ROCC & MOCC II: Optimising capital deployment in Private Markets

In our first publication, we introduced a holistic approach to the evaluation of Private Market funds using the concepts of Return on Committed Capital (ROCC) and Multiple on Committed Capital (MOCC). The paper delved into theory, calculations, drawbacks, considerations, and included a comprehensive guide to understanding these metrics. We invite you to explore it here ROCC & MOCC: Unveiling an Alternative Approach to Private Market Return Analysis.

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This new piece aims to highlight the transformative benefits of overcommitment strategies as well as the utilization of ‘accelerators’ in the portfolio construction within Private Markets. The use of these strategies can improve the efficiency in deployment and thereby the ROCC and MOCC by increasing the invested capital within an Alternatives portfolio. Building on that foundational concept, the article aims to demonstrate the practical application of the Klarphos approach to Private Markets portfolio construction by presenting real examples across alternative asset classes.

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Introduction

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In this second article on ROCC and MOCC, we further explore strategies that enhance deployment efficiency and thereby elevate ROCC and MOCC for Private Market investments. We  begin by briefly revisiting key concepts of the ancillary measures and examining their application across different asset classes. Subsequently, we look at portfolio construction techniques. Through this analysis, we demonstrate how effective implementation can improve deployment efficiency and consequently boost these important KPIs.

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The effective range in a nutshell

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ROCC and MOCC measurements are straightforward to implement across Private Market asset classes. To fully grasp their application and scope, it's crucial to examine unused commitments, as discussed in our previous publication. Our recent analysis provided insights into the pattern of capital contributions, measured as a percentage of total commitments within a specific period and target exposure. Close study of these patterns reveals that the concept of an ‘effective range’ of capital utilization applies to nearly the entirety of the Private Markets, as nearly all funds do not call 100% of committed capital. In fact, conventional drawdown funds often conclude with some non-negligible uncalled commitments – i.e., typically a maximum of only 80-95% of capital may be fully utilized by the end of a fund’s life. This underutilisation leads to an (expensive!) opportunity cost, which is especially prevalent in Private Market funds employing the common drawdown-style, closed-end structure. This dynamic renders it imperative to use ROCC and MOCC to measure, and subsequently optimise, efficiency in capital deployment.

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It is also important to note that Evergreen funds, Secondaries, and late Primaries can improve capital deployment. When integrated into a portfolio, they can not only provide diversification but also significantly enhance performance. The final section of our study will offer an in-depth analysis of how these funds are applied within a portfolio construction framework and their impact on ancillary metrics.

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A comparative guide for ROCC & MOCC

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In Table 1, we present investments across the four main categories of Private Markets. For each of the displayed asset classes, our team selected actual individual funds, however it is important to note that these vehicles were not chosen to be representative of ROCC/MOCC characteristics of their respective vertical within Alternatives but rather to showcase an application of the analysis of these KPIs and highlight that these dynamics are at play across all categories of Private Markets.  

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Direct comparison of these classes is challenging due to their different investment horizons, cash flow lifecycles, and exposures. For example, the lifespan of a Private Debt fund in Direct Lending ranges from 4 to 6 years, while a Private Equity Buyout fund averages about 10 years. Comparing funds with similar characteristics, such as vintage, unused commitment, and strategy is essential to conduct a meaningful analysis.

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Despite these challenges, Table 1 offers valuable insights. It is sorted by unused capital as a percentage of total commitments, with a higher percentage in all cases leading to a more significant deviation from traditional performance measures. This acts as a common theme among asset classes, given the absence of recallability or recycling. The Internal Rate of Return (IRR) typically exceeds the ROCC by approximately 50% or more. Similarly, when examining Total Value to Paid-In Capital (TVPI) and MOCC, we see comparable patterns.

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ROCC starts to align with IRR, and MOCC with TVPI once funds are close to being fully deployed. Importantly, this does not offer a like-for-like comparison with other asset classes, as the selected Private Debt fund has the lowest disparity, bearing a lower cost of opportunity. In conclusion, considering time effect from commitment to deployment and the denominator effect from committed but uncalled capital, the figures are significantly lower due to a much less efficient use of capital.

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Table 1: Primary Private Markets funds performance sorted by percentage of uncalled capital

_{Source: Selected fund cash flow data for calculations were obtained from Preqin, Klarphos, as of Q1 2024. Data extracted on 31 May, 2024.}

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‍Effective portfolio construction strategies can improve MOCC and ROCC

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The core drivers of value in the process of portfolio construction are the Strategic Asset Allocation (SAA) and its implementation.

