Python and MACD Trading Strategy: Backtest, Rules, Code, Setup, Performance
Python is one of the most popular programming languages in finance. It is widely used for data analysis, machine learning and, of course, backtesting trading strategies.
Today we will show you how to calculate and backtest a MACD, Moving Average Convergence/Divergence (MACD), trading strategy using Python. As you will see, it doesn’t take a computer science degree to do it.
In this article, we are going to backtest a MACD trading strategy using Python: from downloading data from Yahoo Finance and calculating the MACD to generating the strategy returns and plotting the results.
Related reading:
Python-related resources
We have written many articles about Python, and you might find these interesting:
- Python Backtesting Trading Strategies (Plenty of examples with code and images)
- Get Started With Python Making Trading Strategies (Step By Step)
- How To Download Data For Your Trading Strategy From Yahoo!Finance With Python
- Best Python Libraries For Algorithmic Trading – Examples
- How To Measure Skewness Of A Trading Strategy Using Python
- Python Bollinger Band Trading Strategy: Backtest, Rules, Code, Setup, Performance
- Python and Trend Following Trading Strategy
- Python and RSI Trading Strategy
- Python and Momentum Trading Strategy
- How To Make An Average True Range (ATR) Trading Strategy In Python
- How To Build A Trading Strategy From FRED Data In Python
- How To Measure Skewness Of A Trading Strategy Using Python
- How To Do A Monte Carlo Simulation Using Python
Downloading historical data from Yahoo Finance
We are going to download Apple’s historical data from Yahoo Finance using the yfinance library. If you want to learn more about how to use yfinance to download not only historical prices but also fundamental data such as dividends, income statements and multiples,