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.
Enroll now: Forex strategies for algorithmic trading 2024
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:
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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.
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
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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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