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Properly implementing the SAA is crucial for enhancing deployment efficiency and, consequently, improving ROCC and MOCC metrics. If a portfolio of funds is managed based solely through a lens of the traditional TVPI-IRR, then the optimisation will result in a suboptimal solution that fails to fully invest the capital. When creating a portfolio, the speed of deployment and maintaining sustained exposure are critically important and can be effectively measured by ROCC and MOCC, with higher values indicating better performance. Improved portfolio deployment can be achieved using three techniques, (the last of which is a combination of the first two):

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I. Overcommitment strategy

Given that empirical evidence is clear that individual fund managers of closed-end drawdown vehicles almost never call more than 90% of capital, a multi-manager allocator to funds may take advantage of this and achieve improved deployment by committing more than what is intended to be invested (i.e., overcommit). In doing so, invested capital will converge towards 100% rather than 80-95%, and this also will occur more swiftly. As a result, the portfolio will need to assume a lower level of risk to achieve the same multiple.

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The first simulation below illustrates the desired exposure achieved through an overcommitment approach with annual commitments (light blue area) versus a suboptimal strategy (pink area).

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Chart 1: Single Primary closed-end funds and suboptimal implementation versus Private Debt Efficient Deployment Portfolio

_{Source: Klarphos 31 May, 2024. The Journal of Alternative Investments Vol. 23, Issue 2; The Journal of Private Equity Vol. 18, Issue 2.}

_{OCR: The total amount of signed commitment divided by desired exposure target.}

_{PD EDP: The simulation consists of 11 investments in Private Debt Direct Lending with three years investing plus three years harvesting assumption. The overcommitment ceiling of 115.8%. Capital return risks are categorised into regular, moderate, and aggressive scenarios, with returns distributed equally each quarter during the harvesting period. The couponing is assumed to be the same among funds and there is no recallability or recycling.}

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The general strategy shifts from focusing solely on making individual allocations to a more comprehensive commitment optimisation strategy. Effective management of the overcommitment ratio (OCR) enables full utilisation of the committed capital. In other words, due to the nature of drawdown funds, we commit more than 100% to ensure the full invested capital.

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For some Alternatives asset classes, it is suggested that an OCR of between approximately 105% and 130% is advisable to achieve a fully deployed strategy that invests in multiple funds annually. The portfolio simulation shown, the Efficient Deployment Portfolio (EDP), which incorporated an overcommitment strategy featuring an OCR of 115.8% and a real deployment of 102%, was conducted using Private Debt (PD) funds over a 10-year investment horizon and then compared to a series of closed-funds with the same characteristics.

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Chart 2: PD EDP versus a closed-end Primary fund

_{Source: The Private Debt closed-end fund cash flow data for calculations were obtained from Preqin. Data extracted on 31 May, 2024.}

_{Performance measures for the Private Debt Enhanced Efficient Deployment Portfolio calculated by Klarphos and data based on (2) simulation.}‍

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Quite interestingly, the PD EDP achieved a MOCC of 1.08, comparable to that of the closed-end Primary fund, despite its IRR of 7.7% being nearly 50% lower than that of the closed-end Primary fund. This indicates that the closed-end Primary fund must assume significantly greater risk to achieve the same deployment efficiency.

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II. Quicker deployment via ‘accelerators’

The use of an accelerator such as an Evergreen fund, Secondaries or Late Primaries allows faster deployment and a better ROCC and MOCC. These accelerators have an immediate deployment or at least significantly higher than a Primary. Chart 3 allows us to gain a better understanding.

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Chart 3: Accelerators cash flow cycle versus Primary closed-end funds (for illustrative purposes)

_{Source: Klarphos 31 May, 2024.}

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An Evergreen fund is a type of investment fund that operates with a perpetual or open-ended structure, rather than having a fixed term. This structure allows the fund to operate indefinitely, continuously offering and redeeming its shares based on investor demand. Some benefits and drawbacks are:

The use of Secondaries and late-stage Primary funds can offer similar benefits and diversification due to differences in underlying assets and/or life stages. A Secondary transaction involves the sale of an existing commitment in a fund that is already at an advanced stage (i.e., several years into its investment period or later). For example, a Limited Partner (LP) might sell their part to an external buyer. Consequently, the new LP avoids the initial commitment phase where capital is not yet drawn. Instead, the LP starts with a significant portion of the commitment already called, and enjoys a shorter remaining fund life, often with a rate of return that is more stable and predictable as the fund has already built a well-developed and well-diversified portfolio of investments. Late-stage Primary funds function similarly, but instead of buying an existing stake from another LP, investors enter the Primary fund at a later closing date when the GP has deployed some, and in certain instances a significant portion, of capital. Although there is invariably a ‘catch-up’ fee charged to LPs entering such a late-stage Primary fund, the opportunity cost is generally measured at a modest rate of return which is more often than not eclipsed by the investments already made.

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III. Overcommitment strategy in concert with ‘accelerators’

Fund investors can earn extra efficiency in deployment by using both an overcommitment strategy and accelerators. For this final simulation, we examine an Evergreen fund to capture the ‘accelerator’ concept, and in the same manner as we did in the first strategy alternative, assess this strategy's performance together with overcommitment relative to straightforward allocations in real examples of Private Debt funds.

