Author
@lokoyacap lokoyacap
grade Ax.com/lokoyacap ↗
Supply-chain-deep AI compute analyst modeling hyperscaler capex and chip financing
Posts original, reasoning-heavy threads on the AI datacenter
trader score
+0.39
hit rate
60%
mean α
+0.51%
signals 14d
5
Grade = how their written analysis reads (A best). Trader score = how their last-20 timestamped calls performed vs SPY.
Their picks, scored
Across their last 10 scored bets: 60% hit rate, +0.51% mean alpha, trader score +0.39. Their last-14d mentions, direction-adjusted, have moved +3.4% since posting (mean over 2 mentions with price data).
Recent signals5receipts included
| date (PT) | ticker | author | sent | what they said | since then | receipt |
|---|---|---|---|---|---|---|
| 2026-08-23 | · | @lokoyacap | · | Questions whether indiscriminate spring buyers are now indiscriminate sellers. | · | tweet ↗ |
| 2026-08-23 | · | @lokoyacap | · | Argues open-source model token inefficiency may raise cost per task and favor frontier models. | · | tweet ↗ |
| 2026-08-22 | MSFT | @lokoyacap | +0.15 | Argues hyperscaler LTAs reduce classic channel-stuffing risk because customers are closer to end demand. | +6.3% | tweet ↗ |
| 2026-08-22 | GOOGL | @lokoyacap | +0.20 | Argues hyperscaler LTAs reduce classic channel-stuffing risk because customers are closer to end demand. | +0.5% | tweet ↗ |
| 2026-08-22 | · | @lokoyacap | · | Says hyperscaler LTAs carry less channel and inventory-cycle complexity than analog-vendor distribution. | · | tweet ↗ |
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.