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股票分析

Analyze stock groups and market data to generate buy/sell signals and performance reports.

Updated Jan 21, 2026
Search Tags:#reporting#signals#backtesting#TA-Lib#stock-analysis#AkShare#LongPort
One-click install
npx skills add https://github.com/zhuxining/skills --skill -zhuxining
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: 股票分析
Source: https://github.com/zhuxining/skills/tree/main/share-trading-analysis
Command: npx skills add https://github.com/zhuxining/skills --skill -zhuxining

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines stock analysis by integrating group management, market data retrieval (LongPort + AkShare), TA-Lib indicators, and signal generation into a single workflow.

Core Features & Use Cases

  • Group management: Retrieve and manage user stock groups via LongPort, keeping symbols organized.
  • Market data integration: Gather market data from LongPort primarily, with AkShare as a fallback for missing data.
  • Indicator calculation & signals: Compute TA-Lib indicators (EMA, MACD, RSI, ATR, OBV, BBANDS) and generate buy/sell points and performance reports.
  • Reporting & backtesting: Support backtesting and optimization workflows, with summarized reports.

Quick Start

Use the LongPort-based workflow to fetch a first group, pull prices for its symbols, compute indicators, and generate signals. For example: python scripts/longport_groups.py list; python scripts/longport_candlesticks.py --symbol <symbol> --period day --count 100; python scripts/talib_calculator.py

Frequently Asked Questions about 股票分析

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

FAQPage Schema
How do I generate buy and sell signals for a stock portfolio using TA-Lib?▼

You can generate buy and sell signals by computing TA-Lib indicators like MACD, RSI, and EMA on your stock group's market data. This skill processes LongPort groups with Python scripts to calculate technical indicators and output actionable trading signals.

Can I use AkShare to fetch market data if LongPort is missing stock prices?▼

Yes, AkShare works as a fallback data source to retrieve missing market data when LongPort does not provide it. This ensures your stock analysis and indicator calculations remain complete without gaps in historical candlestick prices.

What TA-Lib indicators are supported for stock analysis and backtesting?▼

Supported TA-Lib indicators include EMA, MACD, RSI, ATR, OBV, and BBANDS. These indicators are calculated on retrieved candlestick data to generate buy/sell points and performance reports for backtesting workflows.

Do I need LongPort credentials to manage stock groups and pull candlestick data?▼

Yes, LongPort credentials are required to authenticate and retrieve your user stock groups and market data. Once authenticated, you can use CLI scripts to list groups, pull daily candlesticks, and calculate performance signals.

How do I run a backtesting workflow on stock groups using Python scripts?▼

You can run backtesting workflows by executing Python CLI scripts to fetch candlesticks, calculate TA-Lib indicators, and generate summarized reports. This process evaluates buy/sell signals against historical market data to optimize trading strategies.

What is the best way to organize stock symbols for automated technical analysis?▼

The best way is to use LongPort group management to retrieve and organize your stock symbols. This keeps your symbols structured for automated market data retrieval, indicator calculation, and signal generation workflows.

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