harmonic

To detect harmonic XABCD patterns in OHLCV price data, feed your time-series into the signal engine and call the generate method to obtain trading signals at the D point within the PRZ.

You can identify Gartley, Bat, Butterfly, and Crab harmonic patterns using Fibonacci ratios within the five-point XABCD structure to generate actionable trading signals.

Yes, harmonic pattern detection works with crypto, forex, and equity time-series, requiring OHLCV data to identify XABCD patterns and emit D-point signals across these asset classes.

No, you do not need the pyharmonics library to generate D-point trading signals, as the engine includes a deterministic built-in detector that serves as a reliable fallback.

Detecting harmonic patterns in price data requires Python 3.11+ with pandas and numpy installed, alongside either the pyharmonics library or the built-in detector.

Harmonic pattern detection provides proactive entry timing and risk management by identifying specific XABCD Fibonacci structures and generating signals precisely at the PRZ D-point.