From Wall Street Dreams to Python Code: My Journey into AI and Programming

This is the story of how I tried predicting the stock market using Al. However, I ended up “just” learning Python instead.

If you’ve known me for a while, you’d be aware of my longstanding fascination with money. As a youngster, I delved into YouTube videos showcasing “infinite money glitches” and absorbed hacker stories about breaking into casinos. Not to mention, the Ocean’s Eleven series has a special place in my heart, adding a touch of glamour to the allure of making millions. My financial intrigue was born.

Yet, even before my money-minded exploits, I was captivated by the world of mathematics. Whether exploring theoretical and abstract concepts or dabbling in statistics to uncover arbitrage betting opportunities (of which I have another blog post in the pipeline), my journey through numbers has been a defining part of my narrative.

While many might link mathematical prowess with concentrated, long-term investing, the reality is that basic percentage calculations often suffice. Despite the fact that quantitative, algorithmic trading is often popularized in movies, respected investors like Warren Buffett rely more on judgment than intricate calculations—after all, calculations can be automated, right? As the renowned economist John Maynard Keynes wisely put it, “It is better to be roughly right than precisely wrong,” a sentiment that resonates in the world of investing.

Being well-aware that quantitative trading is less successful in practice due to commissions, capital constraints, and theories such as the Efficient Market Hypothesis being against me, I still found myself drawn to the challenge of building a neural network to predict the stock market. A daunting task with slim chances of success, but I was undeterred. But here’s the twist that occurred because I didn’t give up. Instead, my pursuit of predicting the stock market led me down an unexpected path…

Enter Python, the programming language that emerged as the key to unlocking this ambitious endeavor. With its reputation for being user-friendly yet powerful, and an extensive online ecosystem, Python quickly became my go-to choice, despite never really having programmed before. Weeks were dedicated to absorbing the wisdom from Harrison Kinsley and Daniel Kukieła’s excellent book Neural Networks From Scratch in Python. While it would have been easier to leverage existing packages such as TensorFlow, I opted to craft my own neural network from scratch as the book title also suggests. Why? Because the beauty of the underlying mathematics—encompassing linear algebra and calculus—beckoned me to understand it at a deeper level.

So, I immersed myself in Python, unraveling its intricacies and nuances. I learned about object-oriented programming and more, and delved into the very essence of coding.

Fast forward less than a year, and here I am—an 18-year-old (if that detail adds a dash of surprise) securing my first job as a data analyst and software developer. Python is now my daily companion, shaping my professional journey in unforeseen ways.

Reflecting on this journey, I want to leave you with a piece of advice: Don’t shy away from aiming high. As someone wise once said, “Shoot for the moon. Even if you miss, you’ll land among the stars.” It’s okay if your initial goal of creating a trading bot seems elusive right now. The pursuit itself will force you to evolve, learn, and ultimately achieve new heights. Who knows? I might circle back to the world of trading bots one day. Until then, keep reaching for the stars.

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