Private Credit Benchmarking: Why the Cash Flow Clock Matters

At a Glance

Benchmark choice and measurement method can materially affect conclusions about private credit performance. Widely circulated recent research compared drawdown-fund multiples (the traditional capital call and distribution structure of private markets) with buy-and-hold ETF returns. Measuring in this way can be misleading because it ignores the timing of capital calls, distributions, and residual value. Using 2015–2020 fund cash flows from MSCI Private Capital Intel, we apply cash-flow-matched KS-PME and Direct Alpha measures, two measures that are well-established within private markets and that account for these issues. Senior direct lending generated a median KS-PME of 1.18x (roughly produced 18% more value) and Direct Alpha of 3.3% (annualized estimated alpha) versus the Invesco Senior Loan ETF (Ticker: BKLN). These advantages narrow under leverage adjustments and residual-value haircuts but generally remain positive, particularly for subordinated debt.

Key Takeaways

• Benchmark design matters: Private credit funds should be compared with public benchmarks using matched capital calls, distributions, and residual values—not buy-and-hold ETF returns.
• Cash-flow-matched results indicate outperformance: For 2015–2020 vintages, global senior direct lending generated a median KS-PME of 1.18x and annual Direct Alpha of 3.3% versus BKLN.
• Conservative assumptions reduce, but do not generally eliminate, the advantage: Leverage adjustments and residual NAV haircuts narrow measured outperformance, while subordinated debt remains more resilient than senior direct lending in these sensitivity tests.

Private credit investors and industry observers have been asking an important question in recent months: has private credit actually outperformed public credit, or has performance been artificially inflated by leverage and unrealized marks? Arriving at a precise answer requires the use of rigorous methods that capture the cash flow structure of private drawdown fund investments.

A recent academic debate focused on whether private credit drawdown funds have delivered excess returns relative to liquid public market alternatives such as bank loan exchange-traded funds (ETFs). Hooke et al. (2025) pointed to modest fund multiples for a sample of vintage 2015–2020 private credit funds and the fact that a large share of reported value remained in residual net asset value (NAV) rather than realized distributions when they stopped their study in 2024. Those are valid concerns. Private credit valuations should be carefully reviewed, especially when funds are not yet fully realized.

But there is a separate and equally important issue: Hooke et al. (2025) compared drawdown funds to ETFs, which do not invest capital on the same schedule. Comparing a private credit fund’s total value to paid-in capital (TVPI) to the return from buying and holding an ETF starting at the date the fund commitment closes can produce a misleading analysis.

The Problem with TVPI-versus-ETF Comparisons

Private credit drawdown funds do not typically call all committed capital immediately upon fund closing. Capital is called over time, often across several years, as loans are sourced and finalized. Distributions also arrive over time, and a portion of the fund’s value may remain in NAV when fund performance is measured.

An ETF comparison that assumes all capital was invested immediately ignores this reality. It effectively asks, “What if the investor had put all the money into the ETF at the beginning of a fund’s life and held it?” That may be a useful thought experiment, but it is not the right methodology for a drawdown fund.

Benchmarking comparisons are meant to assess a manager’s performance, but the assessment becomes skewed if investment timing is ignored. Comparing TVPI to the multiple earned from buying and holding an ETF implicitly assumes that uncalled capital is held in cash earning zero interest—one might say the cash is put under a mattress. Accurate performance attribution must focus on the value added by a manager’s investment decisions only while capital is under the manager’s control, without making any assumptions about capital the manager does not control.

The need to assess managers only during the time that they control capital is the reason that many investors use internal rates of return (IRR), which are based solely on investment performance while capital is deployed. IRR has drawbacks, including that it can’t be compared directly to buy-and-hold investments due to its reliance on cashflow structure. TVPI, or a simple ratio of cash out divided by cash in, creates a similar problem by assuming that uninvested capital sits in cash earning zero return.

The solution must use a benchmark which mirrors the manager’s actual opportunity set, rather than assuming the manager controlled the capital and did something with it before it was ever called.

The relevant benchmarking question for allocators is: “What would have happened if the same dollars had been invested in a public credit benchmark on the same dates the private fund called capital, and withdrawn on the same dates the private fund made distributions?” That is the most relevant economic comparison.

A Better Framework: Cash-Flow-Matched Benchmarking

A cash-flow-matched public market equivalent (PME) framework addresses the timing problem directly. Each private fund capital call is treated as if it were invested in the public benchmark on the date it was called (e.g., quarterly). Each distribution is treated as if money were withdrawn from the benchmark on the date the fund returned capital. Any remaining NAV is treated as a final value at the measurement date. This approach produces two useful measures.

The first is the Kaplan Schoar Public Market Equivalent, or KS-PME. A KS-PME above 1.0x means the private fund created more value than the matched public benchmark. A value below 1.0x means it underperformed.

The second is Direct Alpha, which translates benchmark-relative performance into an annualized return spread. A positive Direct Alpha means the private fund outperformed the public benchmark after matching the timing of cash flows.

These tools are not perfect. They do not eliminate the need to think about risk, leverage, liquidity, manager selection or valuation uncertainty. But they answer the first-order question: did the private fund outperform an investable public alternative using the same cash flow pattern?

What the Evidence Shows

Using 2015–2020 vintage private credit fund net cash flows from MSCI Private Capital Intel, the analysis finds that private credit performance diverges meaningfully from the Hooke et al. (2025) results when using the same benchmarks but accounting correctly for cash flow timing.¹

For global senior direct lending funds, the median vintage IRR was about 7.6%. Relative to the Invesco Senior Loan ETF (ticker BKLN), a liquid public market proxy for the U.S. Leveraged Loan Market, the median vintage KS-PME for global senior direct lending funds was 1.18x and the median vintage Direct Alpha was 3.3% per year. Senior direct lending vintages therefore generated more value than the cash-flow-matched public loan ETF benchmark.

