Corporate bond portfolios: Are you seeing alpha — or just taking more risk?
Comparing fixed income performance is more complicated than it appears. Differences in duration, spread or credit risk can dominate returns, making it difficult to tell whether apparent outperformance reflects genuine security selection or simply higher risk exposure.
Key takeaways
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Unadjusted fixed income returns often reflect higher risk, not better security selection.
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Risk-neutral portfolios can materially change how sectors and strategies rank.
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Transparent, investable risk adjustment is possible without black-box optimisation.
In a recent Financial Analysts Journal article, Quoniam researchers present a practical way to neutralise these effects using fully investable portfolios. We spoke with Dr Gunther Hahn, CFA, CQA, Fixed Income Portfolio Manager and lead author of the study, about why risk-adjusted performance matters and how investors can apply it in practice.
Why did you feel it was necessary to rethink how fixed income performance is evaluated?
In fixed income, performance comparisons are often taken at face value. If one portfolio outperforms another, it is tempting to assume that this reflects better selection or superior strategy design. But fixed income returns are strongly influenced by a small number of linear risk dimensions, such as duration, spread and duration times spread. If portfolios differ along these dimensions, then comparing raw returns can be misleading. Our motivation was to provide a framework that makes performance comparisons fairer and more informative.
Is this problem particularly acute in credit markets?
Yes, because risk dispersion in credit portfolios is substantial and highly time-varying. Two portfolios investing in similar instruments can still have very different risk profiles. In equities, market beta often dominates the discussion. In fixed income, investors must deal with several risk drivers at once. If these are not controlled for properly, it becomes very difficult to distinguish genuine alpha from compensation for taking more risk.
Many investors already try to control for risk using regressions, leverage or optimisers. Why is that not enough?
Each of these approaches has limitations. Time-series regressions can help analyse exposures, but they do not give you a portfolio you can actually hold. Optimisers are powerful, but they often rely on strong assumptions, produce extreme trades and can be difficult to interpret. Simple leverage-based adjustments typically control for only one dimension of risk and do not result in investable portfolios. As a portfolio manager, I do not just need an estimate — I need a portfolio.
What was missing from a practitioner’s point of view?
A method that allows you to neutralise multiple risk dimensions simultaneously, while preserving the original bond universe and remaining realistic from an implementation perspective. That was the gap we were trying to close.
Your paper proposes a closed-form solution rather than a traditional optimisation. Why was that important?
A closed-form solution is transparent and robust. It makes many small, sensible changes across the portfolio rather than a few large, extreme trades. This is much closer to how real portfolios are managed. The method adjusts weights just enough to match specified risk targets, while keeping the portfolio fully invested and long-only, which is essential in corporate bond markets.
Risk-neutral performance does not mean making returns look better or worse – it means understanding what really drives them and clearly separating alpha from systematic risk.
Dr Gunther Hahn, CFA, CQF, Portfolio Manager Fixed Income
How does this approach relate to existing academic work?
The mathematical foundation builds on earlier work by Richard Roll, originally developed in an equity context. Our contribution was to adapt this framework to fixed income, extend it to multiple risk dimensions such as duration and spread, and develop a practical procedure to eliminate negative weights. This last step is critical, because shorting individual bonds is often impractical or undesirable in real-world portfolios.
What happens to sector performance once risk is properly neutralised?
The rankings change materially. Sectors that look attractive on a raw return basis often lose their leading position once you control for risk exposures. Conversely, more defensive sectors may move up the ranking. This shows that much of what appears to be outperformance is often driven by higher exposure to systematic credit risk rather than superior selection within a sector.
Does that mean investors should avoid higher-risk sectors altogether?
Not at all. The point is not to avoid risk, but to understand it. Risk-adjusted performance allows investors to make conscious decisions. If an investor deliberately wants more spread or duration exposure, that can be a valid choice. But it should be intentional, not hidden in the performance numbers.
How realistic are the resulting portfolios from an implementation perspective?
That was a central concern of our analysis. The portfolios remain long-only, fully invested and based on the original bond universe. We also examine turnover and transaction costs. Adjusting for more risk dimensions naturally increases turnover, but for well-diversified portfolios the results remain economically meaningful and implementable.
Where do you see the most immediate practical applications?
Sector analysis is an obvious one. Rather than discussing spread movements in isolation, investors can compare sector performance on a risk-neutral basis. The method is also very useful for factor research, where it helps separate true factor effects from unintended duration or spread exposures.
Are there areas where this approach could be extended further?
Yes, ESG analysis is a natural extension. ESG scores are linear, just like duration or spread. That means you can deliberately change a portfolio’s ESG profile while holding traditional risk characteristics constant. This allows ESG performance to be evaluated on its own merits, rather than being confounded by unintended risk bets.
Finally, what does this research say about Quoniam’s broader approach to investing?
It reflects our focus on clarity and realism. Rigorous research should lead to practical tools that improve decision-making. Risk-neutral performance is not about making returns look better or worse — it is about understanding what really drives them.
Adjusting for Risk Effects in Fixed Income Portfolios
Dr Desislava Rakova (published previously as Dr Desislava Vladimirova) is a Research Analyst at Quoniam Asset Management GmbH, Frankfurt am Main. Dr Lars Rickenberg is a Data Scientist and Senior Investment Manager in the Private Debt team at Allianz Investment Management in Munich. Dr Gunther Hahn, CFA, CQF is Fixed Income Portfolio Manager at Quoniam Asset Management.
