@ProfKayaFinance ProfKayaFinance

Grade = how their written analysis reads (A best). Trader score = how their last-20 timestamped calls performed vs SPY. · Analyst brief as of 2026-06-22.

ProfKayaFinance is leaning into data-center energy constraints, AI infrastructure suppliers, and a recurring six-name long book led by AMZN, META, NET, RBRK, RKLB, and AXON. His distinctive read is that hyperscaler AI demand is shifting the bottleneck from pure compute toward power, cooling, optical interconnects, MLCCs, and select semiconductor suppliers. Late in the window, he added explicit small-cap longs in AMSC and ONDS while surfacing a newer optical-interconnect framework around hyperscaler demand.

The author is consistently concentrated on AI infrastructure bottlenecks, especially power, cooling, optical interconnects, and supplier constraints, while maintaining a recurring long portfolio in AMZN, META, NET, RBRK, RKLB, and AXON. Explicit adds appeared in AMSC and ONDS, and AVGO was disclosed as a long bought at $380 with a preferred lower entry. There is no clean flip, but META and broader hyperscaler capex commentary became more cautious even as related infrastructure suppliers stayed favored.

Grade is our human read-worthiness rating; trader score is a rolling 20-bet hit-rate/alpha composite — different things, often disagreeing. “Since then” is direction-unaware in the table; the summary line above adjusts for which way they leaned.