How to calculate a 200-Day SMA with Python 3 and MetaTrader 5

Automated Trading Bot with MetaTrader5 and Python

There are a ton of signals to analyze when using quantitative analysis for stock/crypto/futures/FOREX trading!

About This Series

This series demonstrates the automated analysis of 8 different market signals.

Using Python 3, Python Pandas, and MetaTrader5, I’ll show you how to calculate 8 common signals.

All code for this tutorial can be found on my GitHub, and I’ve included working code samples throughout (use at your own risk, give me a shout-out if you do).

How to Connect to MetaTrader 5 with Python

Learn the two steps required to connect effectively to MetaTrader 5 with Python.

The Disruption ContinuumJames Hinton

What You Need

Requirements and assumed knowledge as follows:

• Already connected to MetaTrader 5.
• Windows 10 or above. For reasons known only to MetaTrader, the Python API only works on Windows 😊
• Python 3. This series was built with Python 3.10

The 200-Day SMA

Introduction to the SMA

The Simple Moving Average (SMA) is a popular signal amongst traders. The signal is often used to indicate the support or resistance to price movements. It’s one of the most common trendlines to be seen on a trading chart.

While the SMA can be calculated on any timeframe, it is commonly applied to the close price of a series of days. The three most common time periods are:

• 50-day SMA
• 100-day SMA
• 200-day SMA

In this episode, I’ll show you how to calculate the 200-day SMA.

How to Calculate

How to Code

Generic SMA Function

The first step will be to build a generic SMA calculator. This will calculate the SMA for a defined number of candles across a specified timeframe. I’ll use Pandas to calculate the average (mean).

Here’s the code:

import mt5_interface
import pandas


# Function to search for a defined number of candles across a specified timeframe.
def generic_sma_calculator(symbol, timeframe, num_candles):
    # Retrieve the raw data from MT 5
    raw_data = mt5_interface.query_historic_data(symbol=symbol, timeframe=timeframe, number_of_candles=num_candles)
    # Convert the raw data into a Pandas Dataframe
    sma_data = pandas.DataFrame(raw_data)
    # Calculate the mean of rows
    sma = sma_data['close'].mean()
    # Return the mean
    return sma

Note. Check out the mt5_interface.py file if you’re looking for how to connect to MT5.

To demonstrate how this fits into __main__ check out this Gist:

import json
import os
import mt5_interface
import generic_sma


# Set up the import filepath
import_filepath = "settings.json"


# Function to import settings from settings.json
def get_project_settings(importFilepath):
    # Test the filepath to sure it exists
    if os.path.exists(importFilepath):
        # Open the file
        f = open(importFilepath, "r")
        # Get the information from file
        project_settings = json.load(f)
        # Close the file
        f.close()
        # Return project settings to program
        return project_settings
    else:
        return ImportError


# Main function
if __name__ == '__main__':
    # Import project settings
    project_settings = get_project_settings(import_filepath)
    # Start MT5
    mt5_interface.start_mt5(project_settings["username"], project_settings["password"], project_settings["server"],
                            project_settings["mt5Pathway"])
    mt5_interface.initialize_symbols(project_settings['symbols'])

    # Queries
    sma = generic_sma.generic_sma_calculator(symbol=project_settings['symbols'][0], timeframe="H1", num_candles=50)
    print(sma)

200-Day SMA Function

Abstracting this function, you can create a 200-Day SMA in 2 lines of code (I’ve included the import statement and comments in the code sample below):

import generic_sma


# Function to calculate a 50-day SMA
def calc_200_sma(symbol):
    return generic_sma.generic_sma_calculator(symbol=symbol, timeframe="D1", num_candles=200)

If you update your main.py to import simple_ma_200 and __main__ to use this new function, you’ll get an outcome similar to the below (the number will be different depending on what day and symbol you use):

Wrapping Up

All sorted! You can now include a 200-Day SMA into your Python Trading Bot. Let me know in the comments how you plan on using it!

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