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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)

#131

Post by Workaccount2 »

TheAlchemist wrote: post #83
Workaccount2 wrote: post #75

Earlier quoted context omitted.

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 t…

The way I see HFT, is that previously this money was going to brokers and banks. Now, most of this money is going to HFT shops, but you could also make an argument that some of it stays with the investors, since spreads are much smaller now. There is 0 cost to society, maybe even a small gain. As for moving society forward, I don't know. If not in finance, most of these guys would work for big tech companies trying t…

These are just first order effects. I'm talking about second and third order effects that I would argue make the value prop of tighter spreads enormously negative to society on the whole.

Liken it to the government deciding to spend 40% of the budget on roads. Suddenly the roads quickly get pot holes filled, the lines are seemingly always freshly painted, cracks are all filled, and even mildly uneven roads gets freshly paved.

The first order effects of this would all be positive. The transportation dept. could talk all day about benefits to everyone. Everyone would love the great roads.

But spending 40% of the budget on roads is insane, and the second and third order effects would be disastrous to that society.

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

#132

Post by Workaccount2 »

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.

Funny enough I don't work in tech, but rather manufacturing.

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

#133

Post by data-ottawa »

ErikBjare wrote: post #96
__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).

Why are you trying to test and compose notebooks? Notebooks don't really fit into that lifecycle of work, they're implicitly script-like code.

Any time a notebook needed to be tested, refactoring it into a module and testing that was the better choice.

Notebooks in my opinion are by far the best tool for interactive and exploratory data work. I've been using Jupyter/IPython for 10 years and it takes very little discipline to keep them clean and clear. I've never bothered trying to deploy them in any meaningful way.

The quirks with version control are annoying, that's one reason I've switchex to marimo in the last few months.

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

#134

Post by pclmulqdq »

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.

I went to an "elite" school, but I worked at one HFT where the local team of 5 people had only me with a background from a similar school, and another HFT where I was one of three on my immediate team of ~12 engineers. At one point, one of my colleagues at the second firm asked me why I was there as opposed to the alternatives of (1) a company with more of a focus on the elite and cultivating power or (2) being an artist supported by my well-off parents.

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

#135

Post by whiplash451 »

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 recommend you read the life of Jim Simons (through The Man who Solved the Market) as well as a recent HN thread on DeepSeek showing how their trading arm finances the whole company.

There is much more nuance in this world than your post implies.

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

#136

Post by whiplash451 »

czk wrote: post #22
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 gro…

Well. Read about him all the way to the end, then.

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

#137

Post by owl_vision »

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…

I plus-one the last paragraph, well explained.

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

#138

Post by upbeat_general »

laidoffamazon wrote: post #97
upbeat_general wrote: post #93

Earlier quoted context omitted.

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.

And it was none of the mentioned schools!

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

#140

Post by mhh__ »

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…

That isn't really what the math people are doing. Pricing is easy.
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