Forex strategies for algorithmic trading 2024

Course Curriculum

Chapter 1: Introduction

Lecture 1: Read me

Lecture 2: Install the environments

Lecture 3: FREE E-book!

Chapter 2: Python basics

Lecture 1: Introduction

Lecture 2: Type of Object: Number

Lecture 3: Type of Object: String

Lecture 4: Type of Object: Logical operations / Boolean

Lecture 5: Type of Object: Variable assignment

Lecture 6: Type of Object: Tuple and list

Lecture 7: Type of Object: Dictionary

Lecture 8: Type of Object: Set

Lecture 9: Python structures: If / Elif / Else

Lecture 10: Python structures: For

Lecture 11: Python structures: While

Lecture 12: Functions: Basics of function

Lecture 13: Functions: Local variable

Lecture 14: Functions: Global variable

Lecture 15: Functions: Lambda function

Chapter 3: Python for Data science

Lecture 1: Introduction

Lecture 2: Numpy: Array

Lecture 3: Numpy: Random

Lecture 4: Numpy: Indexing / Slicing / transformation

Lecture 5: Pandas: Serie and DataFrame

Lecture 6: Pandas: Cleaning and selection data

Lecture 7: Pandas: Conditional selection

Lecture 8: Matplotlib: Graph

Lecture 9: Matplotlib: Scatter

Lecture 10: Matplotlib: Tools

Chapter 4: Your first Forex algo trading strategy

Lecture 1: Introduction

Lecture 2: Manage the data

Lecture 3: Import data from your broker using MT5

Lecture 4: Intuition behind the strategy

Lecture 5: Bollinger bands creation

Lecture 6: Signals computation

Lecture 7: How to verify if we compute our signals correctly

Lecture 8: Compute the profits of the strategy

Lecture 9: Automate your strategy

Lecture 10: Compute profits on a train set

Lecture 11: Compute profits on a test set

Chapter 5: Vectorized Backtesting

Lecture 1: Introduction

Lecture 2: Sortino ratio computation

Lecture 3: Beta ratio computation (CAPM metric)

Lecture 4: Alpha ratio computation (CAPM metric)

Lecture 5: Drawdown: function creation

Lecture 6: Drawdown: application

Lecture 7: Backtesting Function (1)

Lecture 8: Backtesting Function (2)

Lecture 9: Backtest your Forex trading strategy

Chapter 6: Advanced Forex algo trading strategies

Lecture 1: Introduction

Lecture 2: Preparation

Lecture 3: Features engineering

Lecture 4: SVM template explanation (more details in chapter: Machine Learning reminder)

Lecture 5: Additional explanations about the strategy

Lecture 6: Compute the profits

Chapter 7: Portfolio / Risk management

Lecture 1: Introduction

Lecture 2: Portfolio optimization: Intuition

Lecture 3: Portfolio optimization: Practice

Lecture 4: Drawdown break strategy: intuition

Lecture 5: Drawdown break strategy: Apply to portolio

Lecture 6: Drawdown break strategy: Apply to portfolio + Individual asset

Lecture 7: Drawdown break strategy Versus Stop loss: Complementary or substitutable

Chapter 8: MetaTrader 5 Live Trading

Lecture 1: Introduction

Lecture 2: Install a library on Jupyter Notebook

Lecture 3: Initialize the platform

Lecture 4: Get data from your broker

Lecture 5: Send orders on the market using Python and MetaTrader 5

Lecture 6: Get current positions

Lecture 7: Run structure positions

Lecture 8: Close all positions

Lecture 9: Live trading application: random signal

Lecture 10: Live trading application: SVR

Chapter 9: Machine Learning remind

Lecture 1: Introduction

Lecture 2: SVR: Theory

Lecture 3: Features engineering: Create technical indicators

Lecture 4: Features engineering: Standardization

Lecture 5: Features engineering: Principal component analysis

Lecture 6: SVR: Practice

Lecture 7: Backtest the strategy

Lecture 8: Automatization