Two Easy Steps to Take Your Private Asset Returns Public
Private asset returns are typically smoothed and infrequent, reducing explainability and artificially lowering volatility.
One way to potentially improve the quality of private asset returns is to make them look and feel more like a public market proxy.
Desmoothing and interpolation features for private asset returns can reveal higher volatility, decrease autocorrelation and residual risk contribution, and increase data frequency to daily.
Excellent performance is one reason private market AUM reached all-time highs in the first half of 2021, just under $10 trillion.1 But as more investors look to diversify their portfolios with these illiquid assets, more realize a significant challenge: data.
In public markets, investors typically utilize performance that is marked-to-market, in real-time, and daily. On the other hand, private market performance is typically smoothed, marked-to-value, lagged relative to public markets, and infrequent. Smoothed private asset returns may also artificially lower volatility and reduce the explainability of risk, the latter being an important and often overlooked consequence of smoothing. For investors looking to holistically analyze a portfolio that includes private assets, especially alongside public market investments, this data limitation poses a significant hurdle.
Take a classic private real estate example such as the NCREIF Property index and a public proxy.2 Focusing on the 2009 rebound, private real estate began an upward movement multiple quarters after that of the public proxy, despite both being driven by the same movements in common risk factors, such as economic growth and interest rates.
Exhibit 1: Smoothed Private Real Estate Has Lagged Public Markets
Source: Solovis, Bloomberg. Period from Q4 1997 to Q3 2022. The NCREIF Property index represents private real estate while the MSCI US REIT index represents the public proxy.
Additionally, over this period the private real estate index exhibited a volatility of just 4.42% while the public proxy’s volatility was 21.13%. Understanding that these differences are not likely real, but rather the outcome of smoothed and infrequent private data, promotes a call to action.
How to View Private Asset Data Through a Public Lens
Public market data is frequent and marked to market. As a result, one way to potentially improve the quality of private asset returns is by making them look and feel more like a public market proxy. To accomplish this goal, Solovis Risk Pro uses two statistical methods: desmoothing and interpolation.
Below you can see the role that each method plays on the journey to viewing private asset returns with a public lens. Specifically, desmoothing aims to reduce private market performance lag and mark it to the market, while interpolation aims to increase the frequency of data.
Exhibit 2: Utilizing Desmoothing and Interpolation to Take a Public View
Source: Solovis. For illustration purposes only.
More About Desmoothing
Desmoothing private asset returns follows the econometric model by Getmansky, Lo, and Makarov (2004).3 Put simply, the approach reverse-engineers the smoothing process by examining the smoothed private asset performance and its regression-based relationship with an appropriate public market proxy.
What are some measures of success for a desmoothed return stream?
An increase in volatility: Desmoothing returns may increase volatility by adjusting them to more accurately reflect public market volatility.
A decrease in autocorrelation: High autocorrelation is a natural bias of smoothing. Decreasing the absolute magnitude of autocorrelation better reflects market reactions (by moving it closer to the autocorrelation of the public proxy) and indicates that past returns are now less similar to future returns.
A decrease in residual contribution to risk: Risk Pro’s factor lens is holistic, aiming to explain a large degree of portfolio variation. Smoothed private asset returns represent an unnatural market process that leads to larger amounts of unexplainable risk (residual). Desmoothing may reduce this unexplainable risk.
Given these three measures of potential success, Risk Pro tested its desmoothing process on private real estate, equity, buyouts, and venture capital, with results summarized below in Exhibit 3. In every instance, changes in all three measures met expectations, with volatility increasing and autocorrelation and residual risk contribution decreasing.
Exhibit 3: Results From Desmoothing Various Private Asset Indexes
Source: Solovis, Bloomberg. Real Estate analysis from Dec 1997 to Sep 2022. All other analysis from March 2001 to March 2022. Public proxies are based on Preqin’s Public Market Equivalent “Pro Tips" and are as follows: Real Estate: MSCI US REIT index (4 lags used). Private Equity: S&P 500 index (4 lags used). PE Buyout: Russell 3000 index (4 lags used). PE Venture Capital: Russell 2000 index (5 lags used).
Returning to the example from Exhibit 1, Exhibit 4 shows the output of the desmoothing feature on the private real estate time series. The orange line now rebounds at the same time as the public proxy in 2009.
Exhibit 4: Results from Desmoothing on Private Real Estate
Source: Solovis, Bloomberg. Period from Q4 1997 to Q3 2022. 4 lags used for desmoothing.
More About Interpolation
Despite the illustrated success of the desmoothing results, increasing the frequency of private asset returns is a separate task. Especially when considering consistency across data sets, it can be useful for allocators to convert their quarterly private asset returns into daily.
When interpolating, Risk Pro:
Adds a constant daily return to the chosen public proxy, such that taking the cumulative return should closely match the private asset’s return. Risk Pro then uses that new daily return stream for the private asset. Exhibit 5 provides an illustrative example of interpolation over a one week period.
Exhibit 5: Illustrative Example of Interpolation Over One Week
Source: Solovis. For illustration purposes only.
Our expectation is that the resulting, now-daily return series will approximate the original private asset’s return, but with a volatility that roughly matches the chosen public proxy.
Exhibit 6 shows the output of both desmoothing and interpolation on private real estate. The once-smoothed quarterly time series now reflects market timing in line with the public proxy from desmoothing, along with daily volatility incorporated from interpolation.
Exhibit 6: Results from Desmoothing and Interpolation on Private Real Estate
Source: Solovis, Bloomberg. Period from 10/3/1997 to 9/30/2022. 4 lags used for desmoothing.
(De)Smoother Sailing When It Comes to Private Asset Returns
Applying Risk Pro’s desmoothing technique to private asset returns reveals higher volatility while decreasing autocorrelation and residual risk contribution. Interpolation transforms infrequent data into daily data.
Risk Pro clients conducting multi-asset portfolio analytics can use these features to view private assets with a familiar public lens. This may allow investors to better understand levels, timing and drivers of risk, and may improve operational logistics when working with other daily holdings in the context of a multi-asset portfolio. When conducting portfolio analytics that include private asset returns, these two steps support a unified public lens.
Proxies are for estimation purposes only and have many inherent limitations. The methodology for calculating potential proxies was chosen based on professional judgment and will not always yield the most accurate available proxy. Proxy suggestions are not a recommendation as to any portfolio, allocation, strategy, or investment, nor an offer to purchase or sell any security. Users should conduct their own research to determine the public proxy that best fits their use case.
Contact Solovis to learn more or request a demo.
1 For example, the Preqin Private Equity Index returned 36.5% in 2021 versus the Russell 3000 at 25.7%. It is important to note that these numbers are delayed and do not capture the drawdown generally seen in markets in 2022. Aum source: read more here.
2 Public proxy is the MSCI US REIT index.
3 Getmansky, Mila, Andrew W. Lo, and Igor Makarov. "An econometric model of serial correlation and illiquidity in hedge fund returns." Journal of Financial Economics 74.3 (2004): 529-609.