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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)

#51

Post by pinkmuffinere »

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…

Ya, I’m very surprised by the argument “you’re some of the best at numerical analysis and high frequency trading, and you’d be bad at anything else”, lol. That said, I think there are better reasons to work at such a place. Providing liquidity to the market is a good thing, and has real world value, it’s just hard for us to connect it to concrete outcomes. But as a simplified “toy” example, when they orchestrate a trade for/with a retirement fund, they help the fund improve its holdings at very low cost. That benefits everyone impacted by the retirement fund

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

#52

Post by Nursie »

keyle wrote: post #9
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.

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.

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.

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

#53

Post by arduanika »

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…

Amazing link. Including the car mechanic joke.

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

#54

Post by TeaBrain »

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…

>The alternative to highly technical, agile quantitative trading is fat middle men, wide spreads

No, this would be the alternative to securities and derivatives markets being electronic.

>If it didn’t provide value, nobody would pay for it.

The parent was remarking on the value provided to society, not the value provided to the firms.

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

#55

Post by Nursie »

pinkmuffinere wrote: post #51
Barrin92 wrote: post #24

Earlier quoted context omitted.

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…

Ya, I’m very surprised by the argument “you’re some of the best at numerical analysis and high frequency trading, and you’d be bad at anything else”, lol. That said, I think there are better reasons to work at such a place. Providing liquidity to the market is a good thing, and has real world value, it’s just hard for us to connect it to concrete outcomes. But as a simplified “toy” example, when they orchestrate a tr…

I think the amount of money that is creamed off for this service is disproportionate, and the amount of benefit to wider society a case of diminishing returns.

Allocation of capital, market liquidity etc are useful, but the size of the financial sector and the rewards it gives out for this shuffling of money are insane.

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

#56

Post by zknow »

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…

they make the mistake of paying for it unlike those who know what to do https://www.investopedia.com/articles/investing/030916/buffe...

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

#57

Post by TeaBrain »

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?

>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?

As with your other comment, this has nothing to do with what the original parent comment was remarking on. They didn't claim, nor did anyone else, that proprietary trading firms weren't making money and that people weren't well compensated due to helping firms make money. Their remark was that the value these firms are providing to society is questionable and that the highly intelligent employees could likely be providing greater value to society elsewhere.

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

#58

Post by FabHK »

pinkmuffinere wrote: post #51
Barrin92 wrote: post #24

Earlier quoted context omitted.

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…

Ya, I’m very surprised by the argument “you’re some of the best at numerical analysis and high frequency trading, and you’d be bad at anything else”, lol. That said, I think there are better reasons to work at such a place. Providing liquidity to the market is a good thing, and has real world value, it’s just hard for us to connect it to concrete outcomes. But as a simplified “toy” example, when they orchestrate a tr…

I think the liquidity argument is overrated.

The market has two functions:

1. Incentivizing convergence of the price towards fundamental value, to support proper asset allocation decisions.

2. Supporting buying and selling (ie "liquidity") to shift consumption in time (and enable productive investments with the delayed consumption).

Suppose a retirement fund holds their investments over a 20 year period on average, growing at a modest 4%. A 1% wider spread would reduce the return from 119% to 118%. I'm not sure avoiding that is worth the financial sector constituting 30% of GDP.

What would happen if equity markets were only open a very short period a day? Say you have one auction a day, or maybe two, and no continuous trading?

Everyone whose advantage is speed would lose out (HFT, some prop traders). Their current gain would instead accrue to those on the other side of the trades.

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

#59

Post by foobar10000 »

fireburning wrote: post #28
foobar10000 wrote: post #7

Earlier quoted context omitted.

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 :)

Personally know of 1 from Ghana and 1 from Nigeria - both engineers in HFT - both emigrated to the US post-college - so not that rare. Is it proportional to population? Of course not. Clearly there's going to be an english-speaking bias and an education availability bias and whatever bias du jour one wants to bake in. I don't think it is controversial to say that being born into poverty hurts - as naively as just accounting for malnutrition, for example, and going from there...

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

#60

Post by Infernal »

Workaccount2 wrote: post #46
madars wrote: post #31

Earlier quoted context omitted.

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…

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?
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