Algorithmic trading using Price action strategies

Algorithmic trading using Price action strategies

Algorithmic trading using Price action strategies

Figures detection, Patterns detection, Backtest, using MetaTrader 5 and Python. Bots included

Language: english

Note: 4.5/5 (11 notes) 3,151 students

Instructor(s): Lucas Inglese

Last update: 2022-04-25

What you’ll learn

  • Create an algorithmic trading strategy using patterns detection or figures detection from scratch
  • Put any algorithm in live trading using MetaTrader 5 and Python
  • Data Cleaning using Pandas
  • Manage financial data using Numpy, Pandas and Matplotlib
  • Python programming for algorithmic trading
  • Combine price action and technical analysis to optimize your performance
  • Detect trading figures through the candlestick

 

Requirements

  • Nothing

 

Description

Do you want to create algorithmic trading strategies?

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 price action to create robust 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 techniques to reduce the drawdown and maximize your returns.


You will learn and understand  quantitative analysis used by portfolio managers and professional traders:

  • Modeling: price action (Support, resistance) patterns detection (trading figures detection)

  • Backtesting: Make a backtest properly without error and minimize the computation time (Vectorized Backtesting).

  • Portfolio management: Combine strategies properly (Strategies portfolio).


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, programming and financial theory 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

  • Everyone who wants to learn algorithmic trading

 

Course content

  • Introduction
    • READ ME
    • Install the environments
  • Basis of the programming language Python
    • Introduction
    • Type of object: Number
    • Type of object: String
    • Type of object: Logical operation / Boolean
    • Type of object: Variable assignment
    • Type of object: Tuple and list
    • Type of object: Dictionary
    • Type of object: Set
    • Python structures: IF / ELIF/ ELSE
    • Python structures: FOR
    • Python structures: WHILE
    • Functions: Basics of function
    • Functions: Local variable
    • Functions: Global variable
    • Functions: Lambda function
  • Python for data science
    • Introduction
    • Numpy: Array
    • Numpy: Random
    • Numpy: Indexing / Slicing / Transformation
    • Pandas: Serie and DataFrame
    • Pandas: Cleaning and transformation
    • Pandas: Conditional selection
    • Matplotlib: Graph
    • Matplotlib: Scatter
    • Matplotlib: Tools
  • Import and manage the financial data
    • Introduction
    • Import & manage data from Metatrader 5
    • Import & manage data from Yahoo Finance
  • Figures detection: Trading strategy using the Engulfing figure
    • Introduction
    • Import / Transform data
    • Bullish Engulfing figure
    • Verification signal creation
    • Bearish Engulfing figure
    • Compute the profit
    • Automate the process
  • Vectorized Backtesting
    • Introduction
    • Sortino ratio computation
    • Beta ratio computation (CAPM metric)
    • Alpha ratio computation (CAPM metric)
    • Drawdown function: creation
    • Drawdown function: application
    • Backtesting function (1)
    • Backtesting function (2)
    • Backtest your strategy
  • Combine price action with technical analysis to optimize your profits
    • Introduction
    • Import the data
    • Support & resistance
    • Support & resistance trading strategy
    • Support & resistance + SMA trading strategy
    • Support & resistance + SMA + RSI trading strategy
    • Automate the process
    • Scalping trading strategy + Portfolio management
  • MetaTrader 5 Live trading
    • Introduction
    • Install a library on Jupyter Notebook
    • Initialize the platform
    • Get data broker
    • Send orders on the market using Python
    • Get current positions
    • Run structure positions
    • Close all positions
    • Live trading application: random signal
    • Live trading application: Engulfing figure strategy
    • Live trading application: Support & resistance + SMA + RSI strategy

 

Algorithmic trading using Price action strategiesAlgorithmic trading using Price action strategies

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