Young & Ambitious: Actuarial Science to Quant Finance, Fortune Khoza (Standard Bank)

Global Markets Graduate Fortune Khoza discusses his transition from Actuarial Science to Quantitative Finance, the challenge of calibrating a local volatility surface, and the necessity of blending academic models with real-world market data.

Welcome to the second episode of Young & Ambitious, where I dive into the inspiring journeys of young professionals making their mark in the world. Today, I am joined by Fortune Khoza, a Global Markets Graduate at Standard Bank and a Master of Financial Engineering graduate from UCT. With a background in Actuarial Science and Quantitative Finance, Fortune is passionate about the intersection of markets, models, and data. From top academic achievements to high-impact internships at Liberty, Old Mutual, and Camissa, Fortune has consistently sought out environments that challenge the way he thinks. Here is what he had to say:

What initially drew you to actuarial science and quantitative finance, and how did your perspective evolve as you progressed through university?

To be honest, when I was in Grade 12, I did not know what I wanted to study. I went on the internet and searched for the highest-paying jobs, and actuarial science was high on the list. I read about it and found out that it involves a lot of math. Since I was doing well in subjects like Mathematics, Physical Sciences, Economics, and Accounting, I thought to myself, I will study actuarial science at university. As I went through my studies at UCT, my understanding of the field deepened. Over time, I realised that quantitative finance had many applications beyond traditional actuarial work, especially in investment banking, trading, and derivatives pricing. My Master of Financial Engineering…

Your master's research involved calibrating a local volatility surface. What were some of the biggest challenges in this project, and what insights did you gain?

The project as a whole was quite challenging, but I was fortunate to have a supervisor whose guidance was extremely valuable. The Black-Scholes model assumes constant volatility, which is unrealistic in practice. My project gave me insight into how this flawed assumption is addressed through local volatility models, allowing for a more accurate representation of market dynamics.