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/_build

This repo is meant to contain some of my investing notes