How To Compute Moving Average Convergence Divergence (MACD) using Python?

by ervin.williamson , in category: SEO Tools , 3 months ago

How To Compute Moving Average Convergence Divergence (MACD) using Python?

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2 answers

by ebudoragina , 3 months ago

@ervin.williamson I usually use the code below to calculate MACD for any stock in python, or you can find already calculated on the websites like https://finquota.com/AAPL/ (Apple) and click "Add Indicator"


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import pandas as pd


def compute_macd(data, short_window=12, long_window=26, signal_window=9):
    # Calculate short and long moving averages
    short_ema = data.ewm(span=short_window, adjust=False).mean()
    long_ema = data.ewm(span=long_window, adjust=False).mean()
    
    # Compute MACD line
    macd_line = short_ema - long_ema
    
    # Compute signal line
    signal_line = macd_line.ewm(span=signal_window, adjust=False).mean()
    
    # Compute MACD histogram
    macd_histogram = macd_line - signal_line
    
    return macd_line, signal_line, macd_histogram


# Example usage
# Assuming 'data' is a pandas DataFrame with a 'Close' column containing closing prices
# Replace 'data' with your actual data
macd_line, signal_line, macd_histogram = compute_macd(data['Close'])


# Print MACD line, Signal line, and MACD histogram
print("MACD Line:")
print(macd_line)
print("\nSignal Line:")
print(signal_line)
print("\nMACD Histogram:")
print(macd_histogram)


by dustin.green , 3 months ago

@ervin.williamson 

To compute the Moving Average Convergence Divergence (MACD) using Python, you can follow these steps:

  1. Import the necessary libraries:
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import pandas as pd
import numpy as np


  1. Create a function to calculate the MACD:
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def calculate_macd(data, short_period=12, long_period=26, signal_period=9):
    data['EMA_short'] = data['Close'].ewm(span=short_period, adjust=False).mean()
    data['EMA_long'] = data['Close'].ewm(span=long_period, adjust=False).mean()
    data['MACD'] = data['EMA_short'] - data['EMA_long']
    data['Signal'] = data['MACD'].ewm(span=signal_period, adjust=False).mean()
    data['Histogram'] = data['MACD'] - data['Signal']
    return data


  1. Read the data from a CSV file or any other source:
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data = pd.read_csv('path/to/data.csv')


  1. Call the calculate_macd function with your data:
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data = calculate_macd(data)


  1. Print or visualize the MACD values:
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print(data[['Close', 'MACD', 'Signal', 'Histogram']])


By following these steps, you will be able to compute the Moving Average Convergence Divergence (MACD) using Python. You can further modify the function or parameters to suit your specific needs and preferences.