Quant Culture
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- Опубліковано 19 жов 2024
- How do you build a quant culture?
Quants have very different needs from business professionals (specifically finance professionals at a bank). Quants operate on a high level of science and art all at the same time. Access to high quality academic and professional resources are needed to build and validate models properly. Mentors (senior quants) are needed to teach junior quants technical skills, business information, and how to operate in the firm (managing corporate politics). Time needs to be flexible as there is a good portion of the job that requires creative thought to solve problems and review work. Having a flat structure that promotes communication across all levels is also important to develop an open team mentality.
There is no perfect quant culture however time should be spent by organizations to create a positive environment where their quants can learn and grow.
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Dimitri this is super useful, overall I think this is the same across most industries. As you said this come from a lack of understanding by senior management about what it is exactly that quants do. For some reason there is this misnomer that all quants just know numbers so they have nothing else to add besides crunching numbers and sending the results to supposedly the smart people who understand the business. In my estimation the more quants are involved in the business side of things the better the more appreciative management and other staff will be to quants.
Amazing video! It is hard to find a good mentor and even harder to be a good mentor. I think this problem is huge in tech field also.
What math skills do you need to know as a quant? And also what degrees are best to find a job?
To get started you need Calc 1, 2, and 3, ODE, PDE, real analysis, and probability theory. In a grad program to become a quant you should learn stochastic calculus and numerical methods applied to finance along with statistical and mathematical models.
The micromanagement is too real. At my current company we just have to log time spent on jira, but i quickly forget what a perk this is. Some managers/supervisors have no idea how to do their jobs.
Do you think the same principles could be applied in other industries? For example in tech or data science? Like I'm also interested in research, would that be tolerated in tech/data sc?
Video response here:
ua-cam.com/video/uwIzBB1Jf28/v-deo.html
Hey Dimitri! Currently, I'm a sophomore in college and have landed a quantitative developer internship at a fairly big company (40+ billion AUM) but I want to know how much time I should be allocating to this internship (how much is too little and how much is too much)? Any range on your expectations for an intern? Is going above and beyond in my internship and having mediocre grades (3.0-3.5) better than having good grades (3.5+) with a mediocre performance during my internship? Obviously, the goal is to get good grades and perform well in the internship but in the case that it doesn't pan out to be that way and I need to choose between one or the other - which is more important and how would this make my resume look when I apply for the next internship/job (also, if possible, please be blunt rather than beating around the bush)?
From a quant perspective I don't care much about the GPA. I want to see the skills you learned from school and internships on the resume and I really want to hear about them in the interview. Doing well in school is important however grades don't reflect true learning.
For Quant positions what is the preferable Master's degree, Economics or Data Science?
This is with a Honours Economics, minor Stats undergrad background
It depends on the courses in each program. How many stats, math, and CS classes are in each program? Some economics programs are rigorous and some are just random theory. Some data science programs are rigorous and some are just how to code models with no understanding of the models.
@@Jay-xb5du data science is not more quantitive in anyway. A statistics applied math or economics including econometrics classes are more than likely much more rigorous than data science. Data science is considered to train you to be mediocre at a lot of different topics. You won't learn advanced material in anything..
@@t_mini5371 ah thanks for that because I was considering doing a data science undergrad however, I’ll stick with math, stats and economics.
@@Jay-xb5du take a look at your schools course descriptions. Sometimes data science programs are good but many lack rigour. It is similar to with Dimitri says in a video where he compares business analytics to something a statistician would do. Data science students in most cases are not taking proof based math or stats classes and validating criteria for a model to be used. But don't take my word for gospel, all programs are created different.
Thanks for being a part of the community! I try and respond to everyone but luckily I have good subscribers like you who help as well.
Mr pouty on another tantrum