zhulinsen/daily_stock_analysis

Daily Stock Analysis is a Python project that automates daily AI-powered analysis of stocks in the Chinese A-share market, Hong Kong H-share market, and US markets. The problem it solves is that tracking multiple stocks across different markets, aggregating price data, news, sentiment, and fundamental information, and producing a structured investment opinion each day is extremely time-consuming if done manually. This tool automates the entire pipeline and delivers a concise decision dashboard to messaging apps on a schedule. The system works by fetching market data from multiple sources, stock price and technical indicator providers like AkShare, Tushare, and YFinance, and combining them with real-time news search (via APIs like SerpAPI, Tavily, or Brave Search), social sentiment signals, and company announcements. It feeds this combined information to a large language model (configurable to use Gemini, Claude, OpenAI-compatible models, DeepSeek, or local Ollama models) which generates a structured analysis for each stock including a one-sentence conclusion, a score, suggested buy/sell levels, risk alerts, and an action checklist. It also generates a daily market overview covering index performance, sector leaders, and market breadth. The output is pushed automatically to notification channels including WeChat Work bots, Feishu (Lark) bots, Telegram, Discord, Slack, and email. The whole pipeline is designed to run for free on GitHub Actions on a schedule, requiring no server, though Docker and local deployment options are also supported. You would use this project if you actively follow a watchlist of Chinese and US stocks and want a daily AI-generated briefing delivered to your team chat or inbox without doing the aggregation yourself. The project is MIT-licensed Python code running on Python 3.10 or newer.