chanlun

Automated Chan Theory technical analysis processes raw OHLCV market data to identify K-line patterns, strokes, and centers. It removes manual chart marking by automatically detecting structural buy and sell signals across various financial assets.

Chan Theory buy and sell points are specific trading signals generated by detecting divergence and trend exhaustion in price structures. The first, second, and third category points identify potential trend reversals or continuation points based on automated pattern classification.

The czsc library supports multi-period analysis and pattern classification for various financial markets including stocks and crypto. You can scan large datasets of OHLCV market data to identify trading signals without manually drawing lines on charts.

Detecting Zhongshu centers and Bi strokes requires processing raw OHLCV data through an automated technical analysis engine. The system identifies these price structures to evaluate market trends and generate precise divergence-based trading signals.

Automated Chan Theory analysis supports multi-period pattern classification to evaluate market structure across different timeframes. This allows traders to process OHLCV data and detect structural buy and sell signals across various financial markets simultaneously.

Automated Chan Theory relies entirely on processing OHLCV data into structured buy and sell signals based on historical price structures. It does not account for fundamental market factors and requires prerequisite data formatting to accurately detect strokes, centers, and divergence.