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ajithkumar31082004-bit
ajithkumar31082004-bitCOMMUNITY
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etf-analysis

Analyze ETF data to rank funds by tracking error, liquidity, and cost.

Updated Apr 19, 2026
Search Tags:#analysis#finance#liquidity#etf#tracking-error#quantitative
One-click install
npx skills add https://github.com/ajithkumar31082004-bit/Vibe-Trading --skill etf-analysis-ajithkumar31082004-bit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: etf-analysis
Source: https://github.com/ajithkumar31082004-bit/Vibe-Trading/tree/main/Vibe-Trading-main/agent/src/skills/etf-analysis
Command: npx skills add https://github.com/ajithkumar31082004-bit/Vibe-Trading --skill etf-analysis-ajithkumar31082004-bit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

ETF分析领域往往信息碎片且缺乏系统化的比较框架。本 Skill 提供一个自包含的分析模型，帮助投资者在众多ETF中快速识别高性价比产品，并支持策略组合的设计与评估。

Core Features & Use Cases

  • 筛选与比较：按规模、费率、跟踪误差、流动性等核心指标筛选ETF。
  • 策略应用：支持核心-卫星、行业轮动、Smart Beta 等策略的ETF组合设计与评估。
  • 数据驱动决策：将市场数据转化为可执行的投资建议和再平衡策略。

Quick Start

Analyze a provided ETF list to generate a ranked, actionable portfolio recommendation.

Frequently Asked Questions about etf-analysis

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

FAQPage Schema
How do I evaluate ETF tracking error and liquidity for portfolio construction?▼

Yes, you can analyze cross-border ETF sets alongside domestically listed funds. The analysis applies the same tracking error, liquidity, and cost considerations to evaluate and rank international ETF products for smarter portfolio diversification.

How do I select the best ETFs for a core-satellite or Smart Beta strategy?▼

Selecting ETFs for core-satellite or Smart Beta strategies involves filtering funds by scale, expense ratio, and tracking error. The analysis transforms market data into actionable investment recommendations and rebalancing strategies for these specific portfolio designs.

Can I use a Python workflow to compare ETFs using NAV and IOPV data?▼

Yes, you can use a Python workflow to compare ETFs by calculating and ranking them based on NAV and IOPV data. This data-driven method requires access to specific ETF price feeds to identify high cost-performance products systematically.

What data do I need to run a quantitative ETF analysis and ranking?▼

Running a quantitative ETF analysis requires access to ETF prices, NAV, and IOPV data within a reproducible Python environment. These inputs enable the calculation of tracking errors and liquidity metrics necessary for generating ranked portfolio recommendations.

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