Acquire Free Financial Market Data with Cutting-Edge Python Libraries

A May 2017 Economist cover declared data to be the world’s most valuable resource. It’s none truer than in algorithmic trading. As algorithmic traders, it’s our job to acquire and make sense of billions of rows of market data for use in trading algorithms. In this context, it’s crucial to gather high-quality, reliable data that can adequately support trading algorithms and market research. Luckily for us, it’s possible to acquire high-quality data for free (or nearly free).

This chapter offers recipes for a series of different Python libraries—including the cutting-edge OpenBB Platform—to acquire free financial market data using Python. One of the primary challenges most non-professional traders face is getting all the data required for analysis together in one place. The OpenBB Platform addresses this issue. We’ll dive into acquiring data for a variety of assets, including stocks, options, futures (both continuous and individual contracts), and Fama-French factors.

One crucial point to remember is that data can vary across different sources. For instance, prices from two sources might differ due to distinct data sourcing methods or different adjustment methods for corporate actions. Some of the libraries we’ll cover might download data for the same asset from the same source. However, libraries vary in how they return that data based on options that help you preprocess the data in preparation for research.

Lastly, while we’ll focus heavily on mainstream financial data in this chapter, financial data is not limited to prices. The concept of “alternative data,” which includes non-traditional data sources such as satellite images, web traffic data, or customer reviews, can be an important source of information for developing trading strategies. The Python tools to acquire and process this type of data are outside the scope of this book. We’ve intentionally left out the methods of acquiring and processing this type of data since it’s covered in other resources dedicated to the topic.

In this chapter, we’ll cover the following recipes:

• Working with stock market data with the OpenBB Platform
• Fetching historic futures data with the OpenBB Platform
• Navigating options market data with the OpenBB Platform
• Harnessing factor data using pandas_datareader