managing-fixed-income-attribution

Structures fixed income performance attribution across duration, credit, and sector allocation effects. Use when attributing fixed income returns, analyzing portfolio performance, or decomposing return drivers.

11 stars

Best use case

managing-fixed-income-attribution is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Structures fixed income performance attribution across duration, credit, and sector allocation effects. Use when attributing fixed income returns, analyzing portfolio performance, or decomposing return drivers.

Teams using managing-fixed-income-attribution should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/managing-fixed-income-attribution/SKILL.md --create-dirs "https://raw.githubusercontent.com/CaseMark/skills/main/skills/finance/managing-fixed-income-attribution/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/managing-fixed-income-attribution/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How managing-fixed-income-attribution Compares

Feature / Agentmanaging-fixed-income-attributionStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Structures fixed income performance attribution across duration, credit, and sector allocation effects. Use when attributing fixed income returns, analyzing portfolio performance, or decomposing return drivers.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Managing Fixed Income Attribution

Decomposes fixed income portfolio returns into constituent effects — duration/yield curve, credit spread, sector allocation, and security selection — to explain performance versus a benchmark and identify repeatable alpha sources.

## When To Use

- Preparing monthly or quarterly performance attribution reports for investment committees or clients
- Diagnosing why a fixed income portfolio outperformed or underperformed its benchmark
- Evaluating portfolio manager skill across interest rate positioning, credit selection, and sector rotation
- Supporting compliance reviews that require transparent return decomposition
- Feeding attribution results into risk budgeting or allocation rebalancing decisions

## Inputs To Gather

- **Portfolio holdings** with market values, durations, spreads, and sector classifications at period start and end
- **Benchmark composition** (e.g., Bloomberg US Aggregate, ICE BofA indices) with matching granularity
- **Return series** — total return, price return, and income return for both portfolio and benchmark
- **Yield curve data** — par/spot/forward curves at period start and end (Treasury + swap if applicable)
- **Spread data** — OAS or Z-spread by sector and rating bucket at period start and end
- **Transaction log** — trades executed during the period (for intra-period rebalancing effects)
- **Attribution methodology selection** — Campisi, Brinson-Fachler adapted for fixed income, or factor-based [VERIFY methodology approved by the firm's performance team]

## Workflow

1. **Validate inputs and align classifications**
   - Confirm holdings data reconciles to custodian/accounting NAV
   - Map portfolio and benchmark securities to consistent sector/rating/maturity buckets
   - Verify curve and spread data timestamps match the attribution period boundaries
   - Flag any securities missing key analytics (duration, OAS) and determine proxy approach

2. **Decompose benchmark return into systematic effects**
   - **Income effect**: accrued coupon and pull-to-par for the period
   - **Treasury/yield curve effect**: return attributable to changes in the risk-free curve (shift, twist, butterfly)
   - **Spread effect**: return from aggregate spread changes across the benchmark
   - **Residual**: convexity, roll-down, and any model noise

3. **Compute portfolio-level effects and differentials**
   - Calculate the same return components for the portfolio
   - Derive active return = portfolio total return − benchmark total return
   - Attribute active return across:
     - **Duration/curve positioning**: over/underweight duration and curve placement vs. benchmark
     - **Credit spread allocation**: sector and rating bucket spread bets
     - **Security selection**: bond-level excess return within each bucket after removing systematic factors
     - **Trading/timing**: impact of intra-period transactions vs. buy-and-hold assumption

4. **Reconcile and cross-check**
   - Sum of all attribution effects must reconcile to total active return within an acceptable tolerance (typically ≤ 2 bps)
   - If residual exceeds tolerance, investigate: missing cash effect, FX overlay, derivative overlay not captured, or sector mapping mismatches
   - Compare results against prior-period attribution to detect sign flips or anomalous magnitudes

5. **Synthesize narrative and reporting**
   - Rank effects by absolute contribution to active return
   - Provide plain-language explanation of the top 3 drivers (positive and negative)
   - Highlight any one-off or non-repeatable effects (e.g., a single distressed bond rally)
   - Present results in standardized table format with period-over-period comparison

## Output

- **Attribution summary table**: rows for each effect (income, curve, spread, selection, trading), columns for portfolio return, benchmark return, and active contribution
- **Sector/rating drill-down**: attribution broken out by BICS or GICS sector and by rating tier (AAA, AA, A, BBB, HY if applicable)
- **Curve positioning exhibit**: visual or tabular comparison of portfolio vs. benchmark key-rate duration profile
- **Narrative commentary**: 1–2 paragraph executive summary suitable for client letters or IC memos
- **Reconciliation footnote**: residual amount and explanation if material

## Quality Checks

- Total active return reconciles to the sum of attribution effects within ±2 bps
- Income effect is positive and directionally consistent with portfolio yield vs. benchmark yield
- Duration effect sign matches the direction of rate moves relative to portfolio's duration overweight/underweight
- Spread effect sign aligns with portfolio's credit beta positioning and actual spread movement direction
- No single "residual" or "other" bucket exceeds 20% of total active return without documented explanation
- Sector classifications are consistent between portfolio and benchmark (no mismatches inflating allocation effects)
- [VERIFY] Attribution methodology matches the firm's GIPS-compliant performance presentation standards
- [VERIFY] Return calculations use the pricing source and day-count conventions specified in the IPS or client agreement
- [VERIFY] Derivative overlays (futures, swaps, CDS) are correctly mapped to their economic exposure buckets rather than reported as a single line item

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