Because of the opaque nature of the inputs - and the leverage behind it.

Nobody knows what demand is going to be for AI in a few years, and that's causing this wild volatility.

It doesn't matter how well you understand the supply chain - that helps.

In many cases, it's literally trying to predict a herd: if the herd steers away from AI based on bad news about it not creating ROI, if the media sours, CEO's pullback, that could cause a slowdown in growth and therefore a crash.

Everything is highly leveraged.

An opaque input on Verizon forecasting model would not result in such a wild variation, they have more predictable operations.

I'm not so much surprised about the volatility as I am about all fund houses arriving at the same variation. I would've expected different models to arrive at different predictions and thus smooth out potential big jumps. So I'm finding it hard to understand how every model predicted 25% down instantaneously and simulatneously.

I don't know much about forecasting models and all, are you saying opaque forecasting is some kinda standardized technique and anybody doing opaque forecasting with the same data will likely end up with similar predictions?