Investment markets operate on relative gain, not absolute gain. E.g.: if you invest in a stock and it gains $5, this would be a great return for a $1 stock but a poor one for a $1000 stock, so the absolute gain doesn't mean anything on its own. A 5% return always means that you've gained 5% on your investment.

I think their point is that predicting that "the stock will go up by 1$" or "the stock will go down by 1$" is worse than "the stock will go up by 0.05%" and "the stock will go down by 0.05%" because of this little paradox:

50$ increase from 50$ is 100% increase 50$ decrease from 100$ is 50% decrease

e.g., if the model finds 50$ increase/decreases, that actually corresponds to very different wealth changes

Here you go:

https://financetrain.com/why-lognormal-distribution-is-used-...

Well, just at a minimum... There's the fact that the majority of large gains and losses exist over single-day frames. That is, guessing "right" or "wrong" on movement means little when one slip on the wrong day will decimate your returns.