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Quantitative Finance/Hedge Fund Questions

Hello,


I wanted to ask about the requirements for Quantitative Finance. I always hear that mathematical ability is all that is required to land and excel at quantitative roles but after talking to some people, they say it is all about coding now. I thought quantitative research roles would still be math-oriented.

I would also like to ask for some recommendations on what should I do as I really feel hopeless right now.

I'm someone who is interested in mathematics and not as much in CS. I'm currently a second-year student doing a five-year dual degree in business and mathematics in Canada (My school is really not that great for mathematics but is the best for business in my country. Yes, I know a business undergrad isn't the place for quant finance but I am stuck here). Now, I love mathematics and I have been self-studying it since last year and most of the topics I know are 1) Topology, 2) Elementary Algebraic Geometry 3) Advanced Linear Algebra, 4) Real Analysis & Measure Theory, 5) Functional Analysis, 6) Some Harmonic Analysis, 7) PDEs and 8) Measure-Theoretic Probability.

Now, I am in a bit of a pickle as to what I should focus my time on. What I had previously planned was to spend my next nine months reading up completely on stochastics and then some numerical analysis. And in my third year, I planned on focusing my time on Statistics and Optimization and getting a feel for ML and even picking up some coding stuff.

1) Is this right? What do you think I should focus more on?

2) Do you think I should even bother with stochastic or should I go all-in on statistics/ML? CS is definitely not my strong suit and I am not that interested in it. I love mathematics and I love finance so I want to do quantitative research.

3) What other careers should I be looking at?

4) Lastly, what are your opinions on not going to grad school? I wouldn't mind going if it is absolutely needed, but I feel like I would be happier skipping grad school.



I would be really grateful if you could help me out.
 
uhhhh...CS is like half of it, nowadays even researcher roles are super coding heavy

saying this as someone who graduated majoring in math and had the same mindset a while ago
Hey, sorry for the late reply. How good would I have to be at CS? I have never really studied anything in CS other than the absolute basics. To what depth would I require it? I wouldn't mind devoting a lot of time into it if it is essential. If you could list the general breadth of topics I would need that would be helpful.
 
Hey, sorry for the late reply. How good would I have to be at CS? I have never really studied anything in CS other than the absolute basics. To what depth would I require it? I wouldn't mind devoting a lot of time into it if it is essential. If you could list the general breadth of topics I would need that would be helpful.
basic CS is enough. Just leetcode your way out. Learn some design patterns in the meanwhile.

But you would probably reconsider choosing this proffession if coding is not something you like. because coding would be 99% of what you do on the job. you don't want to be miserable on the job right =)?
 
basic CS is enough. Just leetcode your way out. Learn some design patterns in the meanwhile.

But you would probably reconsider choosing this proffession if coding is not something you like. because coding would be 99% of what you do on the job. you don't want to be miserable on the job right =)?
Well I wouldn’t agree with the 99%. I had a quant research role in an asset management firm and my job has a lot of components. Reading research papers, meetings, implementing code, back testing, alpha testing, etc. So a lot of planning and research goes into the code your writing so not necessarily just coding all day as in a swe role
 
Basic programming (OOP, data structures, algorithms, recursions, dynamic programming) is required for pretty much every single quant research role I've applied to. Some even required ML. I'd recommend learning the topics I mentioned above in Python, it should get you through most of the coding tests the funds/banks throw at you.

Unless you're aiming for certain firms which use a specific language (C++, Java, Matlab, R, etc.), just work with Python and get decently good at it. I haven't had a single coding test (from banks/hedge funds, can't say anything about prop trading) that doesn't allow Python so far, but I've had a couple which only allowed Python. Of course if you already know your target firm, do some research and learn their preferred language - don't apply to a HFT firm exclusively using C++ if you only know how to code in Python.
 
basic CS is enough. Just leetcode your way out. Learn some design patterns in the meanwhile.

But you would probably reconsider choosing this proffession if coding is not something you like. because coding would be 99% of what you do on the job. you don't want to be miserable on the job right =)?
Hey, what careers are there for a guy like me? I know sales & trading or Investment banking is possible but isn't that basically selling my soul? Also, I don't really seem to like academia because I don't think I'd be good compared to some people. I really want to pursue something that I can do on my own and grind my way into the big leagues, which is my current plan (getting some quant exposure then running my own hedge fund?). If you were somewhat in my shoes and you don't mind putting in a lot of hours (basically I have nothing else in my life) then what would you pursue/do?
 
