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fund-analysis

Analyze fund performance and style drift using quantitative metrics and regression models.

Updated Jul 8, 2026
Search Tags:#investment#risk-management#etf#alpha#fund-analysis#fof
One-click install
npx skills add https://github.com/hxhyyy/Vibe-Trading --skill fund-analysis-hxhyyy
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fund-analysis
Source: https://github.com/hxhyyy/Vibe-Trading/tree/main/agent/src/skills/fund-analysis
Command: npx skills add https://github.com/hxhyyy/Vibe-Trading --skill fund-analysis-hxhyyy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy.

What problem does it solve?

This Skill addresses the difficulty of evaluating public and private funds by providing a rigorous framework to distinguish between sustainable alpha generation and mere historical luck.

Core Features & Use Cases

  • Performance & Risk Assessment: Calculate key metrics like Sharpe, Sortino, and Calmar ratios to evaluate risk-adjusted returns.
  • Style & Drift Detection: Utilize Sharpe style box analysis and rolling regression to identify investment styles and detect style drift.
  • FOF Construction: Build and rebalance Fund-of-Funds portfolios using multi-dimensional screening and asset allocation strategies.

Quick Start

Use the fund-analysis skill to evaluate the performance and style consistency of the fund with code 005827 over the last three years.

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 distinguish alpha from historical luck?▼

To evaluate fund performance and distinguish sustainable alpha from luck, this skill applies quantitative metrics and regression models to analyze historical returns, risk-adjusted performance, and management capability.

How do I detect investment style drift using rolling regression?▼

Detect investment style drift by utilizing Sharpe style box analysis and rolling regression, which identify changing asset exposures and investment styles over a specified time period.

Can I calculate Sharpe, Sortino, and Calmar ratios for fund analysis using Python?▼

Yes, you can calculate Sharpe, Sortino, and Calmar ratios for fund analysis to assess risk-adjusted returns, leveraging statistical computation capabilities from pandas, numpy, and scipy.

How do I build and rebalance a Fund-of-Funds portfolio using multi-dimensional screening?▼

Build and rebalance a Fund-of-Funds (FOF) portfolio by applying multi-dimensional screening and asset allocation strategies to select underlying funds that meet specific financial decision-making criteria.

Does this fund analysis approach work with both public and private funds?▼

Yes, this fund analysis approach works with both public and private funds, evaluating their performance, investment style, and management capability through quantitative metrics and regression models.

What Python dependencies are required for quantitative fund analysis and performance attribution?▼

Quantitative fund analysis and performance attribution require pandas, numpy, and scipy for statistical computation, enabling the calculation of risk metrics and execution of regression models.

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