Author
@SergeyCYW SergeyCYW
grade Bx.com/SergeyCYW ↗
Long-form AI-infrastructure and SaaS analyst who maps bottleneck stacks against valuation
Writes detailed, multi-stock fundamental theses framing the
trader score
-1.17
hit rate
35%
mean α
-0.54%
signals 14d
112
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 20 scored bets: 35% hit rate, -0.54% mean alpha, trader score -1.17. Their last-14d mentions, direction-adjusted, have moved -5.7% since posting (mean over 106 mentions with price data).
Recent signals15receipts included
| date (PT) | ticker | author | sent | what they said | since then | receipt |
|---|---|---|---|---|---|---|
| 2026-10-16 | AAPL | @SergeyCYW | +0.15 | Compares Magnificent Seven fundamentals, finding AI-driven growth strong but capex and cash-flow risks elevated. | +1.2% | tweet ↗ |
| 2026-10-16 | MSFT | @SergeyCYW | +0.45 | Compares Magnificent Seven fundamentals, finding AI-driven growth strong but capex and cash-flow risks elevated. | -0.9% | tweet ↗ |
| 2026-10-16 | AMZN | @SergeyCYW | +0.30 | Compares Magnificent Seven fundamentals, finding AI-driven growth strong but capex and cash-flow risks elevated. | -0.8% | tweet ↗ |
| 2026-10-16 | GOOGL | @SergeyCYW | +0.40 | Compares Magnificent Seven fundamentals, finding AI-driven growth strong but capex and cash-flow risks elevated. | -6.0% | tweet ↗ |
| 2026-10-16 | META | @SergeyCYW | +0.25 | Compares Magnificent Seven fundamentals, finding AI-driven growth strong but capex and cash-flow risks elevated. | -9.4% | tweet ↗ |
| 2026-10-16 | NVDA | @SergeyCYW | +0.55 | Compares Magnificent Seven fundamentals, finding AI-driven growth strong but capex and cash-flow risks elevated. | -1.5% | tweet ↗ |
| 2026-10-16 | RBRK | @SergeyCYW | +0.65 | Bullish deep dive cites accelerating growth, profitability, AI security demand, moat and attractive valuation. | +14.5% | tweet ↗ |
| 2026-10-15 | CIFR | @SergeyCYW | -0.60 | Quantifies severe AI-stock drawdowns and cites financing, revenue and industry risks behind the decline. | -20.9% | tweet ↗ |
| 2026-10-15 | AAOI | @SergeyCYW | -0.55 | Quantifies severe AI-stock drawdowns and cites financing, revenue and industry risks behind the decline. | -19.4% | tweet ↗ |
| 2026-10-15 | WULF | @SergeyCYW | -0.55 | Quantifies severe AI-stock drawdowns and cites financing, revenue and industry risks behind the decline. | -10.3% | tweet ↗ |
| 2026-10-15 | APLD | @SergeyCYW | -0.55 | Quantifies severe AI-stock drawdowns and cites financing, revenue and industry risks behind the decline. | -10.5% | tweet ↗ |
| 2026-10-15 | POET | @SergeyCYW | -0.60 | Quantifies severe AI-stock drawdowns and cites financing, revenue and industry risks behind the decline. | -9.2% | tweet ↗ |
| 2026-10-15 | WYFI | @SergeyCYW | -0.60 | Quantifies severe AI-stock drawdowns and cites financing, revenue and industry risks behind the decline. | -23.3% | tweet ↗ |
| 2026-10-15 | TSM | @SergeyCYW | +0.50 | TSMC reported strong Q3 growth, guided Q4 revenue to $52.3B-$54.3B and raised FY growth guidance. | -0.9% | tweet ↗ |
| 2026-10-13 | AAPL | @SergeyCYW | +0.35 | Compares operating income per R&D dollar and concludes Nvidia is most efficient, followed by Microsoft and Apple. | +1.9% | 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.