Best Python Libraries For Algorithmic Trading (Examples)
Libraries are an essential part of Python that makes programming faster and easier for developers. These two qualities are especially relevant in Algorithmic Trading.
That’s why, in this article, we will explore some of the best algorithmic trading libraries in Python, including those to download data, manipulate data, perform technical analysis, and backtest trading strategies.
What is a Python library?
Think of a Python library as a box of tools that contains different sets of ready-made code. This code can be used over and over again in various programs.
This makes it easier and more convenient for programmers because they don’t have to write the same code multiple times for different programs.
Python libraries are really important, especially in areas like Machine Learning, Data Science, and Algorithmic Trading.
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
- 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
- Python and MACD Trading Strategy: Backtest, Rules, Code, Setup, Performance
- How To Measure Skewness Of A Trading Strategy Using Python
- How To Do A Monte Carlo Simulation Using Python
Python Libraries for Downloading Stock Data
The most popular library to download data is yfinance. This library allows users to download the historical data of any stock or ETF from the Yahoo Finance web