Creating an Algorithmic Trading Strategy Using Python and Logistic Regression

An automated machine learning strategy to determine the optimal stocks for algorithmic trading.

Photo by Stephen Leonardi on Unsplash

With the increasing popularity of machine learning, many traders are looking for ways in which they can “teach” a computer to trade for them. This process is called algorithmic trading (sometimes called algo-trading).

Algorithmic trading is a hands off strategy for buying and selling stocks that leverages technical indicators instead of human intuition.

In order to implement an algorithmic trading strategy though, you have to narrow down a list of stocks you want to analyze. This walk-through provides an automated process (using python and logistic regression) for determining the best stocks to algo-trade.

I will dive deeper into the logic and code below, but here is a high-level overview of the process:

1. Import the historical data of every stock using yahoo finance.
2. Pull in over 32 technical indicators for each stock using the technical analysis library.
3. Perform a logistic regression on each stock using 5, 30, and 60…