by William Morokoff, PhD
The market for funds of private assets has grown enormously over the last decade, with 2021 and 2022 being exceptional years. Things have cooled off a bit in the first half of 2023, but the long-term outlook is for private investments to play an increasingly important role for asset owners and asset managers. Large shifts are also underway in the debt markets, where private credit is rivaling banks as a source of funding.
Traditionally, risk analysis of private funds has relied on deal cash projections and manager assessment, making it difficult to find common risk drivers with other funds and with public equity and debt investments in a multi-asset class portfolio. While private asset returns based on a fund manager’s valuations are occasionally used for risk assessment, the risk tends to be lagged and dampened relative to the economic drivers impacting performance. In the absence of observable, market-traded returns from which volatilities and correlations with other risk factors can be estimated, it is notoriously difficult to capture the risk of private assets in a broad portfolio.
Here we outline some of the key challenges facing risk managers and some solutions to address those pain points.
Challenges
#1: Accurate Data
To accurately capture persistent relationships and determine what factors explain risk, risk models typically require a long history of validated data. While this is readily available for public market investments, private asset data history is tightly controlled and few sources have detailed deal-level cash flow and valuation data for an extensive set of funds that go back to the early days of the private markets. Such data cannot be obtained from public filings or web-scraping, but rather requires long-established relationships with a wide range of fund managers as the direct source for audited fund and deal-level data.
#2: Deriving risk from fund valuation
Traditional risk models determine risk from time series of asset value returns, with portfolio risk based on return volatility and correlation with other assets. Publicly traded asset values are derived from market consensus and respond quickly to economic and market conditions. In contrast, private fund net asset valuations (NAVs) are reported quarterly by the fund manager and tend to be quite stable, with significant adjustments occurring in the last quarter based on more in-depth audits. This leads to low-frequency, low-volatility returns that tend to lag the actual economy and performance of the fund assets. Risk models based on valuation returns require ad-hoc adjustments to address these limitations.
#3: Deriving risk from fund cash flows
A more reliable approach to assessing fund performance is based on fund cash flows, whereby distributions paid back to investors can be compared with their investments. This is the basis of various performance metrics including Total Value Paid In (TVPI), Public Market Equivalent (PME) and the internal rate of return (IRR). The challenge is to extend these measures to estimate a monthly time series of private fund category returns based on cash flows of an estimation universe of funds. One approach is described in a 2018 paper by Ang et al.[1].
As these returns are derived from verifiable cash flow data, they form a more reliable basis for linking private market performance to public market factors. An additional important point is that investor cash flows are net of fees, so the resulting performance metrics do not require adjustment for fees.
#4: Capturing total risk across public and private investments
To capture total plan risk in a portfolio with equity and fixed income investments from the public markets as well as private assets, and have a meaningful risk attribution, it is necessary to identify a consistent set of distinct factors that explain returns at a statistically significant level. While using private asset category returns as a factor can capture total risk, the risk decomposition will miss the joint economic drivers of risk shared by the public and private markets. It is therefore desirable to explain private returns as much as possible with shared factors that also impact public returns. This requires parsimonious risk factor models that can be tested to determine significance in explaining private fund returns.
#5: Finding an appropriate and timely private market index to benchmark performance
In addition to risk models, it is also valuable to have indices that track current private market performance. Many such benchmarks that are currently available rely on fund NAVs to inform index levels. Given the lag in reporting and tendency for NAVs not to reflect economic conditions in a timely fashion, an alternate approach that captures current information but also tracks historical performance accurately would be a compelling addition to the performance indicator landscape.
The CEPRES-Axioma Solution
Recently, we launched a suite of private asset risk models for use in our multi-asset class enterprise risk platform — Axioma Risk — which offer solutions for these challenges. To address the most pressing issue of quality data, we partnered with CEPRES, a leading provider of private market intelligence, data and analytics. CEPRES has collected over 25 years of verified, audited fund and deal-level data from fund managers. Their expertise and rich history of private asset data provide a solid foundation for building risk models.
The fundamental challenge of how relevant manager-reported net asset valuation data are in determining risk remains, particularly in the early years of a fund. The valuation data is useful for mature funds that have not yet liquidated, but the key to estimating private fund category returns lies in capturing fund cash flows. Leveraging the CEPRES fund cash flow data on approximately 2,500 funds selected to meet specific maturity and performance requirements, we have implemented a variation of the methodology from Ang et al[1] that is described in a recent whitepaper[2].
This methodology allows us to describe the performance of private asset funds in ten categories, from North American Buyout to Global Infrastructure, in terms of the factors from the suite of Axioma Equity Factor Risk Models, a collection of factor models calibrated to public equity returns through cross-sectional regression. Each private fund category model includes a unique set of exposures to public factors plus a private-asset latent factor. This provides a robust framework for estimating risk and risk decomposition for multi-asset class portfolios.
As the private markets grow, so does the need for accurate, insightful total plan risk analysis. Challenges persist in the areas of data, methodology and performance tracking. However, solutions do exist that can yield more accurate, transparent results for risk managers incorporating private asset positions in their total risk analysis workflow. Learn more about these private markets models here.
[1] A. Ang, B. Chen, W.N. Goetzmann and L. Phalippou, Estimating private equity returns from limited partner cash flows. The Journal of Finance 73(4) 2018: 1751-1783.
[2] W. Morokoff, Understanding private asset risk through the lens of Axioma equity factor risk models. Available here.
