Forex strategies for algorithmic trading 2022
What you'll learn
- Create Forex strategies from scratch using different techniques like Quantitative technical analysis and Machine Learning
- Import Forex prices directly from your broker
- Put your profitable strategies in Live Trading using MetaTrader 5 and Python
- Plot financial data
- Vectorized Backtesting
- Manage financial data using Pandas
- Create and use template of code to create complexe strategies in few lines of code
- Manage the risk of the currencies
- Incorporate the cost in your analysis
- Combine Forex strategies using portfolio allocation optimization to optimize the Sortino ratio
- Find when you need to stop a Machine Learning algorithm
- Learn some risk management techniques like the Drawdown break strategy (Understand also their strengths and the weaknesses)None. You have to be motivated to lea
- None. You have to be motivated to learn the techniques of quantitative analysts for currencies. That's it!
Do you want to create quantitative FOREX strategies to earn up to 60%/YEAR ?
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 included to master Python.
In this course, you will learn how to use technical analysis and machine learning to create robust forex 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 crypto quantitative analysis used by portfolio managers and professional traders:
Modeling: Technical analysis (Bollinger Bands), Machine Learning (Support vector machine).
Backtesting: Do a backtest properly without error and minimize the computation time (Vectorized Backtesting).
Risk management: Manage the drawdown(Drawdown break strategy), combine strategies properly (Sortino criterion optimization).
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, financial theory, and machine learning 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.
Who this course is for:
Lucas is an independent quantitative trader specializing in Machine learning and data science, and the founder of Quantreo, an algorithmic trading E-learning website (more information in my Udemy profile).
He graduated in mathematics and economics from the University of Strasbourg (France). He has already helped +38.000 students through his online courses and his YouTube channel dedicated to algorithmic quantitative trading.
He has a quantitative trading approach, combining predictive models, financial theory, and stochastic calculus.