Algorithmic trading for beginners: from zero to hero

Technical indicators, risk management, Python programming, maths for trading, MetaTrader 5 live trading. Bots included

4.73 (132 reviews)
Udemy
platform
English
language
Investing & Trading
category
instructor
Algorithmic trading for beginners: from zero to hero
8,638
students
7 hours
content
Mar 2024
last update
$59.99
regular price

What you will learn

Create a trading strategy from scratch, backtest it and optimize it

Basics in Python and Maths for algorithmic trading

Advanced algo trading concepts like Hurst exponent and how to adapt your strategy to your data

Understand how to create and use technical indicators with Python

Backtest your strategy without error using vectorized backtesting

Learn many financial metrics: Sortino ratio, alpha, beta,...

Learn how to analyze your drawdown

Add a stop loss on your strategies

Combine different technical indicators to double your earnings

MetaTrader 5 live trading using Python

Why take this course?

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 technical analysis 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 and risk management techniques to reduce the drawdown and maximize your returns.


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

  • Modeling: Technical analysis (Moving average, RSI) and condition combination.

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

  • Risk management: Manage the drawdown(Stop loss), combine strategies properly (Strategies portoflio).


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.

Screenshots

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Reviews

Dominico
April 17, 2023
I was beginner before that. I know that I still have a lot to do, but I understand what I'm doing now, thanks!
Lakshman
January 11, 2023
without offending the instructor, the accent is hard to follow - the close caption also get it wrong..
Gleb
December 11, 2022
I think it's a very good introduction to algo trading. You get a good overview of what is involved. You can start applying the information immediately after each lecture to start building your own portfolio. The instructor sounds very knowledgeable and (I've not checked) seems to have some more advanced lectures that should enable one to optimize their trading.
Izaia
September 8, 2022
Thanks a lot for this course! You are not a native speaker but it is not a problem for the course! I have learned a lot, really!
Basilia
January 30, 2022
This course worth literally more than 20 times his price. It's just Gorgeous! I was a complete beginners in programming and algo trading and I think I know more now than watching 100hours of Youtube videos from people that doesn't understand what they do. The instructor is really clear and he know its suject for sure! I recommande.

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4497512
udemy ID
1/16/2022
course created date
1/30/2022
course indexed date
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course submited by