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

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

#91

Post by jxjnskkzxxhx »

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…

> 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."

Complete garbage. The same way that Jane Street hires smart people that don't know anything about trading and those people contribute, the same would be true if there was money in curing cancer.

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

#92

Post by leohonexus »

madars wrote: post #31
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.

Why would it be wasted? I like apples and I like being able to buy them any day of year, even out of season. The only reason I can do so is because there is an entire industry of people who manage the inventory, distribution, try to predict supply and demand, and take on a risk doing that. The principal reason why I can buy and sell equities at very small spreads any day of the year is similar: traders are competing…

Thank you for the link, it was very insightful.

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

#93

Post by upbeat_general »

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

Seconding another commenter. I went to a state-school (maybe in the top 5 US state schools) and got an offer without any elite background.

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

#94

Post by FridgeSeal »

Infernal wrote: post #60
Workaccount2 wrote: post #46

Earlier quoted context omitted.

There is an extreme case of diminishing returns at play here, and unfortunately the amount of money that flows through these markets is so incredible that it becomes worth it (more than worth it) to commission the top minds of society to push the limit as close to 1 as absolutely possible. Derivatives have great value to industry. Derivatives that require the fuel of 15 math Phds to lock in fractions of a percentage…

And yet if there was so much gold dust lying on the sidewalk that you could pay 15 Harvard med surgeons enough to pick it up and still have some left over, would you just not?

I think I’d rather have the surgeons saving peoples lives tbh.

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

#95

Post by vismit2000 »

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 sentiment is also covered in 'Zero to One' by Peter Thiel.

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

#96

Post by ErikBjare »

__mharrison__ wrote: post #25

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).

I've been back and forth whether notebooks are really "best practice".

Currently leaning towards no, as they are hard to test, compose, and version control (it is possible, but you need bespoke notebook-specific tools, and most just don't).

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

#97

Post by laidoffamazon »

upbeat_general wrote: post #93
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

Seconding another commenter. I went to a state-school (maybe in the top 5 US state schools) and got an offer without any elite background.

Obviously Michigan, UCB, UDub aren’t in the same category, especially with prior trading firm experience.

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

#99

Post by arthurofbabylon »

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…

Tyler Cowen, master of the ‘cum hoc ergo propter hoc’ fallacy. He frequently mistakes the occurrence of phenomena for causative proof of that phenomena. He particularly exhibits this inclination when his confidence rises amid scant data (like the rest of us).

This error seems to be a particularly common (and often lauded!) trait among those who work in high-conjecture low-evidence fields (eg, economics). The prominent thinkers become skillful at deploying this fallacy: “see, it’s there, therefore is certainly the cause!”, using their credentials and esteem to mask the error. Listeners think, “well he’s a smart, respected guy,” and nod along despite the missing logical link.

I greatly appreciate Cowen’s podcast, and I definitely respect him as a thinker and inquisitor – so I don’t mean to discard his work or opinions (in fact, I appreciate his occasional brashness because it exposes the underlying thought/principle). However, many of his aggressive-yet-speculative statements (like the one you roughly quoted) are best received with an understanding of the error.

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

#100

Post by Nursie »

in3d wrote: post #81
Nursie wrote: post #52

Earlier quoted context omitted.

I’m not sure that’s true either. See for example “effective altruism”, which turns out to have been neither, but more of a self-deluded justification for insane greed, coupled with a god complex.

Ridiculous, uninformed comment. There is no question that Effective Altruism has done tremendous good overall by saving many, many lives. I say this as someone who disagrees with important aspects, such as valuing distant lives equally to local ones. They have also been more correct than anyone else about AI, pandemics, etc.

It’s also been used as a self-justification by the likes of Sam Bankman-Fried, who exemplifies the qualities I mentioned above.

It’s clearly a very flexible philosophy that “smart people” can use to justify pretty much whatever, and given the presence of such people as SBF and cronies, certainly doesn’t support the notion that it’s a great thing for “smart people” to get rich, or really that we should expect that to be any more than neutral.

“Smart People” can be scumbags, and some prominent EA folks were, all the while shouting about how good they were.

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