Data Scientist turning Quant (I)— Why I became an Algo Trader

Jonas Schröder
12 min readOct 23, 2022
Image by the author, source:

In short, 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. I am naive and assume that using the tools I use every day in my job could have prevented my returns to go down the gutter.

My quest is to learn from my mistakes and to investigate if I can predict the stock market by just using free data sources and opensource software on my MacBook Pro.

My goal is NOT to develop a fully automated high-frequency algo-trading machine that makes me rich while sleeping. My goal is to experiment and to learn, and I would like to take you, the reader, on a ride with me.

Since I am not trained in any investment strategy or have any strong believe in either the efficient market hypothesis nor technical analysis or any family of investment hypotheses, I thought about taking whatever theory is there and test it on actual data.

That was the plan, and of course it turned out to be more complex than I thought. This and further articles are meant to follow my approach as a non-financial data scientist to the challenge of predicting the stock market and automate investment decision making.

You are reading Part I, which about my personal background and motivation, as well as a simple data analysis of what went wrong with my former gut-feeling investment “strategy”. It is less technical than the other parts but I hope it’s still useful to follow along and to get started with your own market prediction journey.

I hope you have fun reading this series and learn something on the way, too. 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.

Why am I doing this?

Jonas Schröder

Writes about how #AI and #ML applications help in different fields like #Finance and #Marketing. Data Scientist at the worldwide #1 beauty company #beautytech

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