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ebrahim-sani
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fund-analysis

Analyzes fund and ETF metrics to optimize portfolio construction.

Updated Apr 10, 2026
Search Tags:#screening#risk-assessment#etf#style-drift#fund-analysis#fof
One-click install
npx skills add https://github.com/ebrahim-sani/trading-automation --skill fund-analysis-ebrahim-sani
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fund-analysis
Source: https://github.com/ebrahim-sani/trading-automation/tree/main/vibe-trading/agent/src/skills/fund-analysis
Command: npx skills add https://github.com/ebrahim-sani/trading-automation --skill fund-analysis-ebrahim-sani

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Many investors lack a systematic method to evaluate fund performance, detect style drift, and construct optimal FOF or ETF portfolios, resulting in missed returns and hidden risks.

Core Features & Use Cases

  • Comprehensive fund metrics: calculates annualized return, Sharpe, Sortino, information ratio, Calmar, and other risk‑adjusted measures.
  • Style analysis: Sharpe style‑box classification, regression‑based style detection, and drift monitoring.
  • Manager assessment: evaluates alpha, risk control, turnover, and concentration.
  • ETF selection: screens tracking error, fees, liquidity, and size.
  • FOF construction: defines asset‑class allocation, diversification rules, and rebalancing triggers.

Use case: An analyst wants to identify top‑performing large‑cap growth funds with stable style and low turnover for inclusion in a balanced FOF.

Quick Start

Ask the fund‑analysis skill to evaluate and rank suitable funds for a balanced FOF portfolio using the latest three‑year performance data.

Frequently Asked Questions about fund-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I evaluate fund performance and detect style drift in a portfolio?▼

You can evaluate fund performance and detect style drift by calculating risk-adjusted metrics like Sharpe and Sortino ratios, and applying regression-based style analysis to monitor consistency against benchmark indices.

What metrics are used for ETF selection and screening?▼

ETF selection screens for tracking error, management fees, liquidity, and fund size to identify optimal funds. This ensures the chosen ETFs accurately replicate benchmark indices while minimizing costs and trading frictions.

Can I use this to construct and rebalance a Fund of Funds (FOF) portfolio?▼

Yes, FOF construction defines asset-class allocation, diversification rules, and rebalancing triggers. It evaluates historical returns and fund holdings to systematically select high-quality funds for a balanced portfolio.

What financial data inputs are required to analyze fund manager performance?▼

Analyzing fund manager performance requires historical returns, benchmark indices, and fund holdings data. These inputs enable statistical calculations for alpha, risk control, turnover, and concentration assessments.

What is the best way to monitor style drift in large-cap growth funds?▼

The best way to monitor style drift is through regression-based style detection and Sharpe style-box classification. This tracks whether a fund's holdings consistently align with its stated large-cap growth category over time.

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