Quant Researcher in Quant Funds: Dead-End Career Path?
After doing some research, I am becoming concerned that quant is not the place to be with the current state of the industry. It has been my impression that quants are particularly commoditized and/ or siloed. Basically my questions are this:
- Is quant researcher or trader still a good place to be in 202...?
- What are the most realistic exit options for quants?
- what are the best alternatives for quant research?
- what are the best non-siloed quant funds?
Thanks for the help.
bump
Good as in pays well? Yes Good as in career safety? In banks not funds Exit opps? Limited but they pay great so you could do an MBA and do something like product management or dare I say IB Best alternatives? Depending on your skillset and likes, could be research at a tech company, datascience, consulting, IB, startups etc
I'd probably generalize this to most of the hedge fund industry rather than just quant. Honestly, the outlook for the hedge fund industry is not great right now and the trends that you are seeing at the macro level - consolidation of assets, increasing reliance on technology, rich getting richer - are also happening at the micro level.
Meaning that this isn't the 90s any more when any idiot who graduated from HYP (and trust me there are a lot) could drop his resume at Goldman and be making 7 figures in 5 years. There are still and always will be successful people in hedge funds, but they are now few and far between. The barrier to success is much higher both in quant and fundamental and in fact the barriers are evolving towards the same place in both.
You will not be successful in quant trading these days if you only look at price data and don't spend time thinking about how markets fundamentally work. And you won't be successful in fundamental if you only look at 10Ks and don't know what standard deviation means. I hate using the word "quantamental" but this is what it really means, rather than some Bloomberg article about some fund spewing BS about how they use some exclusive alternative dataset of CEO farting patterns to trade earnings.
If you're having second thoughts about this right now before even starting this probably isn't the career for you. I've seen a lot of people in quant - IMO winners, math PHDs - who are really the cream of the crop intellectually, crash and burn pretty quickly. The main reason is because they really aren't interested in markets, they are interested solving math puzzles or researching new deep neural nets (and money, which is why they are at a hedge fund to begin with). To be successful, you have to be constantly be thinking critically about how markets function (goes for both quant and fundamental), not about whats the hot new machine learning technique.
The reality is there's no real difficult math that's needed to succeed in quant. People who say they are doing fancy machine learning are either 1. smart and just bullshitting you for marketing reasons or 2. dumb and actually think that stuff adds value.
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This is pretty accurate and reflects what I have seen. Critical thinking and creativity are perhaps more important than advanced mathematics and statistics. The latter are the tools we use to model or describe an idea. They can only ever be as useful as the quality of the idea. Good ideas often comes from deep understanding of markets. It might be a bit cliche, but Warren Buffet hit the nail when he said "Beware of geeks bearing formulas".
On machine learning and fancy techniques. I am one of those quants who is working actively in these areas. The premise here are the same as above. Assuming one has enough skills to properly apply these techniques, the main factor driving success and failure is the quality of the idea.
I"ve yet to seen any quant (note I don't mention L/S) make quantamental work. The datasets are either too sparse, or trading signals don't offer enough edge to provide a high enough sharpe. There are alternative datasets that do have signals but they disappear pretty fast.
Which means bread and butter is still technical signals. Unfortunately using only historical price/volume data is really crowded.
I still see differentiation for L/S analysts because its not just looking at 10Ks. They have access to management and being able to attend earnings calls, conferences, etc really helps with information you can't obtain as a quant.
I would bucket all of this as standard fundamental analysis, wasn't trying to distinguish reading 10Ks as something radically different than attending management meetings etc. Certainly quants do not systematically dial in to management meetings and ask questions, but they do analyze earnings transcripts etc. I don't think these things give L/S an advantage per se over quants it's just a different information source that they have access to, just like quants have access (and ability to analyze) certain datasets.
More importantly is how you differentiate your process from your peers rather than the differentiation between quants and L/S. Surely, L/S analysts can attend a management meeting, but if they come out of the meeting with the exact same trade as the other 20 analysts on the call there's not much value in that.
Sounds like you want to be a trader or in equity research or something like that. Definitely don't be a quant if you're not naturally inclined/interested in math/cs.
Thanks for reply I am a math major, but i am more fascinated by the markets and research. I like to dive into something and to be a detective. Also, I like math/ cs but it's not my main interest. So, what job and asset class would you recommend? Provided you had the skills for both, would you rather be a Quant or Fundamental?
