
Learn How to Use and Manipulate Open Source Code in Python so You can Fully Automate a Cryptocurrency Trading Strategy.
Algorithmic Trading: Backtest, Optimize & Automate in Python
InstructorMohsen Hassan
Learn How to Use and Manipulate Open Source Code in Python so You can Fully Automate a Cryptocurrency Trading Strategy.
InstructorMohsen HassanEditorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
This screenshot displays the Atom text editor interface with a Python script for configuring algorithmic trading parameters like ROI and stoploss within the Freqtrade framework.
The terminal output displays a comprehensive backtesting report, detailing performance metrics such as average profit percentage, total profit in BTC, and trade duration for various cryptocurrency pairs.
The curriculum provides detailed walkthroughs for developing, testing, and implementing trading strategies using real-life examples.
Instructional signals suggest the tutor explains the 'why' behind techniques, breaking complex topics into manageable units.
Changes in Freqtrade, Python, and Linux mean that many installation and configuration instructions no longer function as described.
Specific functions and features within the Freqtrade framework have been deprecated, requiring learners to consult current documentation.
The course is better suited for those with existing technical skills rather than absolute beginners due to the setup friction.