@dana
To compute the Commodity Channel Index (CCI) in Python, you can use the following steps:
- Import the necessary libraries:
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import pandas as pd
import numpy as np
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- Define the function to calculate the CCI:
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def compute_CCI(data, period):
typical_price = (data['High'] + data['Low'] + data['Close']) / 3
moving_average = typical_price.rolling(window=period).mean()
mean_deviation = typical_price.rolling(window=period).apply(lambda x: np.mean(np.abs(x - x.mean())))
CCI = (typical_price - moving_average) / (0.015 * mean_deviation)
return CCI
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- Load your stock price data into a DataFrame:
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data = pd.read_csv('stock_data.csv')
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- Call the compute_CCI function with your data and the period you want to use:
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data['CCI'] = compute_CCI(data, 20)
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- Plot the CCI values to visualize the index on a chart:
By following these steps, you can calculate and visualize the Commodity Channel Index (CCI) for your stock price data in Python.