financial-data-fetch

Fetch historical OHLCV data for A-share and ETF markets.

1|Updated Dec 14, 2025

Search Tags:#automation #AKShare #data-fetch #ETF #OHLCV #A股

Ready to run

npx skills add https://github.com/YFOOOO/financial_agent --skill financial-data-fetch

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: financial-data-fetch
Source: https://github.com/YFOOOO/financial_agent/tree/main/skills/financial-data-fetch
Command: npx skills add https://github.com/YFOOOO/financial_agent --skill financial-data-fetch

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires akshare, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a unified interface to fetch China's A股 and ETF market data. It streamlines access to OHLCV for stocks and NAV/成交数据 for ETFs, reducing manual data gathering time and ensuring consistent data formats for analysis.

Core Features & Use Cases

Stock Data: 获取 A 股历史 OHLCV 数据，支持自定义日期区间与天数
ETF Data: 获取 ETF 的 NAV、成交量等历史数据
Use Case: 分析师需要最近 60 天的日线数据来回测策略时，只需调用此 Skill 并传入 symbol 和 days 即可

Quick Start

Fetch 60 days of data for symbol '000001' (A 股) using fetch_stock_data.

Frequently Asked Questions about financial-data-fetch

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

FAQPage Schema

How do I fetch historical OHLCV data for China A-share stocks?▼

This Skill fetches historical OHLCV data for A-share stocks using a 6-digit symbol and a days parameter (1–365). Pass your stock symbol and desired lookback period to retrieve a standardized pandas DataFrame with open, high, low, close, and volume fields for backtesting and analysis.

Can I use this Skill to get ETF historical data and net asset value trends?▼

Yes. The Skill retrieves historical ETF data including NAV and trading volume within your specified date window. It validates 6-digit ETF symbols and the days parameter, then routes to the appropriate fetch tool and returns consistent DataFrame format.

What input validation does this Skill perform on stock symbols and time ranges?▼

The Skill validates that symbols are 6-digit numeric values and that the days parameter falls between 1 and 365. Invalid inputs are rejected before routing to the data fetch tool, ensuring reliable retrieval and preventing malformed queries.

How do I automate daily data retrieval for multiple A-share and ETF symbols?▼

Call the Skill with your symbol list and desired days parameter; it handles routing to the correct data source (stock or ETF) and returns standardized DataFrames. Wrap multiple calls in a loop or automation script to refresh data consistently across your portfolio.

Does this Skill work with the AKShare library for Chinese market data?▼

Yes. The Skill uses AKShare as its underlying dependency to access China's A-share and ETF market data. It abstracts the library's complexity into a unified interface that handles symbol validation and routes queries to the appropriate data fetch function.

What data format does this Skill return, and can I use it directly for strategy backtesting?▼

The Skill returns a standardized pandas DataFrame with OHLCV and volume columns, formatted for immediate use in backtesting frameworks. The consistent structure across stock and ETF queries eliminates manual data alignment work.