What really drives alpha in active bonds and equities

In two recent research papers (see SSRN here for bonds and here for equities), Robeco’s Chief Quant Researcher David Blitz examines this question across both fixed income and equity markets. He takes a research-driven perspective on portfolio construction by stepping back and asking: What is driving returns? Is it intentional? Is it proportional to the risks taken?

Drawing on a large dataset of active funds from the eVestment database over the 2015-2024 period, he analyzes how active returns move relative to peers and what underlying factors explain differences in performance.

The findings reveal striking similarities across asset classes. While the dynamics differ across segments of the market, in both bonds and equities, active returns show strong co-movement and are often driven by common structural exposures rather than purely independent security selection.

For example, in investment grade credit, systematic tilts toward credit risk and duration explain much of the dispersion in returns. In high yield, by contrast, simply taking more risk does not reliably lead to outperformance. In equities, off-benchmark factor exposures such as size, style and regional tilts play a similar role.

To examine what drives active credit returns, he constructs a peer-group performance series by taking the average monthly outperformance of all credit managers and then measures how individual funds are exposed to that collective performance. The results show that around 90% of funds exhibit a positive beta to their peers’ performance, meaning that when peers outperform, most funds tend to outperform as well. In practice, because these common exposures also drive deviations from the benchmark, they become a major source of tracking error and explain a substantial part of active returns.

Further analysis reveals that across US, global and euro bond funds, active returns move together far more than they would if managers were independently selecting bonds. Blitz attributes this co-movement to two common structural positions: running shorter duration than the benchmark and holding more risky, higher-yielding bonds. In practice this often means underweighting government bonds and higher-quality credit, while overweighting lower-quality spread assets.

The result is a clear pattern, as shown in Figure 1. Funds tend to perform well when yields rise, reflecting their shorter duration positioning, and when spreads tighten, reflecting their higher credit exposure. What appears to be alpha, in many cases, is therefore simply beta to credit risk. Blitz estimates that more than half of the cross-sectional differences in fund returns can be explained by these systematic factor tilts alone.

Firstly, the findings highlight a lack of diversification across the industry. If many managers adopt similar structural positions – for example by taking on more credit risk – their returns will naturally move together. As a result, comparing managers purely on headline performance can be misleading.

Indeed, when consultants rank asset managers, those appearing in the top quartile often carry the largest credit overweights and the shortest duration positions, while managers sitting lower in the rankings tend to be closer to the benchmark.

For investors, this has important consequences, with proper evaluation requiring adjusting for the risks taken and ensuring like-for-like comparisons. For example, a client may believe they own exposure to the US Aggregate Index, yet the portfolio may in reality resemble US Aggregate minus Treasuries plus additional exposure to BBBs, BBs, CoCos and new issuance.

Thus, performance should not be viewed in isolation. Understanding the underlying risk exposures in portfolios, and assessing returns on a risk-adjusted basis, is essential for meaningful manager comparison and portfolio construction.

When it comes to high yield, Blitz finds something of a mirror image. High yield managers tend to shy away from the really ‘junky’ bonds like CCCs and Cs and focus more on BBs and Bs – sometimes even BBBs. So in a sense, investment grade managers are moving slightly into high yield territory by taking more credit risk, while high yield managers are leaning slightly toward less risk. The benchmarks are cleanly delineated, but in practice it’s more blurred.

In high yield, returns are less driven by broad market credit exposure and more by issuer selection and risk management. Systematic beta explains far less of the variation in performance than in investment grade, where dispersion is more closely tied to structural credit and duration tilts. Simply put, adding more risk in high yield does not reliably lead to better performance. Instead, performance differences tend to reflect drawdown control, avoiding weaker credits, sector positioning and quality selection.

The findings for active equity funds echo the patterns observed in fixed income. Blitz examined active returns across ten major equity categories, including US large cap, developed markets, emerging markets and global mandates. Once again, the results show strong co-movement in active returns.

Up to 90% of equity funds have a positive beta to the average performance of their peers. In other words, when managers in a given category outperform collectively, most individual funds do too, and when peers struggle, the majority struggle together.

Looking more closely, Blitz finds that many equity funds carry structural exposures that differ from their stated benchmarks. In some cases these are off-benchmark positions: large-cap funds tend to hold small-cap stocks, while developed market funds often have some emerging market exposure. Benchmarks may appear cleanly defined, but in practice portfolio positioning is more blurred.

At the same time, funds also exhibit common factor tilts within their benchmarks. International funds tend to lean toward growth stocks, while US funds display a stronger value bias. These shared factor tilts explain a significant portion of active return dispersion. High active-risk funds show the strongest exposures to common risk factors, while low active-risk funds exhibit more idiosyncratic behavior.

The implication is similar to that in credit: a substantial part of what appears to be alpha can often be traced back to systematic risk exposures rather than purely independent security selection.