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How to Build Quant Algorithmic Trading Model in Python
A step-by-step guide to perform Alpha Research in python
This post covers the basics of the alpha research process. ziplineand alphalens are used to manage the pipeline and measure the performance in a way to be explicit about the quantitative process. You can check zipline tutorial as well.
The focus of this post is on pure alpha research process and I will cover the backtesting (How to Perform Backtesting in Python — added on 14 Jan 2021) and utilisation of AI/machine learning in another post later (How to generate AI Alpha Factor in Python — added on 26 Dec 2020). Also, as a matter of course, the model described in this post is just a sample and should not be used in production.
1. Data Preparation
Ingesting Data
The first step is to get necessary data. zipline provides ingestion function to get data from their bundle or create a custom data bundle. Once zipline is installed, you can simply execute this to get a default data bundle sourced from Quandl and preprocessed by Quantopian.
