus: Navigating investment decisions webinar series.
Topics include:
Investing in private assets through a climate change lens
- Understand the key climate considerations of private assets, across both challenges and opportunities
Understanding private assets in the institutional investment landscape
- Gain a deeper understanding of the risk/return profile of private assets, as well as key considerations when designing investment strategies
Private asset modelling to support strategic asset allocation
- Explore more effective approaches to modelling private asset classes in support of strategic asset allocation (SAA) decisions
Harnessing scenario-based machine learning (SBML) for private asset investment decisions
- Discover how this innovative approach can be leveraged to optimize diverse portfolios aiming to increase their private asset allocations
Contact
Richard Griffiths
Senior Consultant Investment Performance