Daily Stock Analysis
LLM驱动的 A/H/美股智能分析：多数据源行情 + 实时新闻 + LLM决策仪表盘 + 多渠道推送，零成本定时运行，纯白嫖. LLM-powered stock analysis system for A/H/US markets.
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What is Daily Stock Analysis?
DSA is an LLM‑driven stock analysis system that automatically generates daily individual‑stock decision reports and market recaps for A‑shares, Hong Kong stocks, and US stocks. It ingests multi‑source market data, real‑time news and social sentiment, technical indicators and fundamental data, then synthesizes them into structured scores, trend judgments, operation suggestions and risk alerts. The tool supports on‑demand strategy questioning (Agent问股) from multiple strategy perspectives, and stores historical reports for backtesting and discipline checks. Designed for retail traders, quant hobbyists and small research teams, DSA can run in GitHub Actions or self‑hosted environments and push results to many notification channels.
Daily Stock Analysis pricing
Pricing model: Freemium
The website/project is distributed as an open‑source system; there is no hosted paid plan listed on the site—users run DSA themselves. Running DSA requires your own LLM API key (paid by user if using a commercial LLM) and may use third‑party data APIs that have their own limits or costs. GitHub Actions deployment enables scheduled runs without maintaining a personal server, so software itself is effectively free while API and data usage costs are borne by the user.
Daily Stock Analysis pros
- LLM‑generated structured daily reports for each stock
- Supports A‑share, Hong Kong and US markets
- Aggregates multiple market data sources with fallback chains
- Ingests news, announcements and social sentiment for event context
- Outputs scores, trend judgments and explicit operation suggestions
- Agent问股 lets you ask strategy‑specific follow‑ups on a single stock
- Historical reports saved to SQLite for backtesting and review
- Built‑in backtest metrics: direction accuracy and simulated returns
- Multi‑channel push: WeChat/Feishu/Telegram/Discord/Slack/email
- Can run automatically via GitHub Actions—no server required
- Web UI plus CLI and Bot integration options
- Covers common ETFs in addition to single stocks
- Supports multiple technical strategies (moving averages, Chan theory, waves)
- Detailed daily market recap (index, sector strength, market temperature)
- Open‑source documentation and clear quick‑start instructions
Daily Stock Analysis cons
- Relies on external LLM API keys which may incur cost
- Quality depends on LLM responses and prompt engineering
- Not a turnkey brokerage or execution platform
- May need manual configuration for local stock pools and channels
- Data latency depends on chosen data sources and their limits
- No built‑in paid hosted service—self deployment required for full use
- Backtest engine is basic (SQLite storage) not a full research stack
- Interpretability depends on LLM outputs which can vary day to day
Frequently asked questions about Daily Stock Analysis
Which markets does DSA support?
DSA supports A‑shares (China mainland), Hong Kong stocks and US stocks, and it also covers commonly traded ETFs; you select the market universe when configuring your watchlist.
How does DSA obtain market data and news?
DSA integrates multiple data sources (examples listed include TickFlow, AkShare, Tushare, yfinance and Longbridge) and aggregates news, announcements and social sentiment to provide event context; it also maintains a fallback chain among sources to improve reliability.
What does each daily stock report include?
Each daily report summarizes price/volume context, an LLM‑generated score, trend judgment, operation suggestions, risk alerts, catalyst notes and a checklist for execution or follow‑up, all synthesized from market data, technical indicators and news.
Can I ask follow‑up strategy questions about a specific stock?
Yes—DSA provides an Agent 问股 feature that lets you query a single symbol from perspectives such as moving averages, Chan theory, Elliott waves or momentum strategies via Web, CLI or Bot interfaces.
How are historical reports stored and used?
Daily reports are written into a local SQLite database which supports retrospective checks like direction accuracy, simulated returns and position review to validate strategy discipline and for simple backtesting.
Do I need to run my own server to use DSA?
No—DSA can be deployed using GitHub Actions for scheduled automated runs so you don’t need to maintain a dedicated server, though self‑hosting is also supported for more control.
Which notification channels can DSA push reports to?
DSA can push reports to multiple channels including enterprise WeChat, Feishu, Telegram, Discord, Slack and email, configurable in the deployment settings.
Is DSA a paid hosted product?
No—the project is presented as open source and self‑run; there is no hosted paid tier advertised on the site, but users are responsible for any LLM API or data provider fees they incur.
What kind of backtesting and metrics are available?
DSA records historical decisions and offers simple retrospective metrics such as directional accuracy, simulated returns and position review for validating decision quality and strategy behavior.
How do I get started quickly?
Quick start involves choosing a run channel (for example GitHub Actions), configuring your watchlist, supplying an AI key and setting up notification channels; the docs provide step‑by‑step instructions and example configurations.