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.
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.
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 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