A Clearer Way to Benchmark Private Equity

On March 30, the US Department of Labor (DOL) released draft guidance clarifying how defined contribution plan fiduciaries may evaluate private market investments. Central to the guidance is a requirement with implications beyond compliance: fiduciaries should use a “meaningful benchmark” when selecting private market investments and assessing their results. 

By elevating benchmark selection from a technical choice to a fiduciary obligation, the DOL has sharpened focus on a core challenge in private equity evaluation: how to assess performance in a market where the benchmark itself is uncertain.

Benchmarking private equity has always been more complicated than benchmarking public markets. Prices are not continuously observed, disclosures are inconsistent across managers, and there is no centralized performance record. As a result, private equity benchmarks are constructed from partial, heterogeneous data sets rather than a complete view of the market. 

These limitations were long treated as structural features of the asset class. Benchmarks served as broad reference points, useful for orientation but insufficient for attribution or decision making. 

That assumption is no longer holding. As private markets have grown in scale and become more central to institutional and retirement portfolios, investors and fiduciaries are demanding benchmarks that do more than approximate performance. 

Against this backdrop, differences in benchmark construction are no longer academic. They have direct portfolio consequences. Depending on methodology, benchmarks intended to represent the same asset class can diverge by several hundred basis points over identical periods.

For practitioners allocating capital, selecting managers, and managing portfolio risk, understanding why that dispersion exists, and what it implies, is increasingly essential.

Benchmark dispersion in private equity is driven by how the underlying data is sourced and constructed. That construction explains why benchmarks that appear similar can produce materially different results. 

Unlike public markets, performance is observed intermittently, with no single source capturing the full market. Transparency into benchmark constituents, investment holdings, and return drivers is limited, even when benchmarks carry identical labels.

Most private equity benchmarks are constructed from a combination of public disclosures, regulatory filings, advisory relationships, or administrative platforms. Each approach captures a different slice of the market, shaped by who reports, what is reported, and when. None provide a complete view.

These sourcing differences introduce structural biases, including survivorship bias, self-selection bias, and distortions driven by the composition of the reporting base. Benchmarks that are disproportionately influenced by certain investor types — such as large institutional allocators — may tilt toward specific segments of the market and exhibit systematically different return profiles.

In this context, the method of data collection becomes inseparable from the benchmark outcome. Private equity benchmarks reflect not only the market, but the lens through which that market is observed. Dispersion is not an anomaly; it is an expected consequence of incomplete and unevenly reported data.

Historically, private equity has been benchmarked at the closed-end fund level, a framework that reflects how data is reported but not necessarily how portfolios are constructed. 

Benchmarks aggregate net limited partner cash flows and valuations, typically grouped by vintage year and reported using point-in-time metrics such as internal rate of return (IRR), total value to paid in (TVPI), and distributions to paid in (DPI). Percentile and quartile rankings are often layered on top.

This framework remains useful for evaluating individual funds relative to peers launched in similar market environments. It is well suited to manager selection within a closed-end fund universe and continues to dominate private equity performance reporting.

However, fund-level benchmarks have notable limitations. They offer little insight into underlying exposures, return drivers, or sources of risk. They are difficult to reconcile with portfolio level return attribution and provide limited comparability across strategies, structures, or time horizons. As private equity portfolios have diversified and grown more complex, these constraints have become increasingly apparent.

The growth of continuously offered, or “evergreen,” private market vehicles has further complicated benchmarking, reinforcing the limits of traditional fund-level frameworks. In response, some benchmark providers have introduced evergreen-style indices, typically constructed as time-series aggregate of these vehicles.

While these benchmarks attempt to reflect a growing segment of the private markets, they introduce additional challenges. Evergreen vehicles differ materially in strategy mix, investment pace, liquidity terms, leverage, and fee structures. They continuously deploy and recycle capital rather than operating over a fixed life.

Aggregating these vehicles into a single return series, often without transparency into underlying holdings or exposures, can produce a benchmark that is difficult to interpret or compare. 

Applying closed-end fund metrics to these structures can create a category mismatch, exposing the gap between traditional benchmark design and how private capital is increasingly accessed.

These challenges have prompted renewed interest in benchmark frameworks that move beyond the fund as the primary unit of analysis.

As private equity strategies diversify and portfolios grow more complex, meaningful evaluation increasingly requires visibility into the underlying investments and how they perform. Investment-level benchmark construction shifts the focus from funds to those investments.

This shift enables more granular attribution and comparability. By observing performance at the transaction level, investors can analyze sector exposures, holding periods, and factor sensitivities. This allows investors and those serving them to distinguish returns driven by allocation decisions, market exposure, and specific operational outcomes.

Investment-level benchmarking also supports a more consistent comparison between private and public markets. Observing returns at the investment level can allow for clearer alignment with public market equivalents, facilitating capital allocation decisions within a total portfolio framework.

In this context, benchmark dispersion becomes informative rather than problematic. Differences in results help reveal where returns and risks originate, rather than obscuring them behind a single summary statistic.

Private equity benchmarking is shifting toward greater transparency, attribution, and analytical rigor. The Department of Labor’s recent guidance reinforces the importance of meaningful benchmarks in fiduciary evaluation, but the momentum extends beyond regulatory compliance.

Investors increasingly expect to understand what a benchmark includes, what it excludes, and which assumptions materially influence its results. The standard is shifting from trusting the number to understanding its construction. Dispersion, attribution, and transparency are becoming core features rather than optional enhancements.

This evolution does not eliminate tradeoffs. Highly standardized benchmarks remain valuable for broad comparability, but they often obscure the drivers of performance. More granular, transaction-informed approaches offer deeper insight into exposures and risks, but they require stronger data foundations and greater analytical judgment.

The challenge ahead is not to produce more benchmarks, but to develop frameworks that make private market performance interpretable, comparable, and decision relevant. As private assets compete more directly for capital within diversified portfolios, clarity is no longer a luxury. It is a necessity.

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