elliott-wave

You automate Elliott Wave detection by applying a zigzag algorithm to financial price series to identify swing points, validate impulse and corrective patterns against Fibonacci ratios, and output buy or sell signals.

Yes, you can use pandas and numpy to process cryptocurrency OHLCV data, applying zigzag detection and Fibonacci ratio checks to validate 5-wave impulse structures and generate trading signals.

The best way to validate ABC corrective patterns is to match 3-wave structures against Elliott's iron rules and Fibonacci ratios using automated detection on historical price series data.

Yes, automated Elliott Wave analysis works with BTC-USDT daily charts by scanning historical OHLCV data to identify swing points and alert you to potential entry points after an ABC pullback.

Swing point detection algorithms find trend reversals by applying a zigzag method to identify key highs and lows, validating wave structures, and generating signals when corrections end or trend tops form.

Automated Elliott Wave pattern validation relies strictly on rule-based detection of historical price series, meaning its accuracy depends on the quality of input data and the clarity of zigzag swing points.