I’ve noticed a trend where a lot of power traders have backgrounds in engineering and statistics. I am a currently a finance undergrad, and I think I’m about to add on a statistics minor. What value does this necessarily provide on a commodities trading desk?
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finance majors using critical thinking challenge (impossible)
Yeah my bad bro
Finance undergrad may give you decent exposure to learning some of the products and a bit about markets, however it provides a pretty surface level overview and doesn’t really go under the hood at all (which requires more complex math that most business majors won’t take). Coming from an engineering/stats background, you may not know the specific product, but you have the math foundation to learn that product quickly and on a deeper level than most business majors. For example, while a physics major may not have learned about options, they have likely seen geometric brownian motion through heat or some particle PDE, which will give them a much easier transition to understanding options/stochastic calc than a business major that just learned the basic definitions. Also coding has become a big thing in trading, and most stem majors will know how to code
Thanks, this is really the answer I was looking for
You wanted confirmation bias?
Do you actually use Brownian motion in practice? Was told by some traders that knowledge of that stuff is a bit too theoretic, but I don't have any real finance experience. Follow-up, which firms/roles use that sort of advanced math/probability on the daily?
You wont need to be be writing out rigorous proofs (unless maybe ur in strategy writing the appendix to a note) but you need to known enough under the hood of what ever model ur using to price something. You do use Brownian motion in practice - ever head of Black-Scholes or Bachelier? The quant team usually has something built but ive seen some cracked analysts build their own pricing sheets thats faster but obv pulls from the same live curves. Generally, the further removed a product gets from the underlying, the more mathematically intensive the modeling/pricing becomes
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