I first met Silvano in an exam room. The teacher handed out a paper with five straightforward math problems and another A4 sheet with an essay assignment in German, naturally. The German essay didn’t seem too challenging for me, but as I glanced through the math questions, my hope of getting into the Zurich University of Applied Sciences started slipping away with each passing second.

Meanwhile, the guy next to me seemed to be experiencing the opposite. He shot me a quick, secretive look and, upon noticing my blank expression, swapped my math sheet with his German one. Now all I had to do was write two German essays, and in return, he’d give me back my completed math answers. As I recall, Silvano managed to finish my math problems in under 20 minutes.

Silvano Gatto—or just “Gatto,” as we’d call him throughout our studies—solved three out of the five math problems, one of which involved the heat transmission equation. We’d been using that formula for over a year to calculate the thickness of different wall layers and to determine the amount of insulation required to separate indoor and outdoor spaces in buildings.

In 1993, Black and Scholes, alongside Merton H. Miller, would use an extended version of this same Heat Diffusion Equation to create the Black-Scholes-Merton model (and get the Nobel Memorial Prize in Economic Sciences in 1997). This model, now widely used, calculates the fair prices of stock options based on six variables: volatility, option type, underlying stock price, strike price, time, and risk-free rate.

Naturally, Gatto and I became friends—though that bond was put to the test the day Juventus lost to Real Madrid or Barcelona, I can’t recall which. And since neither of us were particularly thrilled with the Heat Diffusion Equation to calculate insulation thickness, we pooled our salaries and invested in our first hedge fund: unregulated, tax-free, high-risk, and managed by a friend who had recently started as an apprentice at UBS.

As our exams approached, the 600 Swiss Francs we’d each invested slipped our minds. Then, one Thursday, Gatto came into class with a grin: the investment committee (Gatto and our derivatives specialist) had decided to close out the fund and distribute dividends. Each “unqualified investor” walked away with 2,300 Swiss Francs—a result that none of us, including our friend at UBS, could have predicted.

Ten years later, I would start my training at UBS in Winterthur and soon after, be transferred to the headquarters—three years after two of our Nobel Prize-winning mentors and a group of ambitious traders had burned nearly $5 billion in the notorious LTCM fund, a regulated, high-risk hedge fund managed by UBS but with a much more “sophisticated” investment committee.

The rest of my training at UBS took place mostly in centralized investment management, and later in wealth management, where we spent much of our time monitoring stock markets and placing buy-and-sell orders on our own accounts. We didn’t make fortunes, but sometimes we’d make just enough to buy a second-hand sports car on a whim. In hindsight, none of this really qualified as “economic intelligence.” And after the dot-com bubble burst, it became clear that we weren’t the only fools out there.

In the end, Gatto’s approach to risk-taking—whether in the classroom or in the markets—left a lasting impression on me. It wasn’t about being right all the time; it was about taking chances, learning from mistakes, and always moving forward. Those early days, filled with improbable investments and unlikely outcomes, became the foundation of my financial career, and for that, I’ll always be grateful.