Career: Have you ever seen a quantitative team get wiped out?
A practical guide to building a career in finance and fund management
Table of contents:
Introduction.
Learning, failing, and evolving.
The birth of a pod shop.
Crafting the blueprint.
The dream team.
Legal, compliance, and regulatory maze.
Lessons learned and what I’d do differently today.
Introduction
I have always believed that success in quantitative trading is not about looking at charts, but rather about combining rigorous mathematical modeling with the innate passion of human creativity. Now, at 38 years old, I reflect on a journey that began with an insatiable curiosity and has become the meal I put on the table every day.
I'm sure if you're reading this, you've fantasized about starting your own fund at some point. Is it worth it? What does it entail? I'm sure more than one of you imagines it as a sort of Wolf of Wall Street, with money, cocaine, and whores. But you should rather imagine it as:
Sleepless nights spent coding and iterating algorithms.
Anxiety, fear, and shame followed by moments when every sacrifice is worth it.
Missteps that taught invaluable lessons—including layoffs.
A transformation from a hopeful young trader to a seasoned entrepreneur.
I invite you to join me today as I share my personal story. Whether you’re an aspiring trader, a tech enthusiast, or simply curious about the world of quant trading, I hope you find this account both informative and inspiring.
Learning, failing, and evolving
My journey began in the summer of 2011. The world was on the brink of significant financial and technological transformations, and I was a bright-eyed 23-year-old, freshly stepping into the quant trading arena. The technology landscape was rapidly evolving:
Dial-up was swiftly giving way to faster, more efficient internet connections.
Early smartphones hinted at the mobile revolution that would soon reshape communication.
I attended a seminar on quantitative finance where a speaker described multi-strategy funds and pod shops as living, breathing cells in a trading organism. I jotted down every idea with fervor, thinking:
“What if every trader could operate like an independent cell—free to innovate yet working together to drive overall success?”
That single idea ignited an obsession. I spent countless nights in front of my setup, sketching models on napkins and dreaming of a firm where brilliant minds could thrive within a supportive yet fiercely competitive ecosystem.
Between 2011 and 2015, my career unfolded, and I embarked on a path to merging trading, technology, and data. I joined a trading firm that specialized in american stocks—a realm where every trade carried its own lesson and every day presented a new challenge.
During these formative years, I immersed myself in the core principles of quant trading:
Data: The raw material powering every buy or sell decision.
Algorithms: The engines transforming data into actionable insights.
Risk Management: The safety net ensuring we could weather market volatility.
I vividly recall the surge of adrenaline when a model executed a flawless trade—only to be jolted by a sudden market twist that nullified what looked like a sure win.
The early days were riddled with setbacks. I learned quickly that:
Every mistake is an expensive learning opportunity.
Backtested models guarantee nothing and often struggled in live markets.
One particularly volatile day, our models—performing well in controlled environments—began to falter. Instead of succumbing to panic, our team gathered, analyzed the situation, and managed to close the day with a positive balance—were we lucky? For sure, I won’t deny it. This experience underscored an invaluable lesson: The devil is in the details, and a trading system has details that even its own developer doesn't know.
