The Algorithm Behind Jim Simons's Success

> And then, the academic perspective is that prices should be modelled as random walks, though you may talk/learn about things such as "trend" and volatility.

The math involved in finance and economics always seems way behind that of other fields. The problem is that the other fields with more advanced math are so deep in theory that the people working in those areas are often either unaware of the potential real world applications of their work, or they are simply not interested in it (I’ve noticed there seems to be little overlap between the type of personality inclined to explore abstract theories as its own reward and the type of personality that prefers to apply existing knowledge to a real world problem).

> Suggesting that hidden variables/states/transitions can be learned from historical data is usually considered pseudo-scientific.

I mean, there’s a definitive answer to the question of stock market predictability. Unfortunately, it’s also uncomputable: if the conditional Kolmogorov complexity of a stock price time series given relevant auxiliary data is less than the size of the time series data (roughly speaking), then the stock price is predictable to some degree. Otherwise, it’s not.

I would be extremely skeptical if anyone claimed that stock price is truly Kolmogorov-random. However, I also think no single trading group’s algorithms (and data) are sufficiently more advanced than any other group’s to the point where algorithmic arbitrage is obvious to the market (or maintainable over a sufficiently long time period). I would not be surprised though if a sudden ML breakthrough destabilizes the entire market at some point in the near future when one group does in fact realize a step function improvement in their algorithms.

I think this is one of those cases where conflating "unpredictable" with "random" breaks down. As a matter of simplification, we treat many unpredictable processes as random if making the process at least somewhat predictable is sufficiently intractable. While this can change very quickly e.g. breaking encryption algorithms, for many data models the gains in making a process less unpredictable are more incremental and are largely dependent on having both better math and more efficient compute.

Unpredictability is as much a computational intractability frontier as it is a math problem. We know how to do approximately optimal prediction, but if you have to throw a supercomputer at the calculation and wait until the heat death of the universe to get an answer (which is the essential reality) then it has no value. But if you can grind out small improvements at the prediction frontier on a tractable amount of computing hardware due to algorithm advances and mathematical improvements in more narrow cases, then you have an almost unbounded greenfield to work with and these improvements will generalize well across diverse markets.

For three years? Is that a serious comparison?

And yeah, it’s not remotely surprising they’ve made trades like selling NVDA at $700. Judging a fish by its ability to fly etc. RenTech doesn’t work by picking stocks based on industrial trends or anything — as far as we know that sort of stuff is literally not even an input.

13Fs are only filed quarterly. RenTechs positions are held very short term.

IIRC, their ELI5 testimony to the Senate (not the one you linked elsethread) is that RenTec's long-term strategy is to make a small profit over many many transactions. Versus buy and hold, or value invest, or whatever.

I don't understand anything about finance. That said, it sounds to me that RenTec is (or portraying themselves as) a classic volatility based hedge fund.

(A good friend is a hedge fund trader. He has tried to explain the maths to me a few times. Something something about Brownian motion, NPV, predicting herd migration. Alas, I am but a simple bear.)

But all their data collection gives me pause. I do think they they're better at spotting market signals. Like using FourSquare check-in location data to predict retail performance. Like using a VPN to spy on users to spot emerging competing startups.

My pet theory is that RenTec's play is restraint, to be patient slow capital. Even though they (probably) have data for bonanza predictions, like your NVDA example, they some how have the discipline to eek out modest profits, preferring consistency over riding the tiger.

It's been an utter cultural disaster. We've missed out on so much original science and progress because these smart idiots threw away their talents on building machines to game the casino, when they could have made game-changing contributions to fundamental original research.

Imagine if Shannon, Turing, Von Neumann, Einstein, and Dirac had done this.

Yes, they put some money back, but not nearly enough to compensate for the damage.

The real disaster has been normalising this kind of "success" as the best of all possible achievements, when in fact it's spectacularly cheap and unambitious compared to the goals of previous generations.

If anyone thinks I'm overstating the heresy here, remember - a financialised economy is optimised for short-term gain, not long-term development.

The flip side of "investment" is an economy where hundreds of millions are bankrupted by health insurance, where rents are unaffordable (never mind property), where workers are treated like spreadsheet assets and not like people, where fraud is endemic, where many people are putting off having kids because they literally can't afford them, where planes fall out of the sky, and where the entire machine regularly demands government bailouts because it's stuck in a manic depressive cycle of overconfidence and opportunism followed by collapse.

That's not even looking at the incredibly toxic political effects.

Eh, it's hard to call it much of a "brain drain" when getting a research job is so difficult. There's no shortage of smart people interested in working in research for less than they'd make at any professional role, much less in the highest-paid industries.

PhD programs pay basically nothing, are selective, require candidates to jump through all sorts of hoops and still have no trouble filling out. Later on, becoming a professor—or some other sort of researcher with similar scope, autonomy and funding—is basically impossible, harder than making a bunch of money in quantitative finance. And yet each opening has hundreds of realistically qualified applicants. (Realistically qualified in the sense that they'd be able to do good research, anyway.)

A 0.1% edge is sufficient.

Yeah

Making 60% a year would still be very high after tax. That’s why he accumulated many billions of dollars.

They would be more impressive if he wasn't the biggest tax cheat in US history.

I can't tell if you're joking or not but that's an interesting approach for sure. I'm surprised gene screening was accurate enough to do that 20-40 years ago?

LOL. I think he was an idiot, in that regards. Similarities to Steve Jobs, who resorted to quackery with his cancer. People can be geniuses and dumbasses at the same time.

What about giving cancer to others by secondary smoke inhalation, what about tongue cancer and mouth cancer and gum disease and cardio-vascular problems and breathing difficulties and eventual COPD and all the negatives of smoking that aren’t lung cancer?

Is it? Being on a constant drip of nootropic nicotine might be an important factor

And if you ever have to choose between the two, you can choose what you value more. But I disagree with the premise that they're mutually exclusive. For the most part your career and financial success is orthogonal to your personal relationships, and to your health.

This is wise, another angle on this that your reputation is the best investment. It is in your control and can't be devalued as easily as a house, car, portfolio.

Only Grigori Perelman has won a Millennium Prize.

Madoff took in other people's money. The Medallion Fund stopped taking new outside money in 1993, and in 2005 it got rid of all outside money. The people making (or potentially losing) money are the people making the trades.