股海罗盘 - A股股票量化分析

Stock Compass aims to address three major pain points for A-share investors: unclear signal effectiveness, severe information fragmentation, and difficulty in preserving analysis results. Through a self-learning quantitative engine, it backtests over 600,000 historical signals for each stock, attaching a clear historical match rate progress bar to each current signal, allowing users to intuitively understand the signal's past performance. Simultaneously, it integrates comprehensive data across 17 dimensions including market quotes, capital flows, technical indicators, and financials, and offers a one-click DOCX report generation feature with K-line charts, significantly enhancing analysis efficiency.

Usage is straightforward: users simply input a stock code or name, and Stock Compass automatically runs its quantitative engine to generate comprehensive analysis results including historical match rates, five types of pattern charts, ETF quadrant linkage analysis, and cross-validation with brokerage research reports. Users can obtain a structured, in-depth report without switching between different software or data sources.

This tool is well-suited for individual investors, quantitative researchers, and financial analysts with some understanding of the A-share market who wish to optimize investment decisions using data and technology. It is particularly suitable for users tired of trading based on intuition and seeking historical data support for every buy/sell decision.

Usage Recommendation: It is recommended to use this tool as an auxiliary verification aid for investment decisions, not as a sole signal source. Users should interpret the pattern mining and match rate data in reports in conjunction with their own risk preferences and market understanding. Note: past performance does not indicate future results; all analysis should be comprehensively judged alongside the current macroeconomic environment.