Cash Flow Forecasting for Private Equity Fund Allocators

Navigating forward-looking PE commitments, allocations, and cash flows has become a focal point for LPs. Stalled exits have heightened the pressure on many institutions’ liability obligations, causing them to grapple with cash constraints. Simultaneously, the denominator effect has left a considerable number of LPs still dealing with overallocation concerns. In part three of our asset allocation series, we explore how LPs can use commitment schedules and cash flow forecasting models to manage cash flow challenges posed by current market dynamics, determine an optimal forward-looking PE allocation aligned with their objectives, and chart a clear path to reach it.

Managing Private Equity Fund Cash Flows

Unlike traditional asset classes, private equity funds call down and distribute committed capital over several years rather than a one-time asset purchase or sale, which surfaces unique cash flow considerations. Capital contributions tend to peak in the early fund years, with middle years witnessing increased distributions as investments mature. Naturally, later years see a gradual decline in distributions due to fewer remaining investments to be harvested.

While this general level of predictability in cash flows exists, the ultimate schedule depends on the fund manager’s pace of sourcing investment and exit opportunities, along with various other factors. For example, intrinsic fund characteristics such as size, strategy, and available capital heavily influence capital call and distribution profiles. Funds with high levels of dry powder tend to make larger capital calls. Larger pools of capital are more difficult to deploy, meaning large funds tend to call capital down at a slower rate than their smaller counterparts. Economic conditions can also distort cash flow patterns, as witnessed in a presently subdued exit environment, leading to a significant slowdown in distributions.

This variability in cash flows becomes a difficult needle to thread for LPs — they must have adequate cash on hand to fund not just capital calls, but also their own cash flow needs. Yet, parking it in liquid, low-return asset classes can compromise returns. Further, liquidity risks arise if LPs don’t properly plan for potential outsized capital calls or align forecasted distributions with liabilities. For example, while PE funds typically draw approximately 5% of committed capital per quarter during the investment period, a capital call totaling 18-20% of the commitment size would not be too much of an anomaly.

Private Equity Cash Flow Forecasting Modeling

Cash flow forecasting models, including the well-known “Yale Model,” created by Dean Takahashi and Seth Alexander, aim to help LPs predict accurate forecasts of cash flow and NAV profiles. Swensen’s non-probabilistic model uses simple, theoretical parameters with the ability to adjust expected forecasts for specific funds by manipulating inputs, such as the “bow” factor, and assuming several key assumptions on contribution, distribution, and NAV behavior:

  • Drawing on trends described above regarding capital call concentration in the early years of a fund, capital calls are calculated by multiplying assumed contribution rates by the remaining capital commitment.
  • Recognizing that the size and timing of distributions are based on the performance of the fund, the distribution formula is based on a rate of distribution along with the NAV of a fund.
  • Future NAV values of a current fund are calculated by multiplying the previous year’s NAV by the projected growth rate, adding contributions, and subtracting distributions, reflecting the idea that NAVs are influenced by three variables: investment performance, capital inflows, and capital outflows.

Each strategy, manager, and market result in differing cash flow dynamics, challenging LPs wishing to better predict what their portfolio may look like over time. The below example highlights this, showing variability between buyout and venture cash flows from equal $100M commitments that an LP must take into consideration.

Achieving a Target PE Allocation and Determining the Associated Commitment Schedule

Apart from considering the cash flow of an LP’s current commitments and funds, it’s crucial to model or determine the size of future commitments needed to achieve or sustain a private equity allocation — along with those future commitments’ associated cash flow profiles. However, establishing a forward-looking commitment schedule is complicated by factors like determining the appropriate commitment size for reaching and maintaining a target, diversifying across vintage years, and aligning allocation goals with liabilities and investment objectives.

Given the nature of closed-end fund cash flows, achieving and maintaining a private market allocation of a certain size requires more thought than that of publicly traded assets, as it involves a multi-year process with many variables at play. The cyclical cash flows in PE funds complicate allocation management, as the NAV of a private equity portfolio is in constant flux. Distributions, for instance, inherently decrease overall portfolio exposure by lowering the total NAV.

Even when an LP determines a commitment size, the subsequent years can easily play out differently than anticipated. GPs assume responsibility for capital calls, value creation, and generating returns, with their performance playing a pivotal role in shaping LP allocations. The wide dispersion of private market returns complicates allocation targeting and commitment planning, as overperforming funds with higher NAV returns — relative to the commitment size — may inflate the LP’s overall private equity allocation. Conversely, underperforming funds in the bottom quartile, with returns lower than anticipated, can lead to LPs falling short of their targets.

Commitment Schedule Modeling

Creating a model to assess potential allocation and cash flow implications of future commitments and layering those forecasts onto the existing cash flow profiles of “in-ground” funds aids LPs in optimizing allocation management.

Commitment planning forecasting – for LPs with a diverse portfolio of asset classes – largely hinges on NAV behavior over time, as the maintenance of a specific PE allocation relies on the NAV of the PE portfolio as a proportion of the entire portfolio. Hence, LPs need to establish a commitment schedule that ensures the desired NAV trajectory aligns with the targeted proportion of PE value relative to their entire portfolio over time while factoring in their desired time period to reach their desired allocation.

With a commitment pacing schedule generated, LPs can then circle back and recalibrate the expected cash flow profile of the overall private fund portfolio over a longer time horizon that incorporates future commitments.

Consider the forward-looking allocation targets of the Alaska Permanent Fund Corporation (APFC) and MainePERs, discussed in our prior article in this series. Both institutions ended 2023 overallocated to private equity — by 3 and 7 percentage points, respectively — causing both to shift their PE targets over the next several years.

In aligning future commitments with refreshed targets, MainePERs, and the APFC can benefit from commitment schedule modeling for empirical insights on check sizes required to attain their PE target allocations.

How Chronograph Helps LPs Optimize Cash Flow Forecasting and Commitment Pacing

For LPs with hundreds or thousands of commitments, generating cash flow forecasting models on a one-off or recurring basis has traditionally been difficult to implement due to manual data compilation and aggregation. Through using Chronograph’s Excel plug-in xConnect, LPs can seamlessly pull in every commitment and cash flow since inception, populating models to forecast the cash flows of their in-ground funds across asset classes.

Once these forecasts are generated, LPs can use a commitment pacing model in xConnect and customize it for institutional methodologies and assumptions. This facilitates the means to map out future commitment dynamics in order to align with desired targets and gain visibility into how variability in NAV behavior, capital calls, and distributions may impact the cash flow profile of their PE commitments.

The below xConnect powered cash flow forecasting model illustrates how to sensitize future allocations to forecast calls and distributions, understand pacing within the broader portfolio, and refresh data in real-time.

Request a demo to learn how LPs use Chronograph to optimize their PE allocation and cash flow management.

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