It'll do great. As everyone in the industry knows, past performance is always indicative of future results.
It will be like you are at the horse race, a punter reads the horses form in the local paper. Versus the computer runs a tuned up linear regression on thousands of variables about past horse races, weather, tracks, horse injuries and so on going back 10 years.
What I replied to was:
> It'll do great. As everyone in the industry knows, past performance is always indicative of future results.
Assuming sarcasm, you are saying:
"It may not do great, because past performance is not always indicative of future results."
This is an adage to warn the everyday person that, say, while MSFT has produced great returns in the last 10 years, it does not guarantee it will carry on producing the same returns.
Which is fine.
But a sophisticated operation running machine learning on large live datasets to predict stock market movements doesn't need this adage. And in addition, it is possible for them to beat the market if they can make predications and connections that no one else is making.
Understand that is not "they can't lose any bet". It is more "they will make money over all bets on average that gives a higher return than the market".
Open question as to whether the generative model can do this by turning on a switch, or whether it is tuned and modified by experts to understand something about current affairs.