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Algorithmic Trading Basics


Algorithmic trading means using computers to make investment decisions.

There are many different types of algorithmic trading (complex and simples).

Here are some of the main players in the algorithmic trading landscape:

  • Renaissance Technologies.
  • AQR Capital Management.
  • Citadel Securities.

Python is the most popular programming language for algorithmic trading. However, Python is slow. This means that is often used as a "glue language" to trigger code that runs in other languages.

One example of this is the NumPy library for python, is popular for performing numerical computing and its data structure which easily allows you to store and manipulate one or two dimensional structures in python. Although it's written for use in Python, his core underlying functionality is written in C.


The process of running a quantitative investing strategy can be broken down into the following steps:

  • 1. Collect data.
  • 2. Develop a hypothesis for strategy.
  • 3. Backtest that strategy. Means formulating the strategy and then seeing how it would perform overtime. There are two ways:
    • Take the strategy back as far as you can.
    • Take the strategy across as many markets as you can.
  • 4. Implement the strategy in production.


An API is an Application Programming Interface. It's a way to a software interact and control the API software.

We could use the IEX Cloud API to gather stocks market data to make investment decisions.

Like most software concepts, APIs are concepts that are best learned through rigorous practice.

Here's is a list of free APIs that you can use to practice interacting with APIs using HTTP request.

S&P 500 Project Overview

The S&P 500 is the world's most popular stock market index.
Many investments founds are benchmarked to the S&P 500. This means that they seek to replicate the performance of this index by owning all

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