Huh? What happened? This is a very interesting claim I would love to hear elaborated
The thing is that there isn’t really strong institutional demand for exotic derivatives, people are happy using existing methods and just applying those to current markets.
The other type of fancy math has to do with deriving alpha, which is also not that complex, from a statistics perspective you’re mostly using linear regression or other basic forms of regression.
The hard part of quant is implementation, making sure your data is right, hunting through poorly understood markets, and managing risks carefully and understanding them.
There’s also ML but that’s equally complex in quant as it is anywhere else.
In my experience I have seen far more division of labor than you describe. Real quants don’t do work like making sure your data is right or even much of implementation; they delegate that to software engineers. But a cheap quant shop might be too cheap to hire SWEs so quants end up doing this work instead. The real quant work is just hunting through poorly understood markets.
It’s essentially IT/data work - the days of sophisticated maths are mostly gone. There always was a lot of code, but these days for most people there’s little to no new maths.
From what I’ve seen, post-2008 the job changed significantly, with more IT, less maths, more standardization - basically the job moved from bespoke everything to super industrialized. You’ll be able to have your model work for one underlying and one product, but what’s really useful is for lots of underlyings and many products - and that’s very hard.
That being said, and that’s important, you must understand the maths behind, otherwise you won’t be able to do anything useful.
You are right. For most people there's little to no new maths.
But not for all. There's still plenty of good quality math to be done in the exotics space. However, there's a bit of Catch 22 that prevents people from doing new math: all the big shops have had exotics libraries since before 2008, and because of the exotics hiatus between about 2008 and maybe 2013, the research momentum was lost. After that, most quants in the space were happy to find ways to use the old stuff, and apply small tweaks at the margins. Most small shops use vendor models (Numerix, Murex) or open source (QuantLib), and people who use vendor solutions or open source are not looking for cutting edge stuff.
But there's still good math left out there.
I didn't go to NYC, but Money is fungible so it's a simple math problem.
How much non-parasite good can you do making $50k/year * 10 years? Even if we ignore taxes and you donated your entire salary, that tops out at $500k worth. If instead you could make, say, $500k/year * 10 years, and then quit and form your own non-profit for $2,000,000 and do 4x as much good.
It is easy to fall into the trap of thinking HFT/low frequency quant firms "leech wealth".
You can get out of the trap by learning about what they do and the essential role they play in the proper functioning of our markets.
A better angle is how finance tends to acquire a ton of smart young people that could/would otherwise be doing work that has more benefits to society. It’s hard to blame the individual here, because the salaries are orders of magnitude larger in finance vs. say, aerospace engineering. Would I turn down $700k at a hedge fund to earn $90k at a science lab? Probably not, unless I was already independently wealthy.
djoldman•1h ago
MUCH has changed since then.
keiferski•1h ago
https://www.dropbox.com/scl/fi/da7zfjj2rplwzf2sfiriz/Buy-Sid...
apt-apt-apt-apt•1h ago
Some options seem to be: Upload to google drive (inconvenient), use some open-source tool (LLM suggests DangerZone), use a VM (very inconvenient)
nebezb•1h ago
I’m assuming the attack surface is reduced. I invoke it through a docker container. But this might be a misplaced sense of safety.
[0] https://github.com/microsoft/markitdown
qwertox•1h ago
philipkglass•48m ago
bormaj•56m ago
r_lee•1h ago
altmanaltman•1h ago
dang•49m ago