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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)

#71

Post by philosopher1234 »

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…

Sorry but this is a shit definition.

You’ve defined scamming people, a totally voluntary error, as creative not extractive.

You’ve also defined building roads as extractive not creative.

I think you’re latching onto some very misguided principles.

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

#72

Post by philosopher1234 »

objektif wrote: post #33
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.

Would you rather people spend their time on centering divs? Or come up more ways to make people click on ads. I see this type of view often on HN from big tech employees. Get off your high horses people.

You haven’t contested the substance of the argument at all. It’s as though you agree.

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

#73

Post by Workaccount2 »

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?

That is the issue.

The amount of gold recovered by them as a function of the entire global gold market is a minuscule rounding error. A loss so small that when distributed across every market participant (as it would be if left alone on the ground), would amount to no practical discernible difference in anyone's life.

But having 15 less top notch surgeons not doing surgery? There stands to be many practical discernible differences in many people's lives.

Keep in mind, the surgeons are not the only ones out there. There are large armies of grunts combing those streets 24/7 picking up all the easy pieces. The surgeons are there to get the dust that everyone else misses. It's an enormous waste of talent.

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

#74

Post by laughingcurve »

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.

Society has the problem, not the individuals.

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

#75

Post by Workaccount2 »

twoodfin wrote: post #13
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.

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…

My actual gripe is with where that value comes from, and what it's true cost to society is.

I'd argue that pulling these people out of moving society forward is just another form of externalized cost. The stanford guy who figured out how to halve the cost of solar in 2012 never got to realize it because $750k/yr to do stochastic modeling of cattle feed to (secretly) overcharge farmers for futures contracts was just too enticing.

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

#76

Post by polygot »

Very interesting podcast, I find that the guest was very candid so it was great to hear what it is really like working at Jane Street.

The reproducible-Python notebook problem/notebook for researchers mentioned in the podcast inspired me to create a new project, branch-pad https://github.com/alexyorke/branch-pad which is an interactive Python notebook environment that allows you to create and explore multiple branches of code execution.

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

#77

Post by elefanten »

Barrin92 wrote: post #24
bblcla wrote: post #16

Earlier quoted context omitted.

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 everythi…

I didn’t take that to be his point. I assume he says “economically efficient” because he means their strongest skillsets don’t have (m)any other uses and they wouldn’t be realizing their potential by leaving those skills unused.

He probably overstates that case, especially talking to early career interns that haven’t yet narrowed their specialization and could pivot to other highly quantitative roles that use other high level math.

He’s also probably flattering his audience, to whom “math research” is more likely to be status-bearing.

Doubt he’s saying they’d suck at anything else.

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

#78

Post by [deleted] »

twoodfin wrote: post #45
godelski wrote: post #39

Earlier quoted context omitted.

Lots of things provide no value that people pay for. The inverse is true too: lots of things provide value that no one pays for. I find it shocking that anyone that programs would think this way considering how widespread and common open source tooling is. I don't know how you can get through your day without using OSS or even free websites like stack overflow.

Of course the inverse is true, and you don’t have to stick to software. Raising children produces value despite no one exchanging currency. But generally nobody pays quants to lose money. They expect value over the other opportunities they have to use that same money. Is this really controversial?

[deleted]

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

#79

Post by godelski »

twoodfin wrote: post #49
godelski wrote: post #40

Earlier quoted context omitted.

I'm pretty sure the parent is implying that there is quite a disproportionate distribution.

Sorry, implying what? That Jane Street quants aren’t getting rich enough ?

Read the comment again

  > The problem is that smart people are the ones being employed, not the ones getting rich.
Employed is a key word. Generalize the point beyond Jane Street if you're still having difficulties. Such general understanding will be necessary if you want to work somewhere like Jane Street.

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

#80

Post by godelski »

twoodfin wrote: post #45
godelski wrote: post #39

Earlier quoted context omitted.

Lots of things provide no value that people pay for. The inverse is true too: lots of things provide value that no one pays for. I find it shocking that anyone that programs would think this way considering how widespread and common open source tooling is. I don't know how you can get through your day without using OSS or even free websites like stack overflow.

Of course the inverse is true, and you don’t have to stick to software. Raising children produces value despite no one exchanging currency. But generally nobody pays quants to lose money. They expect value over the other opportunities they have to use that same money. Is this really controversial?

Your comment comes off as "people pay, therefore it has value." Which the inverse would need to be true in that case.

But you are conflating money and value. As you stated, raising children produces value, and as you imply, this is not generating revenue. Which you are also conflating exchanging money with generating value. Sure, liquidity can generate value but don't confuse these things.

People seem to be forgetting that money is a proxy and that a proxy is not the same as the thing you are proxying.

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