Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

signalsandthreads.com

Post reply on HN
Print view View original

21–30 of 157 posts

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#21

Post by foobar10000 »

anonym29 wrote: post #14
LeroyRaz wrote: post #10

Earlier quoted context omitted.

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).

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 weal…

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.

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#22

Post by czk »

Workaccount2 wrote: post #4

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.

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.

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#23

Post by heavymetalpoizn »

dgfitz wrote: post #12
Workaccount2 wrote: post #4

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.

Smart people who grew up poor making their own way, isn’t that the idea? Or do we just assume they’re all rich, privileged folks?

[dead]

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#24

Post by Barrin92 »

bblcla wrote: post #16
Workaccount2 wrote: post #4

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.

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 ab…

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

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#25

Post by __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).

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#26

Post by YZF »

foobar10000 wrote: post #21
anonym29 wrote: post #14

Earlier quoted context omitted.

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 weal…

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…

Financial markets are not zero sum. Wealth is created or destroyed in financial markets despite each trade having a buyer and a seller.

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#27

Post by heavymetalpoizn »

ecshafer wrote: post #15
laidoffamazon wrote: post #3

> 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

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.

[dead]

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#28

Post by fireburning »

foobar10000 wrote: post #7
laidoffamazon wrote: post #3

> 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

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 :)

ever meet any such engineers from the bottom 20% of the world population? just some food for thought :)

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#29

Post by __cxa_throw »

Workaccount2 wrote: post #4

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.

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.

Re: Finding Signal in the Noise: Machine Learning and the Markets (Jane Street)

#30

Post by tikhonj »

Workaccount2 wrote: post #4

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.

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.
Post reply on HN