Algorithmic Trading & Indicators Beginner

MACD Line, Signal Line & Histogram Momentum Crossover in Python

Calculate Moving Average Convergence Divergence (12, 26, 9 MACD) in Python Pandas and detect histogram zero-line momentum crossovers.

#pandas#numpy

Problem Statement

Waiting for slow SMA crossovers misses early momentum bursts. This vectorized MACD script computes the 12/26 EMA spread, 9-period Signal EMA, and exact Histogram inflection points.

Formula / Core Logic

MACD_Line = EMA(12) - EMA(26) Signal_Line = EMA(MACD_Line, 9) Histogram = MACD_Line - Signal_Line

Installation

pip install pandas numpy

macd-histogram-crossover-signal-python.py

import pandas as pd
import numpy as np

def calculate_macd(df, fast=12, slow=26, signal=9):
    df = df.copy()
    ema_fast = df['Close'].ewm(span=fast, adjust=False).mean()
    ema_slow = df['Close'].ewm(span=slow, adjust=False).mean()
    df['MACD'] = ema_fast - ema_slow
    df['MACD_Signal'] = df['MACD'].ewm(span=signal, adjust=False).mean()
    df['MACD_Hist'] = df['MACD'] - df['MACD_Signal']
    df['Cross_Signal'] = np.where((df['MACD_Hist'] > 0) & (df['MACD_Hist'].shift(1) <= 0), 1, np.where((df['MACD_Hist'] < 0) & (df['MACD_Hist'].shift(1) >= 0), -1, 0))
    return df

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Frequently Asked Questions

Q: How to reduce false MACD signals in downtrends?

Only take bullish MACD crossovers that occur when price is above the 200-period EMA.