Is stochastic math and Brownian motion still important to quantitative..

https://www.quora.com/Is-stochastic-math-and-Brownian-motion-still-important-to-quantitative-hedge-funds-Is-it-all-about-AI-and-machine-learning-now/answer/Aaron-Brown-165

Is stochastic math and Brownian motion still important to quantitative hedge funds? Is it all about AI and machine learning now?

A: Stochastic calculus, which includes the study of Brownian motion, was important for derivative pricing done by dealers more than quantitative investing done by hedge funds. It’s handy to know, and insight into any one branch of mathematics can lead to useful ideas anywhere, but it’s never been as important a field as probability, linear algebra, signal processing or other fields.
Most quantitative strategies are based on very simple mathematics. When more complicated tools are used they’re mainly for elegant exposition of the ideas rather than practical calculation of the decisions.
Machine learning is certainly hot, and has been useful for trading algorithms that decide how to execute orders determined by other algorithms, but has not had conspicuous success in quantitative investment strategy. I suspect it is the future, and people spend a lot of money on it and claim to use it in their marketing, but it has not yet arrived.
The success to date has not come from experts in theoretical machine learning, but from people with broad experience applying well-known ML algorithms to that solve actual—not textbook or contest—problems.

*파생 프라이싱에만 쓰이는 수학 종류들이 있다.
(퀀트도 따지고 보면 종류가 많다)파생 프라이싱 job 시장은 잘 알려져있다시피 금융위기 이후 많이 죽었다. 업계 자체가 성숙기를 지났다는 말도 많다. 그러다보니 퀀트 산업 전반은 꾸준히 확장되고 있음에도, 확률미분 같은 지식들을 배우는 리턴도 많이 줄어든 듯하다.