For global corporate subordinated debt funds, the results were stronger. The median vintage IRR was about 11.3%, with a median KS-PME of 1.42x and median Direct Alpha of 6.8% versus BKLN.

Exhibit A. Direct Alpha Relative to Unlevered Public Credit

Exhibit B. KS-PME Relative to Unlevered Public Credit

The pattern is intuitive. Senior direct lending generally demonstrates lower risk and lower expected returns than subordinated debt. Subordinated debt sits lower in the capital structure and implies higher risk, so should command higher compensation. The results reflect that hierarchy.

Adjusting for Leverage Narrows the Gap, But Does Not Erase It

One critique of private credit outperformance is that private funds may use leverage. If a public benchmark is unlevered while the private fund uses leverage, the comparison may overstate the private fund’s relative performance during periods where fund returns exceed the cost of leverage.

The analysis addresses this by testing leverage-scaled versions of public credit benchmarks. In one scenario, the public benchmark is scaled to 1.25x exposure (i.e., the benchmark index is levered so $1 of equity exposure yields $1.25 of exposure to the index less financing costs). In another, it is scaled to 1.50x exposure.

As expected, adjusting for leverage reduces the measured outperformance of private credit funds relative to bank loans. For global senior direct lending, the median vintage Direct Alpha versus BKLN falls from 3.3% using the unlevered benchmark to 2.8% and 2.3% at 1.25x and 1.50x leverage, respectively. For global corporate subordinated debt, the median vintage Direct Alpha versus BKLN declines from 6.8% to 6.2% and 5.7% at the respective leverage levels.

This is an important result. Leverage adjustment matters, but it does not fully explain the observed performance advantage of private credit funds relative to bank loans in this sample.

Residual NAV Risk Still Matters

The reliability of remaining NAV is a serious concern for many investors. Private credit funds often hold loans that have not yet been repaid, refinanced, or sold. As a result, reported performance can depend heavily on valuation marks. This is especially true for younger vintages, where more of total fund values remain unrealized. Valuation marks can be stress-tested using the same KS-PME and Direct Alpha measurements combined with haircuts to residual NAV.

For global senior direct lending, a 25% NAV haircut reduces median vintage Direct Alpha versus unlevered BKLN from 3.3% to 1.5% while the median vintage KS-PME falls from 1.18x to 1.08x. Performance remains positive, but the cushion is thinner.

For global corporate subordinated debt, the same 25% NAV haircut reduces median vintage Direct Alpha versus BKLN from 6.8% to 5.1% and median KS-PME from 1.42x to 1.31x. Subordinated debt shows more resilience in this sample, though it also carries different risks.

The practical message is straightforward: residual values are not a detail. They are central to interpreting private credit performance, especially for recent vintages. The appropriate response to residual NAV risk is to stress-test those residual values within a cash-flow-matched PME framework, rather than drawing conclusions from ETF comparisons that do not reflect the timing of capital calls and distributions.

What Allocators Should Take Away

The lesson is not that private credit always outperforms, nor that every positive PME or Direct Alpha estimate represents pure manager skill. Some portion of private credit returns may compensate investors for illiquidity, complexity, borrower selection, leverage, or risks not fully captured by public benchmarks.

The better takeaway is that benchmark design can change the conclusion. For allocators, the right comparison is not a drawdown fund multiple versus a buy-and-hold ETF return. The right comparison should ask what would have happened if the same dollars had been put to work in a liquid public benchmark on the same dates and withdrawn on the same dates.

That distinction is essential because private credit funds call capital gradually. Public ETF returns earned before a private fund has called capital are not returns the private fund had the opportunity to earn. Similarly, distributions returned by the fund should not be ignored when constructing the public market counterfactual.

A cash-flow-matched PME and Direct Alpha framework provides a clearer comparison. It helps investors evaluate whether a private credit allocation added value relative to a practical public alternative. It also allows investors to test how results change under different assumptions about leverage and NAV reliability.

The Bottom Line

Private credit performance should be carefully assessed relative to other investment opportunities, but that assessment should be done using the most appropriate measurement tools possible. When 2015–2020 vintage private credit cash flows are compared with public credit benchmarks on a cash-flow-matched basis, senior direct lending and subordinated debt generally outperform the selected public benchmarks in this sample. The advantage narrows when public benchmarks are levered and residual NAVs are stress-tested, but it does not disappear uniformly.

Private credit should not be judged by multiples alone, and it should not be compared with public ETFs on a mismatched investment schedule. The benchmark investors should care about whether private credit has created more wealth than a liquid alternative funded with the same dollars at over the same periods.

For the full academic treatment: See our paper, “Benchmarking Private Credit for Portfolio Allocators: A Public Market Equivalent Approach,” in the Journal of Private Markets Investing.

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Author’s note: This article is a practitioner-oriented companion to our academic paper, Benchmarking Private Credit for Portfolio Allocators: A Public Market Equivalent Approach, prepared for publication in the Journal of Private Markets Investing. The academic paper provides the full methodology, data description, PME and Direct Alpha calculations, leverage-adjusted benchmark tests, and residual NAV sensitivity analysis underlying the discussion below.

1 All results are net cash flows. Private credit data is sourced from MSCI Private Capital Intel (fka Burgiss).

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