How do you decompose active return in fixed income to evaluate manager skill versus systematic exposures?

Active return decomposition in fixed income separates the manager's excess return over the benchmark into decision-specific components. This reveals whether outperformance came from deliberate skill or passive factor tilts.\n\nActive Return Components:\n\n`mermaid\ngraph TD\n A[\"Active Return
Portfolio - Benchmark\"] --> B[\"Duration Management
Over/underweight rate risk\"]\n A --> C[\"Yield Curve Positioning
Bullet vs barbell vs ladder\"]\n A --> D[\"Sector Allocation
Corp vs govt vs MBS weights\"]\n A --> E[\"Security Selection
Individual bond picks\"]\n A --> F[\"Trading Activity
Execution and timing\"]\n B --> G[\"Systematic or
intentional bet?\"]\n D --> H[\"Top-down
macro view\"]\n E --> I[\"Bottom-up
credit research\"]\n`\n\nWorked Example:\n\nRothbury Fixed Income Fund returned +4.82% while the Bloomberg Aggregate benchmark returned +3.45%. Active return = +1.37%.\n\n| Decision | Method | Active Contribution |\n|---|---|---|\n| Duration: Portfolio 6.1 vs benchmark 5.8 | (6.1 - 5.8) x benchmark rate return per unit duration | +0.32% |\n| Curve: Barbell vs benchmark bullet | Scenario decomposition of key rate durations | +0.18% |\n| Sector: Overweight IG corporates by 8% | Sector weight diff x sector excess return | +0.54% |\n| Security selection: Outperforming credits | Residual within each sector | +0.28% |\n| Trading: Execution vs mid-market | Transaction cost analysis | +0.05% |\n| Total Active | | +1.37% |\n\nInterpreting the Results:\n\nRothbury's largest active contribution (+0.54%) came from sector allocation, specifically the decision to overweight investment-grade corporates during a period of spread tightening. This is a top-down macro call. Security selection added +0.28%, reflecting bottom-up credit research identifying individual bonds that outperformed their sector peers.\n\nDuration Management:\n\nThe +0.32% from duration is important to evaluate carefully. If the manager's investment policy statement mandates duration within +/-0.5 years of benchmark, this is an intentional active bet. If it was unintentional drift, it should not be credited as skill.\n\nMulti-Period Attribution:\n\nOver multiple periods, the attribution components are not simply additive due to compounding. Geometric linking methods or Carino/Menchero smoothing algorithms distribute the interaction effects across periods to maintain consistency.\n\nInformation Ratio:\n\nActive return divided by tracking error gives the information ratio, which measures the consistency of active returns. A high information ratio (above 0.5) over extended periods indicates genuine skill rather than luck.\n\nPractice active management attribution in our CFA Fixed Income question bank.