Author Details

Lue Xiong

Lue Xiong

Senior Associate, MSCI Research

Andrew DeMond

Andrew DeMond

Executive Director, MSCI Research

Hamed Faquiryan

Hamed Faquiryan

Executive Director, MSCI Research

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What Drove Private-Credit Funds’ Outperformance?

  • Investors looking for income and diversification in private credit have limited ability to distinguish between funds, beyond assessing overall strategy or size.
  • Combining Burgiss’s database of private-credit funds with MSCI’s analytics, we find significant variation across sectors in the yield difference between private loans and broadly syndicated loans.
  • Limited partners may wish to take a closer look at their funds’ sector allocations to better understand the drivers of return in their private-credit allocation.

When selecting private-credit funds, investors are often limited to the consideration of broad strategies, due to the general lack of transparency within the asset class. In this blog post, we combine Burgiss’s loan-level data1 for private-credit funds with MSCI’s analytics to produce a more detailed picture of the direct-lending market. We find that, at the fund level, the yield premia attributable purely to sectors were quite heterogeneous and ranged from 165 basis points (bps) to 303 bps. Given these differences, additional transparency into sector allocation may help investors better understand the risk and return profiles of private-credit funds.


Sector allocations in private credit

We estimated yield to maturity2 for private-loan holdings across 55 private-credit funds that represent USD 49 billion in assets under management.3 We then calculated the private-credit yield premium as the difference between direct-lending yield and the average yield for broadly syndicated loans within the same sector and seniority bucket as the private loan.

The exhibit below shows the average private-credit yield premium by sector net of subordination effects.4 The figure illustrates that the private-credit premium was not constant across sectors. For example, the communication-services sector had the highest premium at 350 bps, while health care had the lowest, at 120 bps.


Private-public yield difference varied by sector

This chart shows how the private-/public-loan yield varied by sector. It shows that the yield difference was highest for the communication-services sector and lowest for the health-care sector.

Private loans’ credit-spread premium for various sectors, over broadly syndicated loans, with each private loan benchmarked to syndicated loans within the same sector and seniority bucket. The error bars show ±1 standard deviation for the spread-premium estimates.


Sector allocation differentiated private-credit funds

To examine the potential impact of sectoral differences on excess return in private-credit funds’ performance, we estimate each fund’s sector-driven private premium as the sum of the fund’s sector-allocation weights times the sector premium shown in the exhibit above. The histogram below shows the distribution of these fund-level sector-driven private premia across the 55 funds in our study. The figure clearly demonstrates that many funds were concentrated in only a few sectors.


Private-credit premium by fund

This chart shows the distribution of the private-credit yield premium for the 55 private-credit funds in the analysis. It shows that the average fund-level private-credit premium, relative to broadly syndicated loans, was roughly 225 basis points.

Distribution of private funds’ yield premium driven by sector allocation. Red line shows the average fund-level private-credit premium relative to broadly syndicated loans.


A new view on fixed-income allocations

In the public-credit market, sectors have long been an important factor to consider in portfolio construction. Our analysis shows that this can also be true in private credit. Investors may therefore wish to take a holistic view of both public- and private-credit sector exposures as they consider how to diversify their fixed-income allocation.


The authors would like to thank Luis O’Shea and Patrick Warren from Burgiss for their contributions to this post.



1Loan-level data from the Burgiss Manager Universe.

2The MSCI Leveraged Loan Model calculates yield from Burgiss private-loan data, including loan price, coupon rate and time to maturity. For more details on the MSCI loan model, see: DeMond, Andrew, Faquiryan, Hamed, Rueda, Manuel, and Spray, Alexander. “Leveraged Loans.” MSCI Model Insight, June 2018.

3Only senior and subordinated loans were included in this analysis. Distressed loans were excluded. Data is as of Sept. 30, 2020.

4The adjustment had little impact on the result, as the extra yield premium in subordination was almost the same in private and syndicated loans.



Further Reading

Modelling Leveraged Loan Prepayments: COVID-19 and Beyond (client access only)

Assessing Private Infrastructure in a Multi-Asset-Class Portfolio

A Closer Look at Private Debt (Burgiss)

Leveraged Loans (client access only)