Daily Stock Analysis

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GitHub Python MIT

Description

LLM-powered stock analysis system for A/H/US markets with multi-source quotes, real-time news, LLM decision dashboard and multi-channel push notifications.

Key Features

  • Multi-market data aggregation — Supports A-shares, HK stocks, US ETFs with quotes, K-lines, technical indicators, fund flows, chips, news, and fundamentals
  • AI decision dashboard — Generates core conclusions, scores, trends, buy/sell signals, risk alerts, catalysts, and action checklists
  • Agent strategy Q&A — Multi-turn queries with 15 built-in strategies (MA, Chanlun, Wave, Trend, Hotspots, Events, Growth, Expectation), covers Web/Bot/API
  • Web/desktop workbench — Manual analysis, task progress, historical reports, full Markdown, backtesting, position management, config management, light/dark themes
  • Multi-channel push — Enterprise WeChat, Feishu, Telegram, Discord, Slack, email delivery of decision dashboards
  • Smart import & autocomplete — Image, CSV/Excel, clipboard import with stock code/name/pinyin/alias autocomplete

Use Cases

💡 Automatically analyze watchlist stocks after market close and push decision reports to team channels
💡 Individual investors manually analyze stocks and run backtests via the Web workbench
💡 Quant teams use Agent strategy Q&A for multi-round deep technical analysis
💡 Enterprises integrate stock analysis into internal OA systems via API
💡 Track market sector rotation through daily market review on non-trading days

Tags

agent python llm data-processing automation

Categories

📚 RAG Tools

Quick Start

```bash
git clone https://github.com/ZhuLinsen/daily_stock_analysis.git && cd daily_stock_analysis
pip install -r requirements.txt
cp .env.example .env
# Edit .env to configure AI model keys, notification channels, and stock list
python main.py --stocks 600519,hk00700,AAPL
```
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