r/quantfinance

Hi, I'm an incoming college freshman. I have been admitted to UC Berkeley, for the data science major. I kinda wanted to get in for Computer Science, but the data science major was my alternate. Unfortunately, although UC Berkeley is a great school, I'm not sure if the Data Science major is seen as "rigorous" enough for this industry as well as in tech. Obviously it depends on myself though, but you get the idea. I've also heard that the UC Berkeley culture is super competitive and cutthroat, which doesn't seem very appealing to me.

I am from the bay area though, so UC Berkeley's in-state tuition is quite a blessing to me.

However, I've also been waitlisted (and hopefully will be admitted off the waitlist) at UChicago for the Computational and Applied Mathematics major. I am very excited to try and go here, as I think it really fits my interests, and the the math is very rigorous. But the cost of attendance will likely be very high, probably full-pay or very close to it. I know I'm not even admitted yet, but in the case I get off the waitlist, I must prepare for a phone call from the University saying "Will you 100% enroll?"

So my question to you is, as someone who is trying to break into the industry, which should I pick? I was planning on UC Berkeley, which is an amazing school already, but I've kind of idolized UChicago for quite a while now.

Is going to UChicago for being more of a "target" worthwhile to pay that much more for probably a similar education and perception to recruiters? Also, would going to UC Berkeley be more worthwhile, since this industry is so incredibly difficult to break into, that tech is a better fallback?

I understand that it is up to myself to decide on this decision, and not to fully base my opinion off strangers on the internet, but I'd like to hear a few other opinions other than from my family.

Thank you in advance!

i’m trying to understand how competitive model validation, market risk, and risk quant roles actually are right now. from the outside they seem more accessible than front office quant trading or research, but i’m not sure if that’s because there’s more demand, fewer people targeting them, or just a lower barrier overall. i’m mainly curious how the entry level market looks, what skillset is realistically expected in terms of math, coding, and finance, and how these roles compare long term in terms of mobility and comp. also wondering how people end up in these positions, whether it’s something people intentionally choose or if a lot of candidates land there after missing front office quant roles. i’ve seen mixed opinions on how technical the work actually is, so would appreciate honest perspectives from people in these roles

Hi, I’m a third year engineering student at Cambridge.

I applied to Optiver’s Career Kickstarter pretty randomly, didn’t think much of it, but ended up passing the OA. Now I’ve somehow got a final round cognitive interview in 4 days… and I haven’t done a single second of prep.

I’ve basically been putting it off because I’ve got exams coming up that I’m already cooked for, so realistically I can only put in about 2 hours a day over the next 4 days.

They also sent over a sheet about a market making game and told us to learn it. One of the examples was trading estimates on the population of Amsterdam, which actually seemed pretty fun, but I have no idea how deep they expect you to go with it or what they’re really testing there.

Genuinely not sure how to approach this or what actually matters for this stage. Is this something you can realistically prep for in a few days, or is it more about raw thinking ability?

Would really appreciate any advice on:

- what this round is actually testing

- how to prepare efficiently with limited time

- how much to focus on the market making game / what they look for in it

- anything people wish they knew before doing it

Right now I feel like I’ve accidentally walked into something I’m completely unprepared for.

Hi Y'all,
I have a bachelors in AI and Data Science and gonna start my Masters in Data Science this Sept, in KCL. I am really interested in Quants and I want to secure a Internship at a Quant firm such as Jane Street, XTX Capitals, Citadel, etc. With what i've researched, it seems that multiple firms start opening this June itself, for the next year Internships. I have searched a lot for a roadmap, that I can follow for preparing for applying to these internships, starting from what to study, where to study from, and how to test myself. I have exp in Software Engineering and intermediate level in Python programming and have good grasp in Math. I am starting from scratch, and only three months before the first applications open for the firms. What should I do? Appreciate any kind of help and advice. Thank You in Advance.

How good is the ecole polytechnique bachelor of science program math + one of the 3 double degrees for breaking into QT/QR/QD because it’s not talked about much but their math is genuinely top tier. Idk if I should accept my offer from there or Warwick MORSE.

Honestly, at first I thought it was a joke

A friend told me he made $2,100 in a week on a new official project, I didn’t believe him and even laughed, but later I decided to test it with a small amount, and it worked for me too, currently around +$200 per day

I know it’s not huge money, but I’m not using big amounts, and for me it’s вполне decent

If you’re interested, he left a guide on his profile

His username: lolbit_511

You can click it or copy and paste it into search, he’ll be the first one

I'm a Sophomore Computer Engineering student at UIUC / Georgia Tech (T5 CE program) and just landed a SWE internship at Oracle OCI for this summer (don't know my team yet).

My goal for next recruiting cycle is to land interviews at quant firms.

What should I be doing this summer and fall to best position myself to actually get those interviews?

For context:

T5 CE school (UIUC / Georgia Tech)

Oracle OCI intern this summer

GPA will be ~3.7 by next cycle

Any advice is welcomed!

I got into SIG discovery days and am going later in April and was wondering if anyone had any information on the interviews they are doing or anything about the event from the people who went to the earlier session.

Fortunate enough to receive offers for both courses. Leaning more towards Oxford due to the fact that I prefer the optional courses there although I do realise that Cambridge overall is probably the more prestigious programme. Is there a significant gap in prestige between Cambridge and Oxford when it comes to CV screenings. Interested in QR and QT roles.

Hello! I’m an incoming freshman trying to pick between these two schools. I’m aiming to go into quant while having SWE as a backup plan. Which of these would be more beneficial to attend? or has better recruiting?

Thanks!

I was wondering if there is an information inefficiency in commodities between futures and companies who work in the space (think PMPU-type companies from COT report).

