A deeper look at flexible credit strategies and the critical role of manager selection

Investor interest in versatile multi-asset credit (MAC) portfolios has notably increased after the 2022 credit market downturn. Due to the flexible nature of MAC portfolios, investors perceive these mandates as capable of tactically allocating among credit sectors in an effort to enhance returns and reduce volatility, especially on the downside. Are investors getting what they seek from these strategies?

Investors should employ a careful, “buyer beware” approach to strategy selection. Our analysis indicates that some strategies have underutilized the flexibility implied by the product category, in which case investors might end up with more market risk (beta) rather than strategy-driven returns (alpha). Our findings show that strategies that actively adjusted their portfolios typically performed better, especially in managing downside risk.

Some commonly held investor beliefs about multi-asset credit prompted our Multi-Asset Solutions team to examine whether:

• MAC managers are dynamic in their credit exposure positioning.
• MAC strategies have the ability to outperform less flexible fixed income credit strategies.
• Flexible mandates allow managers to adjust to a variety of investing environments.
• MAC strategies provide opportunities for downside risk mitigation.

We studied a cohort of long-tenured MAC strategies¹ to better understand how dynamic their positioning was and whether this dynamic management led to outperformance and reduced downside risk.

How dynamic are multi-asset credit managers?

To begin, we selected strategies from the eVestment multi-asset credit universe² with a minimum of 10 years of performance history, leaving a cohort of 37 strategies. We constructed two risk factors: credit risk³ and duration⁴. We assessed the variations of credit exposures to evaluate how actively a strategy adjusted its portfolio by running 36-month rolling regressions of the returns on the factors for each manager in the cohort. Strategies with significant variations in their credit positioning over the 10‑year period were considered more dynamic.

We categorized managers into two groups based on the variations in how they adjusted their credit exposure:

Dynamic Managers: These strategies frequently adjusted their portfolios. This group had 36-month rolling credit beta dispersion that fell in the top half of the distribution of the cohort. Based on our analysis, they actively increased or decreased risk positions in an effort to enhance performance in both rising and falling markets.

Static Credit Managers: These strategies were in the bottom half of the credit beta dispersion distribution of the cohort. They maintained more consistent credit exposure, appearing to rely on market risk for returns. They adjusted their portfolios less frequently.

Figure 1 shows the credit beta dispersion of the MAC strategies in this cohort over the past 10 years. The very large historical dispersion in how strategies within this cohort dynamically adjusted their exposure to credit illustrates that some strategies have more meaningfully changed their portfolio’s credit exposures than other strategies in the peer group.

We accounted for the notable difference in the average credit levels of the MAC strategies in the cohort by aligning each strategy’s average credit exposure at 0. Relative to their “typical” credit tilt (mean credit beta), the group we classified as “Dynamic Managers” has historically shifted its credit allocations much more actively than the “Static Credit Managers” group.

An example

To demonstrate these results, we analyzed the median (based on breadth of credit beta dispersion) Dynamic Manager and the median Static Credit Manager. We compared each strategy’s credit exposure under two scenarios: a conservative posture (at the 10th percentile of the manager’s 36-month rolling credit beta compared with its mean credit beta) and a more aggressive posture (at the 90th percentile of the manager’s 36-month rolling credit beta compared with its mean credit beta).

• In the conservative posture, we found that the median strategy in the Dynamic Manager group was able to reduce credit exposure by 33%, while the median strategy in the Static Credit Manager group could only reduce credit exposure (credit beta) by 12% compared with its respective typical credit exposure. This indicates that Dynamic Managers had the ability to be more than 2.5 times as agile in adjusting credit exposure.
• In the more aggressive posture, the median Dynamic Manager was 2.4 times more responsive than the median Static Credit Manager in this regard.

Bottom line: Our analysis shows that MAC strategies utilized their flexible mandates to varying degrees. For investors seeking flexible credit allocations, it is crucial to assess how extensively the strategy uses this flexibility as this can potentially impact how a strategy performs.

Does a more dynamic MAC strategy typically outperform fixed allocation portfolios or the broader market?

After establishing that some MAC strategies adjust their credit exposures more dynamically, we wanted to assess what impact dynamic positioning had on performance. Keeping strategies within their Dynamic and Static Credit cohorts, Figure 3 shows a comparison of the performance across a range of traditional metrics for strategies at the 25th, 50th, and 75th percentiles for each metric against two benchmarks: a fixed allocation portfolio and the Bloomberg U.S. Aggregate Bond Index.

Our findings highlight three key performance differences among Dynamic Managers and Static Credit Managers.

