Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)
29 comments
·March 14, 2025Workaccount2
bblcla
Tyler Cowen did an 'ask me anything' at Jane Street when I interned in 2016. One of the interns asked him exactly this: "What do you think of the fact that we all work here instead of, I don't know, curing cancer?"
He replied with, roughly, "Those of you who work here probably couldn't do anything else other than perhaps math research. Arguably, working here is the economically efficient use of your time."
I think about whenever I see a comment like this. Quant firms select for a very specific set of skills. In particular, I've found that many traders/software engineers in quant are very smart but not very self-directed. Places like Jane Street work well for people who can excel, but only when given a lot of structure and direction. I think this is not unrelated to why so many people 'accidentally' end up as traders after going to an Ivy League school!
Barrin92
General intelligence is overstated sometimes, but it is a thing. Someone who is smart enough to work for Jane Street probably could at least be an intelligence analyst or software developer at the NSA contributing to national security. (Jim Simmons literally was a code breaker during the Vietnam War)
I don't think there's a gene for playing esoteric minigames on the options market while you literally suck at everything else
twoodfin
If it didn’t provide value, nobody would pay for it.
The alternative to highly technical, agile quantitative trading is fat middle men, wide spreads, and capital sitting in 8%* stupider places than it would otherwise. That’s a pretty big deal even if the observable effects are extremely diffuse.
* Made up number, but if we woke up on Monday with nothing but the tech we used to trade in 1984 it would probably hit much worse.
czk
This reminds me of Renaissance Technologies (Jim Simons, PhD in math from uc berkeley).
He started the company in 1982 after he left academia for finance and leveraged quant models for training, they mostly hire PhD mathematicians, physicists and scientists, working on algorithms.
They have a fund called Medallion that is closed off from outsiders (you have to be an employee I believe), and it averages 66% annual gross returns (39% net after fees). Generated hundreds of billions in profits.
__cxa_throw
Theres large portions of the tech industry that are pretty useless to society too while paying incredibly high salaries random examples include: - facebook/google ads teams - various SaaSLOP companies
Lots of smart engineers that work on making buttons pretty and A/B testing crap rather than pushing the boundaries of science.
xrisk
At least it’s arguably better than working for giant ad engines.
keyle
I take the silver lining. Smart people getting rich is better than dumb people getting rich. Hopefully some day they'll do something good with that money.
tikhonj
Eh, hard to say that when the main alternative (math, physics or CS research) requires jumping through a lot of selective hoops, barely has positions available, and absolutely no trouble filling all the positions they do have.
LeroyRaz
I agree, how dull and uninspired. I'm very much with Paul Graham, who believes in the creation of wealth (as opposed to the extraction of money).
anonym29
Can you codify the difference? I seem to be fundamentally misunderstanding the difference between wealth creation and wealth extraction if voluntary market activity constitutes extraction.
I'd definitionally describe all voluntary transactions free of coercion to imply the buyer values the utility of what they're buying (i.e. true wealth - piles of currency are not true wealth, they're what you exchange for true wealth) more than the currency they're trading for it, no?
Involuntary transactions featuring coercion on the other hand, like the government demanding you pay taxes under threat of imprisonment (enforced at gunpoint, if necessary) are clearly extractive, by my definition.
LeroyRaz
Money Extraction: fighting over a slice of pie.
Wealth Creation: creating new pie.
In practice, a lot of things that look extractive (e.g., designing better high frequency trading algorithms) potentially have some marginal utility (e.g., creating market liquidity), but the money these people make is likely larger than the utility they add to the system (because most of the money in having the best high frequency trading algorithm comes from beating other people's high frequency trading algorithms).
foobar10000
While there's many definitions, I'd concentrate on zero-sum vs non-zero-sum games. Lots of games in trading are effectively zero-sum games - if I make 100USD, you lose 100USD (there's details about transaction costs going to exchanges that make this more nuanced, but the principle applies). A chunk of financial engineering games are not : for example risk pooling games. A big part of finance for example is liquidity provisioning games - which kindof boil down to risk pooling games in the limit. But unfortunately - a _very_ big chunk of the financial markets is zero-sum.
Even in a purely digital world - most of the economy is not zero sum - i.e., it _creates_ wealth. I pay you 100USD for 1 million LLM tokens - a purely digital transaction - the net result of this is the 1 million tokes that I can consume and use - net of the transaction.
czhu12
Been following signals and threads for a while, and it’s amazing. Have to be in a learning mood, but it gets pretty technical. Podcasts are a tough medium to do that in but if you really zone in, signals and threads is fantastic
__mharrison__
I read this and think: "I would love to spend a day with Jane Street and teach them how to use notebooks." So much effort is wasted because of knowledge gaps or systems that don't encourage best practices.
I just taught a course to a client this week helping them with this (and other best practices for Python).
hardwaregeek
I love this podcast but I can’t listen to it while running. It’s too interesting so I risk falling off the treadmill :D
laidoffamazon
> In Young Cho thought she was going to be a doctor but fell into a trading internship at Jane Street
Genuinely perplexing how they always try to show each multi-million earning engineer as some normal person and not someone that went to Exeter and Harvard
foobar10000
I don't really see a lot of elitism in these circles - there's a chunk of such engineers that did not in fact go to Exeter and Harvard - but what they have in common is they are all to a fault very bright technical people that can produce complicated things quite quickly, and can communicate effectively with people around them - to make sure that what they produce is in fact useful :)
fireburning
ever meet any such engineers from the bottom 20% of the world population? just some food for thought :)
ecshafer
Graduating from a SUNY school, Jane Street gave me an interview and a fair shake. I didn't get the sense of elitism there. There does happen to be a lot of really smart engineers, mathematicians and scientists going to Harvard, MIT, etc.
There are places that without that Ivy League or Target School degree you don't hear back, I don't think Jane Street is one of them.
heavymetalpoizn
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brcmthrowaway
Ten years ago, all the $1mn+ earning engineers were in trading. Now they are in LLM/AI. Glad to see this happen, Jane Street has increased their advertising here because of this.
I will eternally find it sad how much talent is wasted on trading. So much money, so much intelligence, so much time and effort, all the provide almost no tangible value to society.