I think your goal as someone coming out of college should be to get yourself into the right ballpark field/role that aligns with your skills/interests. You definitely shouldn't be deciding on an asset class/firm or smaller details like that- that will sort itself out in time and is largely influenced by randomness/your employers preferences as well. There's a lot of uncertainty you can't account for. The real world is a lot more non-linear than school is where you just get good grades and everything works itself out exactly as you envisioned.
If your question is aligned towards comp, I think the consensus is that fundamental pays slightly better than quant (due to siloing, and some of the points you've mentioned). But its close enough where I think you should be focused on the day-to-day and if you could see yourself succeeding at that job. In other words, the comp distribution for fundamental has a higher mean, but your specific factors will influence where you lie in each distribution.
For quant, does spending most of your time getting data, cleaning data, plotting data, writing infrastructure/tools, testing signals, monitoring performance, debugging code breaks seem appealing and something you'd be good at?
I am quant researcher who switched over from the tech industry several years ago. Let me give my 2 cents.
What is your definition of a "good place"?
In terms of renumeration, yes it is probably still one of the best paying areas, rivaled only by the top tech companies. However, the average hours in the HF industry can be much longer than in tech, especially for junior people who need to prove themselves. I went from working 40hr weeks in tech to 60+hr weeks when I made the move. It gets better after a couple of years and if your team or fund is doing well. I can get by with HFs tend to be more cut throat and less collaborative. During my time in tech colleagues were much more collaborative and we freely exchanged ideas and help out one another. Most projects were group efforts and colleagues were not so much clear cut competitors in the bonus pool. HFs are nearly the complete opposite. There is a prisoners' dilemma sort of a setting, and there tends to be minimal collaboration between colleagues. When people do collaborate on ideas, I find that they are inclined to hold back on sharing to preserve their edge in the competition for better bonuses. In my opinion, it is not exactly a zero-sum game since it is possible to grow the bonus pool by improving the team's overall performance. Ironically, it is difficult to get people to see this despite their supposed intellect. The collaborative culture in my previous job is something I sorely miss.
Despite all of the above, I still prefer the HF industry due to the empowerment and sense of and accomplishment that I can obtain. Working in the tech industry in a corporate environment, there are bureaucracies and idiot managers to deal with to even get started on an idea you believe in. The KPIs used to appraise you are generic and may not always reflect the brilliance and true value of your ideas or the complexity of the problem you were tackling. Visibility and politics are often more important than intellect and actually doing one's job. The expression "cog in the wheel" about sums it up.
A HF setting more or less dispenses with most of these bullshit. Most teams are small and there is no bureaucracies to deal with. The value (or the lack of it) of your ideas are clear cut and easily tracked through profit and losses. One or two good ideas can often be the difference between an average or good year for your team. Because teams are small, every researcher and his work truly matters and if one is indeed as brilliant as he believes, it is not difficult to gain full acknowledgement in such a setting, and quite possibly a small windfall in bonuses for the year.
Edit: Typos and grammar
so this really depends on the environment. If you are at MM then this is true. At larger funds collaboration is better, however again it depends on the culture. Places like G research for example are very close to what's described here.
Again, its also role dependent. For quant dev in HF your job is relatively more secure unless the fund, your team etc goes down but generally its easier to find another seat. If you are directly linked to PnL, which its not clear from the above post, then your head will always be on the line.
For those joining from tech or grad school, beware the recruiters and PMs that entice you with sweet words on large up-front payments in your first year and how you will be valued for your technical expertise/intellect. At the end of the day, they want return on their money, so make sure that you can actually deliver money generating ideas. Otherwise they will not bat an eyelid in cuttiing.
Also, hours in HF land are always much worse than tech. There are holidays / PTOs that you will never be able to take or tacitly understood you should not take if the markets are open. In quant specfically, terminal pay is about equal for both at FAANG vs seniority at funds without direct attribution from a book.
Yes the points regarding MM and quant devs are true. Couldn't cover the first point explicitly in my already long post. I wrote only about researchers since that was the focus of this thread.
Your last point regarding holidays and PTOs are quite different from my experience. At my place, only the devs and PMs are required to follow market hours. Researchers work normal hours according to the location of their office. But I guess this might be something that differs across firms/teams.
even within pods in a MM, there's no collab?
