performance-attribution
Break down why your portfolio outperformed or underperformed its benchmark by isolating contributions from sector positioning, individual stock picks, and market timing. Performance Attribution uses Brinson decomposition, factor regression, and timing models to reveal the true drivers of excess return across multiple time periods.
Performance Attribution decomposes portfolio excess returns into sector allocation, stock selection, and timing contributions to explain strategy performance.
AI-generated summary based on this skill's SKILL.md
Install
HKUDS/Vibe-Trading/performance-attribution · repository language: Python
git clone https://github.com/HKUDS/Vibe-Trading
cp -r Vibe-Trading/agent/src/skills/performance-attribution ~/.claude/skills/performance-attributionFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
What is performance attribution analysis?
Performance Attribution breaks down why your portfolio outperformed or underperformed its benchmark by isolating contributions from sector positioning, individual stock picks, and market timing. It uses Brinson decomposition, factor regression, and timing models to reveal the true drivers of excess return across multiple time periods.
How does performance attribution analyze stock selection vs market timing?
Performance Attribution decomposes portfolio returns into distinct components: sector allocation effects (how your sector bets performed), stock selection effects (how your picks beat sector benchmarks), and timing contributions (whether you bought/sold at opportune moments). Models like Treynor-Mazuy and Henriksson-Merton specifically isolate market-timing ability from pure security selection skill.
Can performance attribution help with factor exposure and alpha/beta analysis?
Yes. Performance Attribution uses multi-factor regression models to analyze your factor exposure and decompose returns into alpha (skill) and beta (systematic risk). This reveals which factors drove your outperformance and whether excess returns came from factor tilts or genuine stock-picking ability.
What is the Brinson sector attribution model?
Performance Attribution's Brinson decomposition breaks portfolio excess return into sector allocation effects and stock selection effects. It measures how much return came from over/underweighting sectors versus how much came from picking better stocks within those sectors, providing clear visibility into where your edge actually lies.
How does performance attribution detect style drift and rolling performance?
Performance Attribution tracks rolling performance metrics and factor exposures over time windows to detect style drift—unintended shifts in your portfolio's risk profile or factor tilts. Rolling Sharpe ratios, information ratios, and factor loadings reveal whether your strategy remains consistent or has drifted from its intended approach.
What risk-adjusted metrics does performance attribution compare against benchmarks?
Performance Attribution compares your portfolio against appropriate benchmarks using risk-adjusted metrics including Information Ratio (excess return per unit of tracking error), Sharpe ratio, and capture ratios. These metrics contextualize your outperformance relative to the risk you took, separating luck from skill.
SKILL.md
rendered from the published skill — quoted content, verbatim
Performance Attribution Analysis
Overview
Decompose portfolio excess returns into explainable sources: sector allocation, stock selection, factor exposure, timing contribution, and more. This helps explain why a strategy made or lost money, rather than only how much it made or lost.
Brinson Attribution Model
Single-Period Brinson-Fachler Model
Total excess return = portfolio return - benchmark return
Decomposed into three parts:
1. Allocation effect: sector-weight deviation × sector benchmark return deviation
2. Selection effect: stock selection within a sector × sector benchmark weight
3. Interaction effect: weight deviation × stock-selection deviation
Mathematical formulas:
``` Let w_p,i = portfolio weight of sector i w_b,i = benchmark weight of sector i r_p,i = portfolio return of sector i r_b,i = benchmark return of sector i R_b = total benchmark return
Allocation_i = (w_p,i -
(truncated - see the full file via the links below)
Read as markdown · JSON record · Browse the source repository
File tree — 1 file
agent/src/skills/performance-attribution/SKILL.md