chan-theory-analysis

What problem does it solve?

It solves the problem of converting raw OHLCV price data into actionable Chan theory trading signals by detecting patterns (fractals), strokes, and consolidation zones automatically.

Core Features & Use Cases

• Chan structure detection: Automatically identifies分型 (fractals), 笔 (strokes), and 中枢 (consolidation zones) from ordered K-lines.
• Buy/Sell signal generation: Produces 一买/一卖, 二买/二卖, and 三买/三卖 signals (including multi-stroke pattern classifications like 3/5/7/9/11 strokes) and maps them to 1 (long) / -1 (short) / 0 (wait).
• Multi-frequency workflow: Works across different K-line frequencies by configuring Freq in czsc, supporting use in backtesting and real-time monitoring pipelines.
• Use Case: Scan BTC daily candles to mark historical turning points and evaluate strategy behavior without manually labeling fractals and strokes.

Quick Start

Provide a time-sorted OHLCV DataFrame (open/high/low/close/volume/amount) and run the signal engine to output a per-timestamp Series of 1 (buy), -1 (sell), or 0 (no signal).