Exponential Moving Average in Python

Learn how to calculate one of the most popular technical analysis measurements in python! Similar to the Simple Moving Average (SMA), the Exponential Moving Average (EMA) is a rolling average value that adds some spice! The EMA has additional weight on values closer to the present day to increase the importance of most recent data. This blog post will show you how to perform Exponential Moving Averages in Python!

Import Needed Libraries

import yfinance as yf 

import pandas as pd 

import matplotlib.pyplot as plt 

from datetime import timedelta, datetime, date

Create a Custom Yahoo Finance GET Data Function

def GetYahooFinanceData(ticker, start, end):

    formatDate = "%Y-%m-%d"

    # Add 1 day to end date

    end = datetime.strptime(end, formatDate)

    end = end + timedelta(days = 1) #add one day to end date to get desired result

    end = end.strftime(formatDate) #converts back to a string type date 

    df = yf.download(ticker, start, end)

    return df 

symbol = 'AAPL'

stock_data = GetYahooFinanceData(symbol,'2022-01-01','2024-02-15')

stock_data

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