Algorithmic trading for beginners: from zero to hero

Algorithmic trading for beginners: from zero to hero, Technical indicators, risk management, Python programming, maths for trading, MetaTrader 5 live trading. Bots included.

Do you want to create algorithmic trading strategies?

You already have some trading knowledge and you want to learn about quantitative trading/finance?

You are simply a curious person who wants to get into this subject to monetize and diversify your knowledge?

If you answer at least one of these questions, I welcome you to this course. All the applications of the course will be done using Python. However, for beginners in Python, don’t panic! There is a FREE python crash course that included mastering Python.

In this course, you will learn how to use technical analysis to create robust strategies. You will perform quantitative analysis to find patterns in the data. Once you will have many profitable strategies, we will learn how to perform vectorized backtesting. Then you will apply portfolio and risk management techniques to reduce the drawdown and maximize your returns.

You will learn and understand  quantitative analysis used by portfolio managers and professional traders:

• Modeling: Technical analysis (Moving average, RSI) and condition combination.
• Backtesting: Do a backtest properly without error and minimize the computation time (Vectorized Backtesting).
• Risk management: Manage the drawdown(Stop loss), combine strategies properly (Strategies portfolio).

Why this course and not another?

• This is not a programming course nor a trading course or a machine learning course. It is a course in which statistics, programming, and financial theory are used for trading.
• This course is not created by a data scientist but by a degree in mathematics and economics specializing in mathematics applied to 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.