Algorithmic Trading: Backtest, Optimize & Automate in Python
4.5 (815 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
5,202 students enrolled

Algorithmic Trading: Backtest, Optimize & Automate in Python

Learn How to Use and Manipulate Open Source Code in Python so You can Fully Automate a Cryptocurrency Trading Strategy.
4.5 (815 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
5,198 students enrolled
Last updated 5/2020
English
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Current price: $129.99 Original price: $199.99 Discount: 35% off
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This course includes
  • 10 hours on-demand video
  • 1 article
  • 4 downloadable resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Use Python to Automate your Cryptocurrency Trading
  • Load Historical Data and Backtest your Strategy
  • Optimize your Strategy to Find the Best Parameters to Use
  • Run the Strategy in Simulation or Live
  • Connect to Multiple Cryptocurrency Exchanges
  • Be able to work on a Virtual Environment
  • Use Open Source Code Freqtrade
  • Communicate with the Strategy through your Phone
Requirements
  • Some Basic Programming knowledge (Any language)
  • Basic Cryptocurrency Trading Knowledge
Description

Learn to fully automate your cryptocurrency trading with this course!


This course is taught by a Quant (and the CEO of a Proprietary Trading Firm) as well as a Python/Cryptocurrency Instructor.


You will learn:

1) How to use freqtrade (open source code)

2) Use a Virtual Machine (we provide you one with all the code on it)

3) Learn How to code any strategy in freqtrade

4) Backtest a strategy so you can see how it would have performed in the past

5) Optimize a strategy to find the best parameters to get the best reward/risk ratio

6) Do a walk forward analysis to see how a strategy would perform with out of sample data (to minimize overfitting)

7) Run the strategy with paper money

8) Run the strategy with real money

9) Connect the code to Telegram so you can communicate with it with your phone.


No python knowledge?

No worries there is a Python primer in the course to get you up to speed on the language :)


See you in the course!

Who this course is for:
  • Traders who would like to Automate their Cryptocurrency Trading
Course content
Expand all 53 lectures 09:51:24
+ About Algorithmic Trading
4 lectures 16:45
The Benefits Of Automated Trading
05:36
The Pits And Downfalls of Automated Trading
03:25
Prevalence of Automated Trading
03:49
Why Use Open Source?
03:55
+ Installations
5 lectures 50:40
Setting Up Your Environment: Options
02:12
Virtual Machine: Installing Virtual Box
04:35
Virtual Machine: Installing Ubuntu
24:02
Python Packages and Virtual Environment
15:45
Deploy Our Virtual Machine
04:06
+ Virtual Machine: Linux Environment
3 lectures 17:33
Ubuntu
04:11
The Terminal
05:30
Installing Apps and Editing Text
07:52
+ Python Primer
9 lectures 01:49:01
What this primer is for
01:00
Installing Python
05:10
Using Python As A Calculator (Operators)
05:59
Strings and Integers
07:47
Lists and Dictionaries
21:22
If Else For Statements
23:35
Imports
08:08
Functions
17:26
Classes
18:34
+ Installing Freqtrade
2 lectures 26:58
Quick Intro To Git
11:25

If you get the following error:
`ERROR: Double requirement given: python-rapidjson==0.6.3 (from -r requirements.txt (line 27)) (already in python-rapidjson (from -r requirements.txt (line 18)), name='python-rapidjson')`
Please open the `requirements.txt` file and delete line 27.

Installing Freqtrade
15:33
+ Configure And Run
4 lectures 42:06
Configure Telegram
06:31
Configure Binance
04:25
Configure Bot
16:30
Run Strategy in Sandbox
14:40
+ Strategy Implementation
12 lectures 03:25:04
Strategy Explanation
18:36
Automated Strategies: Discussion
03:40
Coding The Strategy
22:17
Backtesting Strategy & Plotting Results
18:26
Parameter to Optimize
28:26
Doing the Optimization (part 1)
32:54
Doing the Optimization (part 2)
12:45
Optimizing With Larger Iteration
09:59
Testing / Backtesting Optimized Strategy
05:36
Running The Strategy Live
23:42
Trading Results
10:10
+ In Sample And Out Of Sample Testing
2 lectures 21:20
Walkforward Analysis
06:51
Performing a Walkforward Analysis
14:29
+ Assignment
3 lectures 13:00
freqtrade/strategies repo
08:24
Assignment
02:52
Connect
01:44