,

@arnoldo.moen

To calculate the Average True Range (ATR) using Python, you can use the following code snippet:

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import pandas as pd import numpy as np def calculate_atr(df, period=14): df['HL'] = abs(df['High'] - df['Low']) df['HC'] = abs(df['High'] - df['Close'].shift(1)) df['LC'] = abs(df['Low'] - df['Close'].shift(1)) df['TR'] = df[['HL', 'HC', 'LC']].max(axis=1) atr = df['TR'].rolling(window=period).mean() return atr # Load historical price data data = pd.read_csv('historical_data.csv') # Calculate ATR with default period of 14 data['ATR'] = calculate_atr(data) print(data) |

In this code snippet:

- We define a function calculate_atr that takes a DataFrame of historical price data as input and calculates the ATR using the typical price range for each period.
- We calculate the True Range (TR) by finding the maximum value between the High-Low range, High-Previous Close range, and Low-Previous Close range.
- We calculate the ATR by taking the rolling mean of the True Range over a specified period.
- Finally, we apply the calculate_atr function to our historical price data and store the ATR values in a new column.

You can adjust the `period`

parameter in the `calculate_atr`

function to change the period over which the ATR is calculated.

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