Thanks for reply I am a math major, but i am more fascinated by the markets and research. My main interests are finance and how the world works. Not math, CS or ML. So, what would you recommend? Should I pursue an quant research career or fundamental? Do you dive into companies and thinking about the qualitative aspects of a business?
I think you're asking the wrong questions here. Doing fundamental research and quant research are very different things. I used to be in a similar position as you, but I was lucky enough to get an internship in both and very quickly realised that my personality, temperament and capabilities are simply not cut out for fundamental research roles.
I'd also say it's simply untrue you can't do well in quant funds anymore. A lot of focus is on MMs or extremely siloed funds, but collaborative SMs also exist where the culture is much more like in tech. Again, success in both paths are slightly different - in one you strive to become a PM and manage risk, in the other you strive to become an expert in your domain more akin to other technical roles outside the industry. Once again these are also very different paths in terms of what skills and personality you need to succeed. There's a lot of focus on the former, maybe because of the glamour and "upside", but there's really nothing stopping you from being successful in the latter either. Yes, upside is probably lower (though not true either in the very top SMs) but in return your position is also much more stable, and there's nothing to say it can't be as or more intellectually rewarding than the former.
Ultimately I'd say what it comes down to is what you would be a fit for. Any one of these paths can be extremely rewarding if you are a right fit. For myself, after having seen a few crises from up front, I know I wouldn't want to manage the stress that comes with directly managing risk. I only manage a part of trading, but I'm given nearly full autonomy in deciding how things should work in my little carve out and I personally find the problem I work on to be very interesting. I simply couldn't see myself being successful as either a fundamental analyst or a PM.
This is very accurate, and has been my experience too. You get more ownership in a fund and the work you do is more critical, but there is not much collaboration even in a single-manager environment. You do your job, get paid and go home, and may not talk to anyone all day (or make small talk but avoid discussion of the actual work). Big tech gives you much better colleagues who may become your friends, but also a lot of pointless work that is motivated by trying to get the attention of executives. Most people lose interest in the work but stay for the money and lifestyle. The pay ceiling for non-PnL people is roughly the same these days, but in the tech world people increase their pay by changing jobs while quant is more about doing well in your hired role.
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I think it is still an attractive career.
Key is to find a firm at the beginning of your career where you can really learn and get good mentoring. This is difficult, especially if you come straight out of university and don't really know that much about different funds. All you can do is talk to a lot of people and ask questions during the interview process. Do a lot of background research on how the careers of people at the firms you are talking to developed. There is also a lot of luck involved.
You also need to have a clear objective at some point and then work backwards to see which of the available career choice make most sense. Do you want to become a PM at an MM? Or do you eventually want to move into a "Head of research" kind of position? Or stay a researcher without management or risk responsibilities? You might only be able to really make a meaningful decision of this after a few years on the job.
Myself, I want to eventually move into a PM role. I spent a few years at a large single manager quant fund and was lucky to have some decent mentors and got involved in pretty good strategies. Some of my colleagues there spent most of their time maintaining some highly commoditised strategies, which I found neither particularly interesting nor promising for further career progression. I am now at a new fund, where I am in charge of building up something new. I explored directly moving to an MM as a PM, but I don't really have enough experience for this yet. If I am successful at new current place, I hope I can manage a decent amount of AUM and build up a larger team within the next 2-3 years. I might consider moving to an MM as a PM if I get the opportunity and the new place does not let me grow as I want. So this is my plan for the next years. Lots of uncertainties and of course no guarantee for success, but it gives you an idea of how to plan a career in this field.
Congratulations! Though I think in your case this is probably the best situation possible for someone starting today so strong selection bias.
Even if you can find out which firms are a good fit to start your career, they may not take you on board. The interviews for some of the more established funds are heavily geared towards someone who has done stats/CS. So someone who has stem degree in other fields will find it tough to jump over.
Also, are you now working under a PM at MM or SM? Generally, those that choose the transition from their first fund are expected to bring on board strategies.
The commoditised strats are what pays the bills. When you run a low sharpe, high capacity strategy that can take a couple of B then charge 1-2% on the assets, its extremely lucrative. Ofc, it won't help you start a new fund.
yeah, I agree. I'm in that learning phrase still. Love my current role and it took me a year to find the right fit.
However, when FAANG comes to NYC in a few years, I think the quant job market will get shaken up. If senior researchers leave, I would be tempted lol
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