Download Udemy – Algorithmic trading using Price action strategies 2022-3

Algorithmic trading using Price action strategies


Algorithmic trading using Price action strategies, the Algorithmic trading using Price action strategies course has been published by Yudmi Academy. All course programs will be done using Python. However, for Python beginners there is a free intensive Python course to master Python. In this course you will learn how to use price action to create powerful strategies. You will perform quantitative analysis to find patterns in the data. We will learn how to perform vector backtesting when you have many profitable strategies. You will then use portfolio techniques to minimize your losses and maximize your returns. This is not a programming course nor a business course or a machine learning course. This is a course that applies statistics, programming and financial theory to business. This course was not created by a data scientist, but by someone with a degree in mathematics and economics specializing in applied mathematics in finance.

What you will learn

  • Create an algorithmic trading strategy from scratch using pattern recognition or figure recognition
  • Place any algorithm in live trades 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
  • Recognize trading figures through candlesticks

Who is this course suitable for?

  • Everyone who wants to learn algorithmic trading

Algorithmic trading using price action strategies course specifications

  • Publisher: Udemy
  • teacher : Lucas Inglese
  • English language
  • Education level: all levels
  • Number of courses: 63
  • Training duration: 5 hours and 21 minutes

Head of the course seasons on 2024-3

Course prerequisites


Algorithmic trading using price action strategies

Sample video

Installation guide

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English subtitle

Quality: 720p

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Download part 1 – 1 GB

Download part 2 – 1 GB

Download part 3 – 4 MB

File(s) password:


2 GB

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