Vectorbt for beginners - Full Python Course

A full introduction to backtesting with VectorBt in python. VectorBt utilises common data science libraries like Pandas, Numpy, Plotly, etc. to give us blazing fast performance on thousands of simultaneous backtests. We can also define our own indicators and grid-optimize its parameters until we find the optimal values.

⭐ Code:
https://github.com/ChadThackray/vecto...

🧠 You will learn how to:
⌨️ Create your own custom indicators with the indicator factory
⌨️ Do hyper-parameter optimization and find the best parameters for your  strategy
⌨️ Optimize your backtests using talib + numpy
⌨️ Create dashboards to visualize the performance of your backtests
⌨️ Use different order types, stop-loss, take-profit, and shorting.
⌨️ Guard against over-fitting by running backtests over many time windows and comparing vs random trading.

⏱️ Timestamps:
(00:00:00) Course Introduction
(00:06:36) Quickstart
(00:32:51) Creating Custom Indicators
(01:14:47) Parameter Optimization
(01:45:52) Optimization Techniques
(02:14:59) Graphing / Dashboarding
(02:55:21) Order types, stop-loss, take-profit, shorting
(03:18:21) Avoiding Over-fitting

📋 Blog Posts (with code):

Creating custom indicators:
https://greyhoundanalytics.com/blog/c...

Using Multiple indicators:
https://greyhoundanalytics.com/blog/u...

Parameter Optimization:
https://greyhoundanalytics.com/blog/v...

Graphing in Vectorbt:
https://greyhoundanalytics.com/blog/p...