Forex strategies for algorithmic trading 2024

Forex strategies for algorithmic trading 2024, available at $64.99, has an average rating of 4.4, with 79 lectures, based on 50 reviews, and has 7463 subscribers.

You will learn about 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 This course is ideal for individuals who are Everyone It is particularly useful for Everyone.

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Summary

Title: Forex strategies for algorithmic trading 2024

Price: $64.99

Average Rating: 4.4

Number of Lectures: 79

Number of Published Lectures: 79

Number of Curriculum Items: 79

Number of Published Curriculum Objects: 79

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

Everyone

Target Audiences

Everyone

Do you want to create quantitativeFOREX strategies to earn up to60%/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.

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

Instructors

Lucas Inglese
Founder of Quantreo

Rating Distribution

1 stars: 1 votes

2 stars: 1 votes

3 stars: 2 votes

4 stars: 15 votes

5 stars: 31 votes

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