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fund-analysis

Calculate fund performance metrics and analyze investment styles for FOF portfolios.

Updated May 25, 2026
Search Tags:#style analysis#performance evaluation#fund analysis#ETF selection#manager assessment#FOF composition
One-click install
npx skills add https://github.com/NigarumOvum/AutoTrading --skill fund-analysis-nigarumovum
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fund-analysis
Source: https://github.com/NigarumOvum/AutoTrading/tree/main/Vibe-Trading/agent/src/skills/fund-analysis
Command: npx skills add https://github.com/NigarumOvum/AutoTrading --skill fund-analysis-nigarumovum

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the comprehensive analysis and selection of funds, including performance evaluation, style analysis, and manager assessment, providing insights into sustainable outperformance.

Core Features & Use Cases

  • Fund Performance Analysis: Evaluate the performance of mutual funds, private funds, and ETFs using multiple metrics like Sharpe ratio, information ratio, and Calmar ratio.
  • Style Analysis: Perform Sharpe style box analysis and detect style drift in fund managers.
  • Manager Evaluation: Assess the investment style and performance of fund managers.
  • FOF Composition: Build diversified fund of funds (FOF) portfolios.
  • ETF Selection: Evaluate tracking efficiency of ETF products.
  • Use Case: Imagine you are a financial advisor looking for high-performing funds for your clients. Use this Skill to screen and select funds based on various criteria, including performance, risk, and style.

Quick Start

Use the fund-analysis skill to evaluate the performance and style of a specific fund, 'Easyfund Blue Chip Mixed Fund (005827)'.

Frequently Asked Questions about fund-analysis

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

FAQPage Schema
How do I automate fund analysis and calculate performance metrics like the Sharpe ratio?▼

Automating fund analysis involves calculating performance metrics like the Sharpe ratio, information ratio, and Calmar ratio to evaluate mutual funds, private funds, and ETFs. This provides insights into sustainable outperformance and risk assessment.

What is Sharpe style box analysis and how does it detect style drift in fund managers?▼

Sharpe style box analysis is a technique that identifies a fund manager's investment style by decomposing returns. It detects style drift by revealing when a manager deviates from their stated investment mandate over time.

Can I use Python with pandas and numpy to build a fund of funds portfolio?▼

Yes, you can use Python with pandas, numpy, and scipy to build a diversified fund of funds portfolio. These libraries support the advanced quantitative analysis needed for asset allocation and investment management workflows.

How do I evaluate ETF selection and tracking efficiency using Python?▼

Evaluating ETF selection and tracking efficiency involves calculating the divergence between the ETF's returns and its underlying benchmark index. Python libraries like pandas and numpy automate this quantitative analysis to identify optimal ETF products.

Does this fund analysis approach support private funds and mutual funds simultaneously?▼

Yes, this fund analysis approach supports evaluating the performance of mutual funds, private funds, and ETFs simultaneously. It applies standardized metrics across different asset classes for comprehensive portfolio screening.

What are the limitations of using pandas and scipy for manager assessment and style analysis?▼

While pandas and scipy handle quantitative style analysis and manager assessment, limitations arise when integrating proprietary data feeds or non-standard financial datasets, which may require additional proprietary libraries for advanced analysis.

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