6 June 2024

Why Less Is More in Multi-Asset Credit

John Yovanovic, CFA

John Yovanovic, CFA

Portfolio Manager, Co-Head of Leveraged Finance

Why Less Is More in Multi-Asset Credit

The logic of most multi-asset credit strategies appears self-evident: Spread the risk of fixed income investing across a number of credit asset classes and the resulting diversification should result in better outcomes. But what if a different kind of diversification produces better risk-adjusted returns?

With many managers emphasizing the “multi-asset” aspect of multi-asset credit strategies, it is our contention that focusing on the quality of the “credit” component is the basis for a more effective form of diversification – and one with the potential to achieve better outcomes. Here we explore key three reasons why.

1) High correlations minimize excess return advantages from top-down asset allocation alone

Consider the five or six typical components of a multi-asset credit strategy — US and European high yield bonds, emerging market debt, and various tranches of US and European collateralized loan obligations (CLOs). All are essentially spread products where the major risk revolves around the issuer, because, unlike sovereign and investment grade markets, there is a material degree of default risk. As a result, these credits tend to be very sensitive to changes in the economy, making them highly correlated on an excess-return basis. Yes, there are periodic dislocations around short-term technical flows that favor one segment over another. Realistically, however, the asset classes tend to be 85% to 90% correlated (see chart). As a result, on an excess-return basis, there is usually not much to gain from concentrating on asset allocation from a top-down perspective, especially between high yield bonds and leveraged loans.

Credit Is Highly Correlated on a Same-Currency Basis for Below-Investment Grade Asset Classes

10-year correlation matrix

Why Less Is More in MA Credit charts-01

Source: Bloomberg as of 31 March 2024. European High Yield is the Bloomberg Pan-European High Yield Total Return Index Value Hedged USD. EM High Yield is J.P. Morgan Corporate Broad EMBI Diversified High Yield Index Level. European Leveraged Loans represented by the Morningstar European Leveraged Loan TR Hdg USD. High Yield is the Bloomberg US Corporate High Yield Index. US Leveraged Loans represented by the Morningstar LSTA US Leveraged Loan Index.

2) Expanding the issuer universe lowers pairwise correlations while enhancing security selection potential

Because there is so much idiosyncratic issuer risk below investment grade, expanding the pool of issuers under consideration lowers pairwise correlation in the investment universe (see chart) – and a manager skilled at security selection should find more opportunities if they are not locked into an asset-class-specific mandate. At the same time, the large universe of issuers creates a market in which deep and meaningful analyses of each company’s fundamentals are not available to most investors; while credit ratings can provide a critical base of information, investors in a pool of credits may not be aware of the nuanced and idiosyncratic differences among issuers. This is where we believe skilled asset management can enhance investment outcomes. With credit fundamentals driving returns, we believe an emphasis on issuer selection rather than on issue type has a greater impact on risk-based return potential, especially as the same issuer may offer more than one type of debt.

Pairwise Correlation Decreases as Universe Expands – the Time Is Right for Security Selection

Lower pairwise correlations from larger opportunity set

Why Less Is More in MA Credit charts-02

Source: Bloomberg as of 31 December 2023. Data was calculated for rolling 12-month time periods. Source for High Yield Bonds: Bloomberg US Corporate High Yield Index. Excess returns were calculated by Bloomberg on a monthly basis by Ticker. Source for Loans: Credit Suisse Leveraged Loan Index. Excess returns were calculated by subtracting a 50% 1-month Libor / 50% 3-month Libor index return from the total return of each issuer in the index. Pairwise correlations were calculated by taking an average of every possible issuer combination on a monthly basis. Diversification does not ensure against loss in any market. Benchmarks are used for illustrative purposes only - it is not possible to invest directly in an index. Past performance is not indicative of future results.

3) More asset classes can mean added risk with little potential reward

Because the asset classes tend to move together, and pairwise correlation falls as the universe expands, we’ve found that a flexible approach to allocations that looks at an expanded pool of issuers while concentrating on three key asset classes – high yield bonds, leveraged loans, and CLO tranches as a tactical play – offers better risk-adjusted return potential than relying on asset allocation across a larger number of asset classes as the main driver of returns. We see plenty of opportunity to increase portfolio tracking error and beta within these areas of leveraged finance.

Intuitively, there should be diminishing marginal returns as other credit asset classes that may add to the portfolio’s spread duration are included in portfolio allocations. The data from our analysis supports this conclusion, even with on-benchmark securities, as the lowest rating tier has the worst Sharpe ratio (see table). Multi-asset credit strategies that focus on allocations among a range of credit types may veer toward investing in higher-volatility asset classes and away from the core allocation in order to improve returns. An example might be adding CCC rated and distressed parts of the loan and bond markets. While there may always be discounted credits that are worth considering, we believe history does not support consistent, broad exposure to the lowest-rated segments of the universe. We believe a larger opportunity set can help better source spread credit issuers in the field of play, and by looking outside the benchmark investment universe, correlated instruments that are of higher quality are more drawdown resistant, and can help preserve carry. Sharpe ratios decline at the CCC level, and volatility aside, there is little return benefit.

More Credit Risk Does Not Always Lead to Higher Returns

Lower-quality CCC rated assets have not outperformed over longer-term periods

Why Less Is More in MA Credit charts-03

CCC does not consistently outperform broad indices. Historical results suggest a countercyclical approach could lead to superior results.

Why Less Is More in MA Credit charts-04

Source: Bloomberg, as of 31 March 2024. 1 Sources for High Yield: Bloomberg US Corporate High Yield Index; High Yield B-Rated: Bloomberg US HY B TR Index USD; High Yield BB-Rated: Bloomberg US HY Ba TR Index USD; High Yield CCC-Rated: Bloomberg US HY Caa TR Index USD. 2 Sources for Bank Loans: Morningstar LSTA US LL TR Index USD; Bank Loans B-Rated: Morningstar LSTA US LL B TR Index USD; Bank Loans BB-Rated: Morningstar LSTA US LL BB TR Index USD; Bank Loans CCC-Rated: Morningstar LSTA US LL CCC TR Index USD.

For illustrative purposes only. Past performance is not indicative of future results. Benchmarks are used for illustrative purposes only, and any such references should not be understood to mean there would necessarily be a correlation between investment returns of any investment and any benchmark. An investor generally cannot invest in a benchmark, and any referenced benchmark does not reflect fees and expenses associated with the active management of any investment.

A different approach to multi-asset credit

We believe that a purposefully flexible allocation strategy and focus on high yield bonds, leveraged loans, and tactical use of CLO tranches offers better risk-adjusted return potential within multi-asset credit. And while this strategy may reduce the breadth of companies in a portfolio, we believe this can be an advantage for managers if bottom-up fundamental research is a core competency: the focus on issuer-level research, security selection, and credit quality results in a select pool that includes only those credits with the strongest risk-adjusted return potential. It’s critical, of course, that from an investment perspective, there is a strong understanding of the nuances – not only across issuers, but also between issues of the same issuers.

An approach with the flexibility to move up and down the capital structure from secured to unsecured or floating to fixed-rate debt may also allow for stronger risk management. Taking on more risk when returns are available and moving into higher-quality instruments when conditions turn may help protect the portfolio in times of volatility while improving investment outcomes.

We believe the result is a portfolio with more high-conviction core positions, and one where risk positioning can be adjusted to capitalize on market inefficiencies as conditions swing from bullish to bearish.


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