Python Code — Elliott Wave

Ready to code? Clone the repository, adjust the Fibonacci thresholds, and let me know in the comments how your automated wave counter performs on the current Bitcoin rally.

The coder decides to build a "Wave Hunter." They start by importing matplotlib to handle the price data and to grab historical stock quotes. The hardest part is the Rule Engine

Elliott proposed that markets move in a structure. A fractal is a geometric shape that can be split into parts, each of which is a reduced-size copy of the whole. In the context of markets, this means that a large trend is composed of smaller trends, which are composed of even smaller trends. elliott wave python code

# Annotate wave numbers (first 5 waves if exist) waves = result['waves'] for i, wave in enumerate(waves[:5]): mid_idx = (wave['start_idx'] + wave['end_idx']) // 2 mid_price = (wave['start_price'] + wave['end_price']) / 2 plt.text(mid_idx, mid_price, str(i+1), fontsize=12, fontweight='bold', bbox=dict(facecolor='yellow', alpha=0.7))

return True

# Rule 1: Wave 2 retrace < 100% of Wave 1 if w2['magnitude'] >= w1['magnitude']: return False

This function reduces thousands of candles to a manageable series of turning points. The lookback parameter is crucial; a lower value detects more noise, a higher value catches the major trend. Ready to code

import numpy as np import pandas as pd from scipy.signal import argrelextrema from typing import List, Tuple, Dict, Optional