• The best-performing (75th percentile) Dynamic Manager outperformed (gross of fees) both benchmarks as well as its Static Credit Manager peer and also generated strong risk‑adjusted returns, with a Sharpe ratio of 0.8. Similarly, the median Dynamic Manager outperformed both benchmarks and its Static Credit Manager peer.
• The median and top quartile Static Credit Managers also outperformed (gross of fees) both benchmarks, generating solid risk‑adjusted returns, but they trailed their Dynamic Manager peers. While they delivered solid returns, they lacked the upside potential seen in the Dynamic Manager group.
• Despite the potential for outperformance due to its flexible credit positioning, the bottom quartile Dynamic Manager underperformed, lagging notably in both excess returns and Sharpe ratio, suggesting that a MAC strategy’s success depends heavily on manager skill. This underscores the importance of strategy selection within this category.

How did MAC portfolios perform in different environments?

One perceived attribute of MAC strategies is that their flexibility may lead to more durable performance in a variety of environments. To evaluate this belief, we considered Dynamic and Static Credit Manager performance across different market regimes.

Our examination focused on performance during different interest rate and credit spread scenarios. Figure 4 illustrates performance patterns that are consistent with our expectations for strategies that have higher credit beta (Static Credit Managers) versus those that seek to generate alpha by actively managing their market exposure (Dynamic Managers).

Rising Rates and Widening Credit Spreads: During periods of market stress, such as in 2022, the Dynamic Managers demonstrated their advantage. Their flexible approach allowed them to tactically adjust exposures, resulting in meaningful outperformance relative to the Static Credit Managers and the benchmarks. In this environment, the ability to de-risk and actively manage exposures became a clear differentiator, as the Static Credit Managers’ structural beta left them more exposed to downside risks.

Falling Rates and Tightening Credit Spreads: Conversely, in bullish credit markets where rates were falling and spreads were tightening, the Static Credit Managers tended to outperform. In these conditions, more beta exposure led to better results, and the more stable, high‑beta nature of the Static Credit Managers’ portfolios allowed them to capture more of the upside.

Despite the average performance of Dynamic Managers and Static Credit Managers demonstrating expected results, Figure 5 shows that there has been heightened dispersion of performance by regime. Here, we see a wider range of results for the Dynamic Managers across all regimes. In all regimes, the Dynamic Manager grouping provided more potential for both upside and downside outperformance. Strategy selection is critical in this category.

How do these findings influence portfolio construction?

If allocators can successfully identify skilled dynamic strategies, the resulting improvement in return-seeking fixed income portfolios’ performance becomes evident. Given the high tracking error, MAC strategies are often best employed as a complement to a fixed allocation. To illustrate, we constructed hypothetical blended portfolios, allocating 75% to the “fixed allocation” (equal parts global high yield, floating rate bonds, and emerging market debt) and 25% to either the median Dynamic Manager or Static Credit Manager.

Figure 6 shows the resulting distribution of returns for the two hypothetical blended portfolios over four rolling windows: one, three, five, and seven years. Seven years was selected due to our analysis using 10 years of historical data.

We note an interesting observation. Over the rolling one-year window, the hypothetical portfolio that allocated to the median Dynamic Manager had wider dispersion in portfolio returns, including the potential for more downside. However, as we expanded the rolling window, the dispersion of returns for the portfolio with the Dynamic Manager tightened. We see that the portfolio with the Dynamic Manager both outperformed the portfolio that allocated to the Static Credit manager, with less downside.

We further examine the Dynamic Manager downside risk mitigation in Figure 7. We note that while the Dynamic Manager offered meaningfully less down-market capture, that came at the expense of less participation in up markets. However, a lower allocation to the Dynamic Manager was needed to achieve a targeted level of downside mitigation (e.g., 90%).

Careful choices for stronger portfolios

The growth of the flexible multi-asset credit category is driven by a clear goal: to build a more resilient credit portfolio capable of navigating challenging credit markets and ultimately generating stronger asset compounding by avoiding significant drawdowns.

However, achieving this goal requires careful diligence. A buyer beware approach is essential in trying to distinguish between managers truly generating alpha and those relying primarily on beta, helping ensure that investors are not misled by passive market exposure masquerading as skillful management.

Choosing the right dynamic strategy can enhance portfolio returns and reduce downside risk, highlighting the importance of careful strategy selection.

 

Appendix

Important information regarding hypothetical results:

The information provided above reflects data for hypothetical portfolios based on the theoretical blending of the indicated benchmarks and eVestment category data. It does not reflect the actual returns of any portfolio or strategy. For the applicable hypothetical portfolios, the assumption of constant benchmark weights has been made for modeling purposes and is unlikely to be realized. Results shown for blended portfolios are hypothetical, do not reflect actual investment results, and are not a reliable indicator of future results. Hypothetical results were developed with the benefit of hindsight and have inherent limitations. Hypothetical results do not reflect actual trading or the effect of material economic and market factors on the decision-making process. Results are based on recognized broad market indexes and eVestment data gross of fees returns. It does not reflect fees associated with an actively managed portfolio. Returns would have been lower and conclusions might differ as the result of the deduction of applicable fees. Actual returns may differ significantly from the results shown above. It is not possible to invest in an index or category. Different time periods would yield different results.

Active investing may have higher costs than passive investing and may underperform the broad market or passive peers with similar objectives.

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