elliott-wave

To detect Elliott Wave patterns, apply a rule-based engine to OHLCV data that identifies swing points via Zigzag, validates 5-wave impulses and ABC corrections using Fibonacci relationships, and outputs buy, sell, or hold signals. This generates a time-aligned integer series per symbol.

Automate trading signals by configuring swing_window, fib_tolerance, and min_wave_bars parameters to validate 5-wave impulses and ABC corrections. The engine processes price data streams and returns an integer series with 1 for buy, -1 for sell, and 0 for hold signals.

Zigzag swing-point detection identifies major swing highs and lows in price data, filtering minor noise to isolate significant turning points. These swing points form the structural foundation for validating Elliott Wave impulses and Fibonacci relationships across timeframes.

Yes, you can validate Elliott Wave patterns across timeframes using Fibonacci relationships by adjusting the fib_tolerance parameter. The engine applies these Fibonacci rules to confirm 5-wave impulse structures and ABC corrections, generating objective signals aligned with your timeframe data.

Configure swing_window to define the lookback for swing points, fib_tolerance to set acceptable deviation for Fibonacci relationships, and min_wave_bars to establish the minimum bars per wave. These parameters control the sensitivity and validation strictness of the impulse and correction detection.

The engine outputs hold signals (0) when the rule-based detection cannot validate a complete 5-wave impulse or ABC correction pattern. This occurs when price data lacks sufficient swing points or fails Fibonacci relationship validation, indicating no actionable trend reversal.