Building and Maintaining a Desired Exposure to Private Markets
Commitment Pacing, Cash Flow Modeling, and Beyond
A good commitment pacing plan is often the lynchpin of a private capital program and can account for much of the dispersion in performance across LPs. CIOs may ask for a systematic way to pace new commitments that will, in the long run, reach an equilibrium in which several objectives are satisfied including stable NAV, cash flow balancing, portfolio liquidity, and minimum disruption to the rest of the portfolio due to capital calls. We describe and simulate a simple commitment pacing plan that is generic, flexible and can be tailored to meet many situations.
Figure 1 shows that a simple private capital portfolio consists of three distinct pools of capital: Called capital that remains “in the ground” also known as the NAV; Committed, but uncalled capital, which is the capital that is committed but has not yet been called; and Uncommitted capital, which is a fraction of the capital initially allocated to private assets plus distributions received from prior commitments that have yet to be re-committed.
A simple strategy is to commit a fixed fraction (labeled the “commitment strategy”) of uncommitted capital every period. To see how this strategy behaves we link public and private markets using Takahashi and Alexander’s cash flow model and simulate the portfolio shown in Figure 1 over a horizon of 100 quarters. We run this simulation for various commitment strategies and plot results in Figure 2 and Figure 3.
Figure 2 shows the relationship between the fixed fraction, or commitment strategy, and the average steady-state NAV% maintained in the simulated portfolio. The relationship that emerges in Figure 2 fits an investor’s intuition as a higher fraction should lead to higher NAV%, at least eventually. In fact, we show that for higher fractions it takes longer to reach a steady state. In the case of the 100% commitment strategy it could take more than 20y for the NAV% and net cash flow to settle down.
The simulation generates performance data across number of sample portfolios which are summarized in Figure 3. We use terminal wealth analysis to compute the mean and volatility of periodic returns using all 5,000 paths. One can clearly see that one’s intuition about buyout alpha is confirmed in the figure’s first facet which plots commitment strategy against horizon returns. The higher the fixed fraction the more is NAV%, and the higher are terminal wealth and annualized horizon returns. Volatility, however, shows no clear pattern because we assume the risk of investing in buyouts is similar to that of public markets.
A highlight of Figure 3 is the relationship between risk-adjusted returns and commitment strategy. This figure combines three different aspects of private capital investing: risk, return, and liquidity. Assuming a 4% private market premium in buyout investments, what is the tradeoff between risk-adjusted performance and the commitment fraction? We observe that there is no added advantage of committing more than 25-30% of uncommitted capital to new funds every quarter as it results in no noticeable gain in terms of risk-adjusted performance although it may have implications in terms of portfolio liquidity.
We present a flexible commitment pacing framework that can be tailored to meet an investor’s objective of building and maintaining a target NAV% of their portfolio. Using this framework, we present the tradeoff between risk-adjusted performance and liquidity. Our computational results conform to investors’ intuitive understanding of these tradeoffs.