Daily Stock Analysis is a stock analysis system powered by large language models that automates multi-market equity research and decision-making.
The system addresses the challenge of tracking and analyzing stocks across multiple markets by combining real-time market data, news feeds, and AI-driven analysis into a unified workflow. It aggregates data from multiple sources covering Chinese A-shares, Hong Kong stocks, US equities, Japanese, Korean, and Taiwan stocks, along with ETFs. The core output is an automated decision dashboard that synthesizes AI analysis into actionable insights including buy and sell signals, risk alerts, and trend assessments. The system supports multiple deployment modes including GitHub Actions for cost-free scheduled execution, Docker containers, local task scheduling, and a FastAPI service, with notifications delivered through enterprise WeChat, Feishu, Telegram, Discord, Slack, or email.
Developers should adopt this tool if they manage a watchlist across multiple markets and want daily automated analysis without manual research overhead. The project suits quantitative traders, portfolio managers, and individual investors who prefer systematic decision support over manual chart analysis. The system includes a web and desktop workspace for manual analysis, historical report review, and backtesting, alongside an agent-based strategy interface supporting fifteen built-in analytical approaches. The intelligent import system accepts stock data from images, spreadsheets, and clipboard input with automatic ticker completion.
The project receives issues from both core maintainers and external users, indicating adoption beyond the original team without excessive support burden. Maintainers typically respond to new issues and pull requests within hours. Work in the issue tracker centers on bug fixes, feature enhancements, and automated code improvements.
