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Comment by wuj | Hacker News Reader

HFTs exploit price inefficiencies that last only milliseconds. The time-series data mentioned in the article is on the scale of seconds. I wonder if its possible to get the time-series data on the scale of milliseconds, and how that would affect the training of the objective function in a LLM.

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Todays derivatives and their pricing are based on the premise that stock prices can not be predicted and behave like a Brownian motion system. If you take real time data from any stock and calculate in order how many times a stock went up in a row or down in a row you end up almost perfectly with a natural probability distribution. HFT's are involved in market making and arbitrage both of which already involves high speed, the later much more, and earning minuscule profits. There are ghost patterns who can be mined for a certain period of time but they are not solely calculated based on trading time series. They involve complex proprietary calculations, some machine learning and relationships between stocks. There is no pattern in the flow how a particular stock is trading.

Also from a long-term view its very questionable. How should a model be able to predict that in the middle of a high interest environment, a tech bubble burst and a dumping stock market in general, a new platform called Chat-GPT gets launched that basically carries the whole world's stock market to new heights which causes among other things retail investors to liquidate bonds and other high interest environment assets and flood it into the stock market. It is more than completely of the text-book. That can not be predicted. The million dollar spending guy is at the end the same way off as the guy who simply employs a 100 python line trend-following strategy.

Derivatives are priced under those assumptions because the aim is to calculate exposure/risk (where simple / assume you're wrong is desirable), the pricing is sort of an afterthought most of the time.

> How should a model be able to predict that in the middle of a high interest environment, a tech bubble burst and a dumping stock market in general, a new platform called Chat-GPT gets launched that basically carries the whole world's stock market to new heights which causes among other things retail investors to liquidate bonds and other high interest environment assets and flood it into the stock market.

Because it happened in the railroad boom in the 19th century, the roaring 20s, the 80s, the 90s dot com boom, the biotech boom...

History rhymes, and as we know, LLMs make decent rappers.

The tech is different but the people are the same.

The data is reasonably easily acquired, for a price...

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