Alpha in Fixed Income: Why Consistency Is the True Differentiator

Active fixed income managers also benefit from new issues and can dynamically adjust portfolios in response to changing market conditions, exploit dislocations, and manage risk more precisely. Passive strategies, by contrast, are often forced to ride out volatility and accept market pricing.

In fact, over the past decade, active managers have outperformed passive funds in 84 rolling three-year periods, achieving an 87% batting average³.

However, while active fixed income management outperforms passive overall, consistency at the top is elusive. It’s particularly difficult for individual funds to remain in the top quartile of the actively-managed core plus bond universe—especially during periods of heightened volatility. For example, in one of the studies we conducted by following 102 US intermediate Core Plus funds and looking at risk-adjusted returns (measured by the information ratio), only 7 stayed at top quantile from 2019 to 2014. Among all the funds with $10 billion AUM or more, only 2 fit that category. In fact, half of the 2019 top quartile funds fell two or more quantiles in five years.

Volatility Is Increasing—and So Are the Challenges

Periods of volatility are becoming more frequent, more intense, and shorter-lived. The structural tailwind of long-duration bonds has faded with the end of the 40-year bull market. In this environment, strong active management becomes not just advantageous—but essential. When volatility spikes, the ability to identify dislocations, manage downside risk and dynamically reposition portfolios is critical to outperform peers.

Our Prescription for Consistent Alpha

1. Macro is Foundational—but Not Sufficient and less consistent than sector/security selection
   Market cycle calls and the deep research for those are critical to fixed income strategies, but expressing them purely through duration or FX is limiting. Active decisions such as curve positioning or cross-country positions are very important. Our performance also shows that sector and security selection if done right are more consistent and reliable than macro positioning.
2. Sector Allocation Must Consider Downside Risk and Correlations
   Especially in large benchmark sectors, it’s not just about expected return—it’s about identifying the cross sector relationships, relative value between sectors and correlations to manage downside volatility.
3. Explore a Wide Opportunity Set with a Well-Sized Team
   Breadth increases the chances to apply skill. A sufficiently resourced team can scale the best ideas in markets that are more complex, deep and inefficient.
4. Stay Flexible and Nimble
   Fund size matters. Being able to move across environments and scale bottom-up ideas is key to repeatable success. But size is a double-edged sword: too small, and a fund may lack access to new issues or the depth of bottom-up expertise needed to capitalize on opportunities; too large, and it may be forced to buy the entire market or dominate new issues in smaller sectors, limiting flexibility and real active management.

Importantly, all of these elements are only achievable with a deep team of analysts and substantial resources. Consistently generating alpha across different environments requires both macro expertise and rigorous bottom-up security selection.

Some Examples of How Top Managers Generated Alpha

1. Flexible Sector Allocation
   Sector allocation decisions—particularly in benchmark-heavy sectors like Agency MBS—can be a powerful source of alpha when approached with flexibility and foresight. Top-performing core plus managers demonstrated this by entering 2022 with significantly lower exposure to Agency MBS than their peers, anticipating spread widening. As spreads widened through 2022 and 2023, these managers increased their allocations more aggressively than peers, capitalizing on the relative value opportunity. This dynamic reallocation highlights how active managers can outperform by not just chasing returns, but by managing downside risk and timing re-entry into sectors when valuations become attractive. It also underscores the importance of being unconstrained by benchmark weights and having the conviction to diverge from consensus positioning.
2. Security Selection
   Alpha from issue selection in IG corporates has proven to be one of the most durable sources of outperformance. During periods of market stress, forced selling can create significant dislocations in spreads. Top-performing managers have been able to identify and capitalize on these opportunities—often before new issuance resumes—by targeting specific issuers or structures that offer compelling relative value. However, this strategy can be difficult to scale, especially in benchmark-heavy portfolios where liquidity and concentration constraints limit flexibility.
3. Non-Benchmark Securities
   Given the limiting benchmark creation methodologies, some of the most compelling alpha opportunities lie outside traditional benchmarks. Top-performing managers have consistently tapped into non-benchmark and emerging security types—such as structured credit, private placements, or off-the-run issues—that are often overlooked by larger or more constrained funds. These segments can offer attractive relative value and diversification benefits, but they also require deep credit expertise and nimble execution. While these opportunities may be harder to scale, especially in smaller or less liquid markets, they provide a critical edge for managers willing and able to go beyond the index.

Conclusion
In a fixed income landscape defined by rising volatility, shrinking buffers, and shifting macro regimes, the case for active management is not just compelling—it’s essential. While active strategies have a proven track record of outperforming passive ones, not all active managers are created equal. The inconsistency in performance we found underscores the importance of a repeatable, risk-aware process. Sustained alpha requires more than a good trade—it demands a deep, well-resourced team with both macro insights and deep bottom-up security selection expertise. It’s the combination of experience managers, large global teams and precise execution that enables performance to persist through cycles.

¹ Source: Morningstar, six largest Morningstar equity categories, active funds underperformed their passive counterparts for the 10 years ended December 31, 2023 on an equal-weighted basis. Categories are Large-cap growth, large-cap value, large-cap blend, mid-cap growth, mid-cap value, mid-cap blend. Past performance is no guarantee of future results. Also see S&P Dow Jones Indices, SPIVA report as of December 31, 2024. Past performance is no guarantee of future results.

² MSIM research based on Morningstar U.S. fund data, comparing actively managed fund net returns with passive funds, based on the lowest expense ratio share class performance on an equal weighted basis, as of December 31, 2023.

The study considered a Morningstar universe comprising 793 active funds with $1,438 billion in assets under management (AUM) and 137 passive funds, with $1,097 billion AUM, including both open end funds and ETFs, in nine well-defined and relatively homogeneous fixed income categories. 

We made several adjustments to ensure balanced and fair comparisons, starting with analysis of the benchmarks used by all funds – active and passive – within a certain category. We then excluded funds benchmarked to indexes that don’t represent the general characteristics of the category. This included indexes that generally did not match the category’s overall characteristics based on criteria such as credit, duration, geographic or asset class. We further applied an AUM floor of $500M (as of 1/31/2024).

After applying the benchmark and AUM filters, the study’s universe included 289 active funds with $1,226 billion AUM, or 85% of the original, and 38 passive funds with $982 billion AUM, or 90% of the original. Past performance is no guarantee of future results.

³ MSIM research based on Morningstar U.S. fund data, comparing actively managed fund net returns with passive funds, based on the lowest expense ratio share class performance on an equal weighted basis, as of December 31, 2023.

The study considered a Morningstar universe comprising 793 active funds with $1,438 billion in assets under management (AUM) and 137 passive funds, with $1,097 billion AUM, including both open end funds and ETFs, in nine well-defined and relatively homogeneous fixed income categories. 

We made several adjustments to ensure balanced and fair comparisons, starting with analysis of the benchmarks used by all funds – active and passive – within a certain category. We then excluded funds benchmarked to indexes that don’t represent the general characteristics of the category. This included indexes that generally did not match the category’s overall characteristics based on criteria such as credit, duration, geographic or asset class. We further applied an AUM floor of $500M (as of 1/31/2024).