Data Scientist turning Quant (II) — Let’s Predict Stock Move Directions
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Short background about me. I am a data scientist by trade and my investment portfolio turned from great (thanks to the 10-year bull market rally) to not-so-great. For the purpose of this blog series, I am naive and assume that using the tools I use every day in my job could help me to be a better investor in the future.
My goal is to experiment and to learn, and I would like to take you, the reader, on a ride with me in this exploratory multi-part series on predicting the stock market. You can find out more about my motivation and approach in Part I of this series.
This is Part II, and its about my experiments with predicting directional stock moves for almost all of the S&P 500 companies from 2014 to today (fall 2022). Thus, it’s going to be a bit more technical than Part I but certainly no research paper level. It should be easy to follow along even with limited Machine Learning knowledge.
I hope you have fun reading this series and learn something on the way, too. I surely learned a lot.
If you have anything to add to my journey, feel free to write it in the comments or to contact me here/on LinkedIn.
Disclaimer: To avoid any legal liabilities: nothing here is investment advice nor am I qualified to give such advice. When you crunch data, the fact that there’s always an outcome is not proof that this is what’s actually happening to create this outcome. Take anything you read with a cup of salt. But still — have fun and experiment.
Predicting the direction of the market/stocks
What goes through your head before buying a stock? Many things, I guess, but in the end it all comes down to whether you think that stock will be worth more in the future or not.
