Skip to main content
Skip table of contents

1.2.2 Performance Measurement

A. Internal Rate of Returns

Internal rates of returns or IRRs are widely used in fund reporting and benchmarking in private markets. The IRR is the discount rate at which the net present value of a series of cash flows equals zero, where CFs include inflows (investments) and outflows (distributions). IRRs can be computed at a holding level or fund level by GPs and are often disseminated as the performance metric of choice. Holding level IRRs can also be aggregated into fund levels based on capitalisation weights.

Despite its many shortcomings, the IRR is very appealing for private asset investments, as in theory it is based on actual realised CFs, and thus less subject to biases or assumptions. However, in practice, these considerations are likely trumped by the illiquidity of private investments and the discretion of GPs on the timing of cash flows (e.g., Phalippou, 2008).

  • Methodological concerns: IRR suffers from multiple methodological problems, such as having multiple IRR solutions for the same CF stream and reinvestment rate assumptions that interim CFs can be reinvested at the same rate as the IRR. Methodological solutions exist to overcome each of these deficiencies (e.g., a modified IRR). However, they are not popularly adopted in private markets.

  • Combining estimated and realised CFs: Due to illiquidity, in applications, realised CFs are combined with unrealised estimated valuations in IRR computations, thus making the metric less useful, as estimated valuations are not standardised and can vary a lot based on methodological choices.

  • CF Timing: IRRs are also distorted due to the timing of cash flows. As GPs have discretion on calling for capital and giving out distributions (at the fund level) or paying dividends and arranging debt financing (at the holding level), they can effectively game the IRR by their timing choices. In fact, many market phenomena indicate that GPs seek alternative financing to manage the timing of CFs, such as subscription lines or loans against commitments and net asset value-based loans. Such forms of financing can help manage IRR while increasing the costs for the fund.

Year

Fund A

Fund B

2022

-50.0

-50.0

2023

-25.0

100.0

2024

100.0

-25.0

2025

50.0

50.0

IRR

41.42%

100.00%

Time-weighted return

51.83%

51.83%

Table 1: Illustration of IRR Anomalies

Table 1 presents two examples of how the use of IRRs can distort private investments. Assuming two funds call and distribute identical amounts of capital, but only differ in their timing as shown in Table 1.

The timing of capital calls and distributions severely distorts reported IRRs in this example. Fund A reports an IRR of 41% while Fund B which paid out earlier distributions reports an IRR of 100%. On the other hand, the LP’s average realised returns differ significantly from these reported IRRs. For example, the time-weighted return, which is better in representing the average realised annual return (ignoring the irregular cash flows), works out to an annual 51.83% for both the above investments.

Thus, when GPs can influence the timing of these cash outflows and inflows, IRRs are subject to severe distortions, and lose meaning, especially when reported without the context of cash flow sizes and their timing.

Public Market Equivalent Approaches

The most commonly used private equity performance metrics include multiples of invested capital (MOIC) and IRRs. But both these metrics are inadequate at capturing fund performance and are not comparable across funds, the key requirement of any performance metric.

MOIC expresses fund performance as a multiple of its investment contributions, with greater values being preferable. A key issue of MOIC is that they do not consider the time value of money, the most important tenet in finance. Similarly, issues with IRRs are described above, specifically concerning how the timing and size of cash flows can distort them.

Some proponents propose a public market equivalent (or PME) approach to overcoming some of the problems associated with IRRs and MOIC. To take out the effect of timing from the performance metric, the most basic PME approach (e.g., Long Nickels PME approach) relies on building a portfolio that makes theoretical investments and withdrawals in a stock market index at the same time as the private equity fund calls for contributions or make distributions. Finally, the IRR of the fund is compared with the IRR of the theoretical portfolio (or PME) to get the IRR spread, i.e., how much the IRR exceeds the PME. Greater values of the IRR spread indicate the outperformance of the fund, and vice versa. Several improvements have been proposed to the basic PME approach to tackle its deficiencies, but as illustrated below, is still unreliable.

The PME approach in trying to solve one problem ends up creating another. In addition to all the flaws of IRR, PME that is based on IRRs can additionally rank funds incorrectly, when the market is volatile and funds differ on their timing skills. In the end, investors care about returns, and hence it may be inappropriate to completely nullify managers’ timing skills in their performance analysis.

Year

Index

Index returns

Fund A CFs

Fund B CFs

Value of Theoretical A

Value of Theoretical B

2022

100

0.0%

-75

-75

75.00

75.00

2023

110

10.0%

-50

1

132.50

81.50

2024

160

45.5%

1

-50

191.73

168.55

2025

120

-25.0%

25

25

118.80

101.41

2026

120

0.0%

115

115

118.80

101.41

IRR

3.60%

4.07%

PME

4.40%

0.64%

IRR Spread

-0.80%

3.43%

Table 2: Flaws in PME Approaches

Table 2 illustrates the computations for two Funds A and B that call and distribute capital from 2022 to 2025 and are valued in 2026. Both the funds are identical in CFs except the contribution and distributions for years 2023 and 2024 are interchanged. Specifically, Fund B returns a nominal $1 in 2023, which Fund A does in 2024. At the same time as these funds’ existence, the stock market represented by the index in column 2 is volatile, experiencing both negative and positive returns annually.

The PME computations are performed as follows. Two portfolios named Theoretical A and Theoretical B are formed to mimic the CFs of the two funds. So in 2022, $75 is invested each in the two theoretical portfolios. In 2023, the $75 investment in each fund grows at 10% (the return on the index). Fund A calls for $50 worth capital, which is then added to Theoretical A portfolio which is worth $75 x 1.1 in 2023. Fund B distributes $1, which is then subtracted from Theoretical B portfolio ($75 x 1.1). These calculations are repeated in each row based on the cash flows of the fund and the index returns. Finally, in 2026, IRRs are computed for the two funds and their theoretical equivalents.

The IRR spread for the two funds indicates that Fund A underperformed whereas Fund B outperformed. However, the real performance of the two funds is much more nuanced. Although Funds A and B have performed somewhat similarly, with even their IRRs indicating such similar performance, PME-based IRR spreads are very different. Why is this happening?

To the extent that private and public market valuations are correlated, as agreed by most market participants, both timing and company selection are important aspects of value creation in private markets. But by focusing too much on company selection, rather than timing, PME approaches reward managers more on their company selection rather than market timing. Given that GPs can manage their capital calls and distributions, this approach may lead to misleading conclusions.

For example, Fund A has called capital before a period preceding high growth in the market, i.e., 2024 whereas Fund B has returned capital before good market performance. This indicates that Fund A has timed the financial markets very well compared to Fund B. However, Fund B has been able to select superior companies to invest in as they have been able to return the same amount of capital as Fund A over the fund life, despite being poor in their timing. Although the IRRs and MOICs are very similar between the two funds, PME rewards Fund B more than A.

Moreover, IRR focuses on the stock market index as the benchmark, which is not useful for investors who choose to diversify their public stock market investments through private capital markets. Thus, PME methods suffer from a benchmark choice problem along with asset selection versus market timing issues.

JavaScript errors detected

Please note, these errors can depend on your browser setup.

If this problem persists, please contact our support.