Well I wouldn’t agree with the 99%. I had a quant research role in an asset management firm and my job has a lot of components. Reading research papers, meetings, implementing code, back testing, alpha testing, etc. So a lot of planning and research goes into the code your writing so not necessarily just coding all day as in a swe role
Are these type of roles quite common in the industry? Which firms do this type of thing?
 
Hey, what careers are there for a guy like me? I know sales & trading or Investment banking is possible but isn't that basically selling my soul? Also, I don't really seem to like academia because I don't think I'd be good compared to some people. I really want to pursue something that I can do on my own and grind my way into the big leagues, which is my current plan (getting some quant exposure then running my own hedge fund?). If you were somewhat in my shoes and you don't mind putting in a lot of hours (basically I have nothing else in my life) then what would you pursue/do?
Even the coding it’s not all just “coding”. A lot of it is using python/matlab to do data analysis and cleaning data. Cleaning data is a large part of the job that not everyone talks about. Then once you finally get a clean data set you then implement whatever ideas you have. During my internship most of the job other then reading papers on esg data was getting the data set ready to do analysis on it. So coding doesn’t necessarily mean swe style stuff. Also you attend meetings and get prospective from other groups and learn about fundamental analysis and what not.
 
Basic programming (OOP, data structures, algorithms, recursions, dynamic programming) is required for pretty much every single quant research role I've applied to. Some even required ML. I'd recommend learning the topics I mentioned above in Python, it should get you through most of the coding tests the funds/banks throw at you.

Unless you're aiming for certain firms which use a specific language (C++, Java, Matlab, R, etc.), just work with Python and get decently good at it. I haven't had a single coding test (from banks/hedge funds, can't say anything about prop trading) that doesn't allow Python so far, but I've had a couple which only allowed Python. Of course if you already know your target firm, do some research and learn their preferred language - don't apply to a HFT firm exclusively using C++ if you only know how to code in Python.
Ok, I seem to understand what your mentioning. It is essential for me to learn coding and I think I'll give it a good shot. But there is one thing I can't really comprehend. The prerequisites to quant finance seem so basic. Like what people mention as the requirements are simply basic CS which you can get at any undergrad CS/SE program and some elementary mathematics. So why is that quant firms pay so much and are so selective if the barrier to entry is so low? Is there another career out there for someone focusing on higher level maths mixed with some CS and finance?
 
Even the coding it’s not all just “coding”. A lot of it is using python/matlab to do data analysis and cleaning data. Cleaning data is a large part of the job that not everyone talks about. Then once you finally get a clean data set you then implement whatever ideas you have. During my internship most of the job other then reading papers on esg data was getting the data set ready to do analysis on it. So coding doesn’t necessarily mean swe style stuff. Also you attend meetings and get prospective from other groups and learn about fundamental analysis and what not.
So it seems to my novice eye that a lot of the firms are really inefficient. Isn't there a way that the quant heavy guys that get paid 300k+ be restricted only to actual idea implementation and maybe hire a cheap data guy for <100k to just grind out cleaning data and then make a concise report on it for the quant guy? Why is it like that?
 
So it seems to my novice eye that a lot of the firms are really inefficient. Isn't there a way that the quant heavy guys that get paid 300k+ be restricted only to actual idea implementation and maybe hire a cheap data guy for <100k to just grind out cleaning data and then make a concise report on it for the quant guy? Why is it like that?
If you have are new to the job, you're probably going to be that "cheap data guy" grinding out stuffs like data cleaning and making report to the senior quants.

Put it this way: If you have no experience, no actual track record, and can't do data cleaning to even backtest your own idea, how would you convince any company to pay another $100k guy to do the hassle of testing your idea which may or may not generate any value for the firm? That's like an IB summer analyst asking the bank to hire a cheaper guy to do his ppt slides and type his reports.
 
Well for me basically I was mapping out something new and they needed someone to start setting up the data set. There's some challenges involved, but yeah the manager isn't going to be doing data wrangling.
 
@noether-skolem @Michsund
Thank you guys a lot for the information, I think I understand why it happens now.

Edit: If I may ask, what do you guys think of learning numerical analysis and a lot of advanced stochastics. Would that be a waste of time? I think I can get the math aspect (adv. stochastics etc.) while also getting done with some adv. stats + basic CS before I start my applications. Do you think I would be better off spending all my time on learning more than the 'basics' in CS, or could I benefit with adv. stochastic knowledge and some other stuff like reading up more on PDEs and even some Numerical Analysis what Daniel Duffy seems to like a lot?
 
