Forex strategies for algorithmic trading 2022
- Description
- Curriculum
- FAQ
- Reviews
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:
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Modeling: Technical analysis (Bollinger Bands), Machine Learning (Support vector machine).
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Backtesting: Do a backtest properly without error and minimize the computation time (Vectorized Backtesting).
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Risk management: Manage the drawdown(Drawdown break strategy), combine strategies properly (Sortino criterion optimization).
Why this course and not another?
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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.
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This course is not created by a data scientist but by a degree in mathematics and economics specializing in mathematics applied to finance.
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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.
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Introduction -
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Type of Object: Number
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Type of Object: String
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Type of Object: Logical operations / Boolean
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Type of Object: Variable assignment
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Type of Object: Tuple and list
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Type of Object: Dictionary
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Type of Object: Set
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Python structures: If / Elif / Else
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Python structures: For
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Python structures: While
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Functions: Basics of function
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Functions: Local variable
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Functions: Global variable
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Functions: Lambda function
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Introduction
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Manage the data
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Import data from your broker using MT5
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Intuition behind the strategy
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Bollinger bands creation
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Signals computation
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How to verify if we compute our signals correctly
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Compute the profits of the strategy
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Automate your strategy
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Compute profits on a train set
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Compute profits on a test set
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Introduction
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Portfolio optimization: Intuition
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Portfolio optimization: Practice
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Drawdown break strategy: intuition
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Drawdown break strategy: Apply to portolio
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Drawdown break strategy: Apply to portfolio + Individual asset
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Drawdown break strategy Versus Stop loss: Complementary or substitutable
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Introduction
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Install a library on Jupyter Notebook
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Initialize the platform
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Get data from your broker
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Send orders on the market using Python and MetaTrader 5
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Get current positions
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Run structure positions
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Close all positions
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Live trading application: random signal
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Live trading application: SVR
