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Comment by lordnacho | Hacker News Reader

I'll second that. I've done options trading, trend following, and HFT. Often you need smart people to do simple things, but they are still simple things. Gotta remember there's a lot of noise in financial data, and you don't actually have as much of it as people think. Even all the ticks on all the exchanges fit in a few GB of binary per day.

RenTech is especially good at acting like they're from another planet, which I'm sure helps them attract those stellar mathematicians.

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Your especially right about the noise in financial data. Nice thing about linear models (vs i.e. random forest, or even worse deep learning) is that they are limited in how they can overfit the noise. They only fit a known function to known regressors.

And, even more important, they aren't susceptible to adversarial activity like a deep net could be.

RenTech is also basically the only largest hedge fund that has beat the market by a wide margin for decades. An average 66% annual return in their Medallion Fund since 1988 according to wikipedia. That is pretty much insane and seems to be something only space aliens could do. If anyone is using quantum computers to help trade, it is probably them.

Worth noting that their public funds don’t return anything like the rumored Medallion fund returns (though they are generally pretty good).

Medallion is also kept very small because I would guess the tricks that they use to keep those returns so high (maybe even some sort of topological quantum field theory!) don't scale well to larger investments.

Not sure if I would call ~$10 billion very small and making $6-7 billion per year is good chunk of money. But, yea, I'm sure that would get bigger if they thought they could keep their returns high.

The Medallion Fund has already reached their max investment amount so while it's ground-breaking, no new RenTech employees can take advantage of it.

> An average 66% annual return in their Medallion Fund since 1988 according to wikipedia.

The claim, the secondary (tertiary?) source, and the primary source make that all hard to not smile at.

66% annualized returns are more likely to be pyramid schemes - but that couldn't happen, could it?

That's because it's not 66% but instead $6B. If they had twice as much capital it would be 33%, and if they had ten times as much capital it would be 6.6%. I'm simplifying to show the main point.

That's actually been surprising to me but makes sense: "the entire history of the stock market" is not that big in terms of data, and the dynamics change frequently enough to where things that happened in 2000 are almost useless from a machine learning standpoint, my models perform best when trained on a much more selective subset (I believe because the reasons for trades and market participants keep changing, so the dynamics change enough to where old rules don't apply anymore).

Correct. You can make money using only yesterday’s data for training purposes.

Can you distinguish noise from non-linear correlations? I feel like you can never prove the absence of non-linear correlation, but only showing it‘s presence once modelled/detected

> Even all the ticks on all the exchanges fit in a few GB of binary per day.

This isn’t true once you include equity options, which have several orders of magnitude more data.

However your general point still stands, because most options trading strategies don’t need such extreme granularity of data. Much of it can be ignored, or close to it.

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