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@noether-skolem @Michsund
Thank you guys a lot for the information, I think I understand why it happens now.

Edit: If I may ask, what do you guys think of learning numerical analysis and a lot of advanced stochastics. Would that be a waste of time? I think I can get the math aspect (adv. stochastics etc.) while also getting done with some adv. stats + basic CS before I start my applications. Do you think I would be better off spending all my time on learning more than the 'basics' in CS, or could I benefit with adv. stochastic knowledge and some other stuff like reading up more on PDEs and even some Numerical Analysis what Daniel Duffy seems to like a lot?
I would say at the undergraduate level take more prob/stats and cs. Most firms will be focusing on those two things while interviewing. If you can I would taken more ML classes just so your more competitive for many jobs in the field.
 
@noether-skolem @Michsund
Thank you guys a lot for the information, I think I understand why it happens now.

Edit: If I may ask, what do you guys think of learning numerical analysis and a lot of advanced stochastics. Would that be a waste of time? I think I can get the math aspect (adv. stochastics etc.) while also getting done with some adv. stats + basic CS before I start my applications. Do you think I would be better off spending all my time on learning more than the 'basics' in CS, or could I benefit with adv. stochastic knowledge and some other stuff like reading up more on PDEs and even some Numerical Analysis what Daniel Duffy seems to like a lot?
I don't think I'm qualified to answer that (yet) as I'm just a new MFE student who hasn't even gone through an internship. I'd let someone with more experience answer that for you. (Seems like Michsund just did)

Keep in mind everything I said above regarding basic CS is just the absolute bare minimum to even be considered for a quant research interview - any less than that and you probably won't even get past the resume screening stage, but just having those may not be enough to be successful in the coding tests or technical interviews.

If you do get interested enough to further pursue CS there is another role which you may want to consider: quant developer. From what I've seen those roles are often filled by people who are otherwise qualified for software engineering roles (e.g. ex-FAANG or tech startup developers).
 
Hey, what careers are there for a guy like me? I know sales & trading or Investment banking is possible but isn't that basically selling my soul? Also, I don't really seem to like academia because I don't think I'd be good compared to some people. I really want to pursue something that I can do on my own and grind my way into the big leagues, which is my current plan (getting some quant exposure then running my own hedge fund?). If you were somewhat in my shoes and you don't mind putting in a lot of hours (basically I have nothing else in my life) then what would you pursue/do?
I can't give you advice on what you want to do. You must figure it out yourself. It is not my interest and neither I am in such position to give you this type of advice. You know the best for yourself.

Even the coding it’s not all just “coding”. A lot of it is using python/matlab to do data analysis and cleaning data. Cleaning data is a large part of the job that not everyone talks about. Then once you finally get a clean data set you then implement whatever ideas you have. During my internship most of the job other then reading papers on esg data was getting the data set ready to do analysis on it. So coding doesn’t necessarily mean swe style stuff. Also you attend meetings and get prospective from other groups and learn about fundamental analysis and what not.
Depends on the asset classes. I was doing your type of work when I was more on the e-trading side. It is not much fun tbh. I rather do more C++ model development. Also it is highly replaicable role. But i guess this is a matter of taste.

Ok, I seem to understand what your mentioning. It is essential for me to learn coding and I think I'll give it a good shot. But there is one thing I can't really comprehend. The prerequisites to quant finance seem so basic. Like what people mention as the requirements are simply basic CS which you can get at any undergrad CS/SE program and some elementary mathematics. So why is that quant firms pay so much and are so selective if the barrier to entry is so low? Is there another career out there for someone focusing on higher level maths mixed with some CS and finance?
I don't know why you have such impression. You don't even need a CS degree to get into Google neither. (But do you say Google's bar is low as well?) Just leetcode your way out. But for quant roles they only (unless you are some sort of ranked in math olympic) hire MFE/PhD. Not that a master degree can teach you how to be a successful quant but it is just a benchmark so they pre-filter out large pool of candidates and reduce the variance of the sample size.

Can you be a successful quant without a MFE/PhD? Definite can. Can you be a successful quant without even a colledge degree? Possible. But why would they bother? The cost of finding such candidate is much higher with much bigger sample pool.

In general, they just need someone who is smart and able to think from their feet. You can break the norm if you want. But how much effort is going to be? You would need to go into every employer and convince them that they are idiots and most likely start with an analyst posiiton. On the contrary it will cost u 1 year ish to follow the norm and get a master degree.
 
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