The purpose of this repository is to journal my own algorithmic trading journey and help fill some knowledge gaps for those starting their own journey as well.
Some may relate to the struggle of finding what seems to be a promising tutorial filled with script that cannot be executed and debugging is still a foreign concept. Or perhaps you are a saavy programmer already but developing an investing strategy is not yet your forte.
By no means am I an expert on either subject, having have found myself in both the situations described above sometime ago. Again my aim here is primarily to document my own algorithmic journey but perhaps someone else can benefit from my memoir surrounding the subject. Of course I welcome any feedback and questions.
By benefit I mean establish enough of a foundation both in the investing and programming sense to aid in the developement of ones own trading stratgies that will eventually be implemented with some confidence out in the real world.
So without further ado lets begin. The outline for this repo will be something like this:
- setting up your development environment (handled further down in this README)
- the Robinhood API and processing data
- building a portfolio via fundamental analysis
- Entry and Exit points via Technical Analysis
- Building a Trading Agent
- Backtesting
Supplemented with excerpts mostly from the Intelligent Investor, a book worth anyones time reading,, as well as other useful material from Investopeida, Medium, Youtube and other great sources that I will be sure to cite.
Alright I'll assume that if you're browsing Git then you are already familiar with either Ubuntu, WSL2, Docker or Anaconda. Here I used miniconda with python 3.9
So here are the steps.
- Download Miniconda
- Fork then clone this repository.