Learn how to perform algorithmic trading using Python in this complete course. Algorithmic trading means using computers to make investment decisions. Computer algorithms can make trades at a speed and frequency that is not possible by a human.

After learning the basics of algorithmic trading, you will learn how to build three algorithmic trading projects.

💻 Code: https://github.com/nickmccullum/algorithmic-trading-python

⭐️ Course Contents ⭐️

⌨️ (0:00:00) Algorithmic Trading Fundamentals & API Basics

⌨️ (0:17:20) Building An Equal-Weight S&P 500 Index Fund

⌨️ (1:38:44) Building A Quantitative Momentum Investing Strategy

⌨️ (2:54:02) Building A Quantitative Value Investing Strategy

In this course you will first learn the basics of algorithmic trading. Then you will learn how the IEX Cloud API works. We will use the API to gather data.

The bulk of this course teaches how to build three algorithmic trading projects.

Section 1: Algorithmic Trading Fundamentals

- What is Algorithmic Trading?
- The Differences Between Real-World Algorithmic Trading and This Course

Section 2: Course Configuration & API Basics

- How to Install Python
- Cloning The Repository & Installing Our Dependencies
- Jupyter Notebook Basics
- The Basics of API Requests

Section 3: Building An Equal-Weight S&P 500 Index Fund

- Theory & Concepts
- Importing our Constituents
- Pulling Data For Our Constituents
- Calculating Weights
- Generating Our Output File
- Additional Project Ideas

Section 4: Building A Quantitative Momentum Investing Strategy

- Theory & Concepts
- Pulling Data For Our Constituents
- Calculating Weights
- Generating Our Output File
- Additional Project Ideas

Section 5: Building A Quantitative Value Investing Strategy

- Theory & Concepts
- Importing our Constituents
- Pulling Data For Our Constituents
- Calculating Weights
- Generating Our Output File
- Additional Project Ideas

The first project in the course is an equal-weight S&P 500 screener. The S&P 500 is the world’s most popular stock market index. In this project, you will build an alternative version of the S&P 500 Index Fund where each company has the same weighting.

The second project is a quantitative momentum screener. Momentum investing means investing in assets that have increased in price the most. You will create an algorithm that implements this strategy. First, you will build a strategy that uses a single momentum metric. Then, you will expand to build a more sophisticated strategy that uses multiple metrics together.

The final project is a quantitative value screener. Value investing means investing in stocks that are trading below their perceived intrinsic value. Like the previous project, you will first build a strategy that uses 1 value metric. Then, you will expand to build a more sophisticated strategy that uses 5 different value metrics together.

#python #data-science #machine-learning #developer

38.15 GEEK