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We will create an algorithmic trading strategy that earns 50% annually.
What you'll learn:- Use numpy to do scientific calculation
- Use pandas to import and organize data
- Use Matplotlib to visualize data
- Use, create, understand mathematical model
- Machine learning for algorithmic trading
- Features Engineering
- Statistics for finance
- Create an easy-to-reuse backtesting universe
- Automatically take sales and buy positions
- Data import with a API
It is with pride that I offer this data science course for algorithmic trading. It is the fruit of several years of work in the field to truly understand all the subtleties of the world of quantitative finance.
Using libraries will allow you to do complex mathematical calculations applied to finance in just a few lines of code. We will see how to create an algorithm for trading from data import to automatic positions. You will create an algorithm that will yield more than 50% annually on the Nasdaq 100 using an algorithm.
In summary, we will study:
The numpy library to do scientific calculations
The pandas library organize and visualize data
The Matplotlib library to make powerful graphics
Features engineering
Linear regression for finance
Machine vector support
Decision tree
Random Forest
Apply and understand the Sharpe ratio
Apply and understand the Sortino ratio
Understanding the volatility of a stock market asset
Understand and create a backtesting universe that is easy to use
Backtest the strategy using the most know metrics in trading
How to choose the best features for Machine Learning models
The basics in python language to follow the course and to do your own projects after the course.
The basics in python language to follow the course and to do your own projects after the course.
Overview
