Algorithmic Trading with Python: Machine Learning strategies
Algorithmic Trading with Python: Machine Learning strategies, Artificial intelligence / Machine Learning for algorithmic trading. MetaTrader 5 bots included!
You already know python, and you want to monetize and diversify your knowledge?
You already have some trading knowledge, and you want to learn about artificial intelligence in algorithmic trading?
You are simply a curious person who wants to get into this subject?
If you answer at least one of these questions, I welcome you to this course. For beginners in python, don’t panic! There is a python course (small but condensed) to master this python knowledge.
In this course, you will learn how to program strategies from scratch. Indeed, after a crash course in Python, you will learn how to implement a system based on Machine Learning (Linear regression, Support Vector Machine).
Once the strategies are created, we will backtest them using python. So that we know better this strategy using statistics like Sortino ratio, drawdown the beta… Then we will put our best algorithm in live trading.
You will learn about tools used by both portfolio managers and professional traders:
- Artificial intelligence algorithm
- Apply Machine Learning in Live Trading
- Predict stock prices using Machine Learning
- Live trading implementation
- Import financial data
- Linear Regression Algorithm
- Support Vector Machine (SVM)
- How to do a backtest
- The risk of a stock
- What is a long and short position
- Sharpe ratio
- Sortino ratio
- Alpha coefficient
- Beta coefficient
Why this course and not another?
- It is not a programming course nor a trading course. It is a course in which programming is used for trading.
- A data scientist does not create this course, but a degree in mathematics and economics specialized in Machine learning for finance.
- You can ask questions or read our quantitative finance articles simply by registering on our free Discord forum.
Without forgetting that the course is satisfied or refunded for 30 days. Don’t miss an opportunity to improve your knowledge of this fascinating subject.