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Chart 4: Private Debt Enhanced Efficient Deployment Portfolio Breakdown as a percentage of € invested

_{Source: Klarphos 31 May, 2024.}

_{The simulation of the Enhanced Efficient Deployed Fund consists of four distinct investment strategies across 33 funds, with an overcommitment ceiling of 115.8% of the fund's original size. It allocates 36.4% to Direct Lending across 11 funds with a 3-year investing and harvesting cycle, 22.7% to Opportunistic Credit across 12 funds with a 4-year cycle, 22.7% to Asset-Based Lending across 11 funds with a 2-year cycle, and 18.2% to a perpetual Evergreen fund. The investment strategies diverge notably in their cash flow lifecycles, tailored to their specific capital appreciation and coupon rates, ensuring the funds' returns reflect the unique nature of each strategy. Capital return risks are categorised into regular, moderate, and aggressive scenarios, with returns distributed equally during the harvesting period. The couponing is assumed to be the same among funds of the same strategy and there is no recallability or recycling.}

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To construct the portfolio simulation, we overcommitted at a rate of 115.5% on a portfolio basis and invested annually in a total of 33 funds, including an Evergreen fund (18.2% of the total portfolio), over a 10-year investment horizon, with real deployment resulting in nearly fully invested capital.

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‍Chart 5: Private Debt Enhanced Efficient Deployment Portfolio Strategy versus closed-end Primary funds

_{Source: Private Debt closed-end fund cash flow data for calculations were obtained from Preqin. Data extracted on 31 May, 2024.}

_{Performance measures for the Private Debt Enhanced Efficient Deployment Portfolio calculated by Klarphos data based on (4) simulation.}

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When a multi-manager fund investor employs overcommitment techniques and ‘accelerators’ together, the result is an improvement in the overall risk-adjusted performance. Allocators using traditional techniques, by contrast, achieve  a similar MOCC  but require significantly more return on invested capital (and presumably more risk) to achieve this result – i.e., an IRR 30 to 50% higher than for the efficiently deployed investor.

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Key takeaways

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ROCC and MOCC can be effectively applied across the entire spectrum of Private Markets, provided they are compared on a like-for-like basis.

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Understanding the use and timing of commitments is imperative. With better knowledge about GP behavior in deploying capital, a fund investor may be more efficient by appropriately overcommitting and strategically using secondaries and late-stage Primaries which, in turn, will make a higher MOCC and ROCC achievable. If distribution recallability or recycling dynamics are present, an allocator may need to analyze further to gain insights. Consult our first paper for a deeper understanding: 'ROCC & MOCC: Unveiling an Alternative Approach to Private Market Return Analysis'.

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We have targeted and enhanced the MOCC, improved the efficiency in deployment and, consequently reduced the risk needed through the proper implementation of the Strategic Asset Allocation (SAA). This efficiency was achieved using two portfolio construction strategies, individually or in combination:

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• To achieve full investment on a portfolio basis, the use of an overcommitment technique within a 105-130% OCR is recommended.

• To enhance efficiency in deployment, the use of an accelerator within a portfolio is recommended: Evergreen, Secondaries or late-stage Primaries funds.

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Ideally, use both. These strategies significantly improve deployment efficiency and enhance portfolio optimal exposure. Higher MOCC values reduce risk exposure, as reflected by a lower required Internal Rate of Return (IRR).

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At Klarphos, we have the necessary in-house expertise to effectively implement the strategies described above. We take pride in our comprehensive and well-calibrated investment approach. Our diverse team, abundant industry expertise, and ample resources drive our robust systems to ensure not only meticulous manager selection but also optimal portfolio construction for strategic decision-making. By actively leveraging cutting-edge technology from trusted providers, we remain agile in the dynamic financial landscape.

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Definitions:

A&L: Assets and Liabilities

GPs: General Partners

FoF: Fund of Funds

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Important Information

This document is informative purposes only. It does not constitute research, investment advice nor solicitation to invest in any investment product or service that Klarphos offers or may offer in the future in any jurisdiction. The information contained herein is based on projections, estimates and/or other financial data and has been prepared internally by Klarphos. Opinions expressed therein are current opinions as of the date of this document only and are subject to change at any time without notice.

No representations are made as to the accuracy of the observations, assumptions, and projections. No subscriptions to any Klarphos products are possible based solely on this document. Any investment decisions should be made in accordance with the legal documentation of a fund such as its offering memorandum.

Klarphos is not entitled to provide any tax, regulatory or legal advice.

Past performance is not indicative of future returns. There can be no assurance that the strategy objectives will be realized or that the strategy will not experience losses. Target returns are hypothetical and are neither guarantees nor predictions of future performance. There can be no assurance that the target returns will be achieved.

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