This is my a interactive recording of my quest to become a successful investor.
Contains various code snippets in python and ipython notebooks with useful code snippets to analyze a variety of stocks and stock related data.
My quest to gain an edge on stocks includes
- Scanning for news from yahoo
- Subscribing to ceo.ca to get news alerts
- Python scripts to visualize my yolo purchase decisions
- Sentiment Analysis on published documents and text
- Analyze the transcripts of youtube videos for nlp
- Algorithmic trading - just for back testing
- Price Prediction
- Risk Analyze - I honestly just held enough cash to deploy in any situation.
- Estimation of Returns
But to be perfectly honest, I have done fairly well buying canadian small cap companies that were interesting or undervalued in 2021, not 2022.
To build this project
jb build ibook/
To convert an ipynb book to a markdown file
jupytext CorrelationExamples.ipynb --to rmarkdown
Since this book contains useful contain, I will try to make money on ads, please click on them <3
To serve content directly you can use
python -m http.server 8080 --bind 127.0.0.1 --directory ibook/_buildThis repo is meant to contain some of my investing notes
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent