Modeling Private Investment Cash Flows with Market-Sensitive Periodic Growth
In this paper, IAS explores a modification to the TA model in which a series of periodic growth rates are used to model distributions and valuations.
The search for higher returns and better diversification has led many institutional investors to allocate more capital to illiquid private assets. This has come at the cost of decreasing portfolio liquidity, as private assets are not easily sold in a short period of time and may be unable to meet immediate portfolio liquidity demands. At the same time, private asset investors may encounter additional and often hard to predict liquidity demands when GPs make capital calls stemming from prior commitments. Investors need to have a strong understanding of how the liquidity characteristics of private assets impact their portfolios.
Investors are increasingly faced with the difficult choice between potentially higher returns and greater liquidity. Given market uncertainty, the risk of failing to meet liability obligations or failing to capture attractive opportunities during market dislocations further complicates the decision. What is the right amount of private assets in one’s portfolio?
Leveraging the cross-asset research capability and experience of GIC EIS and PGIM IAS, we have enhanced and expanded PGIM’s asset allocation framework (OASISTM – Optimal Asset Allocation with Illiquid Assets) to formally integrate liquidity measurement and cash flow management into a multi-asset, multi-period portfolio construction process.
Investors can use this framework to analyze how allocations to illiquid private assets (a topdown decision), in combination with their private asset commitment strategy (a bottom-up decision), affect their portfolio’s ability to respond to liquidity demands (Figure 1).
Specifically, this framework can help investors address the following key asset allocation questions:
The OASIS framework is modular (Figure 2), with each underlying component customizable by the investor.
First, it begins by simulating the returns and risk of public and private assets in a multi-asset portfolio. The simulation can incorporate an investor’s own capital market assumptions. It also allows investors to express their views on future private asset performance (relative to public assets) and their fund-selection skills which can be an important performance driver. In addition, the framework introduces cash flow modeling which is consistent with and responsive to the underlying market environment.
Second, the framework uses the investor’s portfolio structure that specifies a “waterfall” rule for sourcing liquidity: Which assets to sell to meet a liquidity demand, starting with those that are the least disruptive and costly.
Last, bringing it all together, we apply the framework and show examples of how investors can analyze their portfolio’s performance and liquidity. This flexible and customizable framework can incorporate investors’ own assumptions regarding:
This research is a collaboration between GIC TPS and PGIM IAS. The Total Portfolio Strategy division (TPS) of GIC’s Economics & Investment Strategy department (EIS) works closely with the Group Executive Committee to set the Total Portfolio’s strategic asset allocation, define factor and asset class opportunity sets and benchmarks, and target optimal internal active strategy exposure. The PGIM Institutional Advisory and Solutions (IAS) group provides objective, data-informed analysis to help Chief Investment Officers and Investment Committees manage their portfolios.