chanlun

To identify Chanlun buy and sell signals from price data, feed OHLCV inputs into the engine to automatically detect FX, BI, and ZS structures. It classifies 3/5/7/9/11-bar patterns and outputs first, second, and third buy/sell signals for trading decisions.

Multi-timeframe Chanlun pattern recognition applies the czsc library to detect fractals, strokes, and central pivots across different time periods simultaneously. This mechanism classifies bar patterns to pinpoint trend reversal points and generate robust trading signals.

Yes, you can use automated Chanlun analysis for crypto and futures markets. The engine supports multi-period analysis for different markets, applying consistent pattern classification to generate trading signals across various asset types.

To classify 3, 5, 7, 9, and 11-bar Chanlun patterns, the engine processes price data to detect structural fractals and strokes. It automatically categorizes these multi-bar combinations and triggers layer-specific buy and sell signals for strategy execution.

The czsc library requires standard OHLCV price data as input to perform Chanlun signal detection. Once provided, it automatically processes the open, high, low, and close values to identify central structures and output automated trading signals.

A limitation of automated Chanlun pattern detection is its reliance on accurate OHLCV data to correctly identify FX, BI, and ZS structures. Signal robustness depends on market volatility, and outputs are designed for automated workflows rather than guaranteeing profit.