Help 🆘 Scanning through 20 stock research reports, checking K-lines, and browsing financial news before the market opens every day was literally exhausting me 😭
That's until I discovered this open-source gem — daily_stock_analysis — a large language model (LLM)-based stock analysis system that runs once a day, covers 20 stocks in 30 minutes, and saves you hours of manual work 💪
What Is This Tool? 🤔
It's an LLM-powered multi-market stock analysis system that supports A-shares (China), Hong Kong stocks, and US stocks.
Open-source and free, with 3,912 stars on GitHub and an incredibly active community.
It's suitable for developers with some Python experience, but even beginners can follow the tutorial to get it running.
Core Features Breakdown (Super Practical) 🔥
1️⃣ One-Click Market Data Retrieval 📊
Configure your stock pool, run a command, and instantly get technical analysis scores.
Moving averages, MACD, RSI — all analyzed automatically.
Even volume changes are flagged for you.
2️⃣ Real-Time News Sentiment Analysis 📰
Automatically fetches the day's news and analyzes positive vs. negative sentiment.
For example, if Moutai 1935's wholesale price recovers, it's immediately marked as "positive."
No more manually scrolling through financial apps.
3️⃣ AI-Powered Decision Recommendations 🤖
Combining technical indicators with news sentiment, the LLM outputs actionable suggestions.
"Short-term volatility, mid-term focus on consumption recovery, hold and observe — no additional positions."
It's like having an analyst write you a daily brief.
4️⃣ Automated Push Notifications 📲
Supports scheduled tasks — runs automatically before the market opens each day.
Results can be pushed to email, DingTalk, or WeCom.
You can review your analysis report while still in bed.
Real-World Experience (Pros + Cons) ⚖️
👍 Pros:
Time-saving! 20 stocks analyzed in 90 seconds — previously took me 2 hours manually.
Open-source and free, with low running costs. Using gpt-4o-mini costs only $0.1 per run.
Multi-market support — A-shares, Hong Kong stocks, and US stocks all covered.
👎 Cons:
Setup requires some configuration — beginners need to modify
config.yaml.LLMs occasionally hallucinate news — you'll need to add validation logic.
Hong Kong stock data may be missing for obscure tickers — manual fallback required.
For 50+ stocks, run in batches — otherwise token consumption becomes too high.
Who Should Use This? 🎯
✅ Retail investors who manually scan research reports daily.
✅ Quant enthusiasts who know Python.
✅ Investors looking to use AI for decision support.
❌ Absolute beginners (learn basic Python first).
❌ Anyone expecting it to generate easy money (this is not a trading signal generator).
Final Thoughts 📝
This tool is more like an "automated assistant that reads the market for you every day."
It's not a get-rich-quick solution, but it can free you from the overwhelming flood of information.
Rating: 4.2/5 — definitely worth trying.
Want to see my full configuration tutorial and the pitfalls I encountered? Check out my detailed video guide on my homepage 🎬
Drop a comment below — what tools do you use for stock analysis? 👇
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