Take the gold miners for example extract out the excess returns (equity alpha), that equity alpha embeds the markets information for the company's future cash flow derived from non-beta activities. Then fit that alpha against commodity returns and trade the residuals.

For a group of commodity verticals: oil, precious metals, mining, and agriculture I get about 1.1-1.3 sharpe. I used thematic ETFs as my proxies for the alpha. Since the results were decent I've started to refine my model.

I took every company from the Gold Miners ETF extracted their alpha controlling for various factors then fit those individual alphas to trade gold futures. The results are better since I get about 0.8-1.2 sharpe just for the gold futures model. I'm also starting to run the same approach for the other commodity verticals.

Any ideas on to help improve this model would be great. Or any feedback. I was thinking about some pre-processing tools to extract factors (PCA) out of my equity alphas before fitting them to the futures returns. I can also enhance my fitting using ML.

Here is the GitHub repo. There is a LaTex style pdf with the full writeup.

Howdy folks, I’m starting my first role as a QR at an HFT firm soon, I’ve already accumulated some literature I think is relevant/interesting. I’d be keen to hear from some practitioners your favourite bits of reading in order to hit the ground running! :)

Currently interviewing for a quant position in the investment risk team at Man Group. Team members I’ve met so far all seem nice and smart. Pay is pretty good.

I’m slightly concerned that it’s a position that’s not directly tied to alpha. I would prefer to be going towards the quantitative research side and have seen a few past employees at the investment risk team have gone on to quant research positions within Man Group.

Would this role be a good move for me (if I get it)? For context I’m currently working as a quant in the eTrading division of a large bank.

I wanted help like how do you find meaningful things out of anonymized features in kaggle type competition. And what score is believed good I am just not able to begin

So about myself:

I’m an engineering student, currently studying Computer Systems (+ hackathons).

I got interested in quant a few weeks ago but wasn’t fully prepared for assessments. I’ve started reading the Green Book.

My CV has passed screening at IMC Amsterdam and SIG (Neurolympics and CodeSignal), but I haven’t received replies yet, so there’s clearly room for improvement. Currently preparing for OA Citadel Terminal Europe.

I’m looking for someone in a ±CET time zone, preferably, but ET could also work.

My plan is to meet online about once a week to keep each other accountable, track progress, and work through exercises from the Green Book and LeetCode.

The goal is to apply for summer internships 2027.

Comment or DM me with a short background.

Hello! I’m a Pre-U student (18F) who just finished her A levels in Singapore. I have always enjoyed math and cs and am interested in a career in quant finance. I have natural ability for math but I do know that that is not enough to break into quant as it is highly competitive. Hence this post.

Currently, I hold an offer from NUS for a double major programme in Math + CS. I am planning to take the offer but also apply to Oxbridge/Imperial next year as I missed the chance this year due to some extenuating circumstances. If I get in, I will likely finish Uni in London.

I do have a few questions so I can maximise my chances of breaking into Quant.

1. Is NUS math + CS good enough if I don’t get into/don’t have the means of studying in London?
2. I heard Masters/PhD is important, so what are some PG programmes that I can aim for?
3. What can I do over the next four years in Uni? Courses? Competitions? Personal projects? EC? to set myself apart.
4. What can I do/how do I make connections and maximise on them?
5. What can I do right now? I have a few months till Uni starts. Someone close to me suggested that I cold email mid-level/smaller quant companies in Singapore asking for a shadow/internship so I can get some experience in the environment, but not sure how viable that is.
6. Likely, if I enter the industry, it will be in Asia. However, my long term goal is US. How can I “plan” my career path so that I will eventually be based in the US?

Currently, I don’t know a lot of people in the quant industry so I need help from someone within the industry. I have done quite a bit of research but the above questions are those that haven‘t been answered. Essentially, a “roadmap” to a Quant career would be greatly appreciated. I know it won’t be easy and there is a ton of competition and while I am not a genius, my goals and ambitions are not something I am willing to sacrifice and I will work hard (sacrifice my 20s if I have to haha) to reach them. Any advice and help will be appreciated. Thank you!

I got my link to OA Neurolympics and did it literally a week ago but still no reply (not even rejection). Though on profile website it’s written they usually give the replies. Or am I mistaken?

Was it 1-1 tech interview after Neurolympics I didn’t get?

😭😭😭

Hey everyone,
I’m interested in becoming a Quant Trader and studying Applied Math and Econ/CS

My options: MIT, Caltech, Harvard, UChicago, UC Berkley

any advice would be greatly appreciated!7

I just came across and attended a call by WSQ since I got curious. Frankly don't think I got much chance to be a quant since I didn't study math (did Econs), and just somehow bumbled into a govt-funded equity research role after graduation. They said they would let their so called mentors choose who they might want to work with, and may lower their fees by 2,100 pounds(?) from 5,900 pounds(?) (i.e., likely to 3,800 pounds). Converted to SGD (currency where i'm at), that's still around 6.5k though.

I mean like, I'm not sure if an SG quant firm would really take up someone that somehow paid for a course and pay that guy a 6-figure salary? Not sure if I can pick up the math and coding skills in a few months too??? Or if the so called mentors would be willing to continue to work with me as I work thru WSQ's materials.

I don't know. Is the course really good? Those that paid for and attended it - did it work out for you or did you just not care halfway through?

I'm not exactly keen on quant but just wanted to do more math and quant seems to be math-ish so... and maybe quant might be related to some econs too. In my FT role I've asked Claude to make simple web scrapers or json-to-csv convertors, not quite sure if these are even relevant.

Flattering though if the program would give me a genuine chance as breaking out of my currently not-so-good salary trajectory