# performance-attribution

Splits portfolio return into explainable pieces: how much came from sector weights, how much from stock picking inside them. Useful when you need to know why a portfolio beat or missed its benchmark.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 668 installs · ★ 218
- Author: JoelLewis
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/JoelLewis/finance_skills/tree/HEAD/plugins/wealth-management/skills/performance-attribution/SKILL.md
- Updated: 2026-07-18
- HTML: https://affpapa.org/en/nevibecode/skills/performance-attribution

## What it does

The skill covers Brinson-Fachler attribution and computes three effects: allocation, selection and interaction. Allocation shows what over- or underweighting a sector against the benchmark contributed, selection shows what picking better securities inside that sector contributed, and interaction captures the joint effect of doing both. The three parts should sum to active return, which is a handy way to check the math.

Factor-based attribution is in there too: returns break into loadings on market, size, value, momentum, quality and low volatility, plus residual alpha. For bonds you get yield return, roll return, curve shift, spread change and credit losses. International portfolios split into local return, currency return and their cross-product. A separate section compares holdings-based, returns-based and transaction-based approaches.

Single-period attribution does not compound, so longer stretches need linking methods — Carino, Menchero or GRAP. The factor model you pick also moves the numbers: Fama-French 3, Carhart 4, Fama-French 5, Barra and Axioma will disagree on the same portfolio. Decide on one model before you run factor attribution, or period-over-period comparisons will drift.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add JoelLewis/finance_skills --skill performance-attribution -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/performance-attribution/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/performance-attribution/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add JoelLewis/finance_skills --skill performance-attribution -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/performance-attribution/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add JoelLewis/finance_skills --skill performance-attribution -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/performance-attribution/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install JoelLewis/finance_skills performance-attribution
```

2. **Manually: put the files in place**
- File: `.github/skills/performance-attribution/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add JoelLewis/finance_skills --skill performance-attribution -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/JoelLewis/finance_skills --path plugins/wealth-management/skills/performance-attribution
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/performance-attribution/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add JoelLewis/finance_skills --skill performance-attribution -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/JoelLewis/finance_skills/tree/HEAD/plugins/wealth-management/skills/performance-attribution/SKILL.md

## When to use it
- break active return into allocation, selection and interaction effects
- tell whether sector bets or stock picking drove the result
- link single-period effects into a geometric return for the full year
- decompose a bond portfolio into income, roll-down and curve shift
- separate local return from currency return in an international book

## Example prompts
- run a Brinson attribution on this portfolio: allocation, selection, interaction
- was it sector bets or stock picking that drove my active return?
- link the quarterly effects with the Carino method so the total matches geometric active return

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 8757d808a36b35cf.

BEGIN THIRD-PARTY FILE 8757d808a36b35cf
```text
---
name: performance-attribution
description: "Decompose portfolio returns into explainable components to identify where value was added or lost. Use when the user asks about Brinson attribution, allocation vs selection effects, factor-based attribution, fixed-income attribution, or currency attribution. Also trigger when users mention 'what drove my returns', 'was it stock picking or sector bets', 'alpha decomposition', 'multi-period linking', 'interaction effect', 'active return breakdown', or ask why their portfolio outperformed or underperformed the benchmark."
---

# Performance Attribution

## Core Concepts

### Brinson-Fachler Attribution (Single Period)
The classic equity attribution model decomposes active return (portfolio return minus benchmark return) into three effects:

- **Allocation effect:** Value added by over/underweighting sectors relative to the benchmark
  - A_i = (w_p,i - w_b,i) × (R_b,i - R_b)
  - Rewards overweighting sectors that outperform the total benchmark
- **Selection effect:** Value added by picking better securities within each sector
  - S_i = w_b,i × (R_p,i - R_b,i)
  - Rewards outperforming the sector benchmark regardless of weight
- **Interaction effect:** Combined effect of both overweighting and outperforming (or vice versa)
  - I_i = (w_p,i - w_b,i) × (R_p,i - R_b,i)
  - Captures the joint benefit of overweighting a sector AND selecting better securities in it
- **Total active return:** R_p - R_b = Σ A_i + Σ S_i + Σ I_i

Where: w_p,i = portfolio weight in sector i, w_b,i = benchmark weight in sector i, R_p,i = portfolio return in sector i, R_b,i = benchmark return in sector i, R_b = total benchmark return.

### Multi-Period Attribution
Single-period attribution does not compound across periods. Geometric linking methods are required:

- **Carino method:** Applies a smoothing factor to make arithmetic effects compound to the correct geometric total
- **Menchero method:** Uses a logarithmic approach for smoother decomposition
- **GRAP (Geometric Return Attribution Program):** Converts arithmetic effects to geometric equivalents
```
END THIRD-PARTY FILE 8757d808a36b35cf

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