Ticker brief
VYM VANGUARD HIGH DVD YIELD ETF
last close
$161.50
1 day
-0.7%
14 days
+1.7%
mkt cap
·
signals 14d
6
authors 14d
4
crowd 14d
+0.3σ
Options inteloptions-surface reads · latest available day per source
| metric | reading | context |
|---|---|---|
| IV — ATM 30d | 12% | IV/HV 1.35× |
| Skew — 25Δ RR 30d | -0.026 | 25Δ call IV − put IV |
| OI alarm | quiet | last alarm 2026-06-25 (z=6.8) |
Sentiment — last 14 days
daily mean sentiment, 2026-10-08 → 2026-10-16 · now +0.60 (−1 bearish … +1 bullish)
Who spoke4
| author | grade | trader score | signals | mean sent |
|---|---|---|---|---|
| @toushi_tommy | C | -1.97 | 3 | +0.08 |
| @bugra_kurtoglu | C | -0.19 | 1 | +0.25 |
| @RealSimpleAriel | C | -3.19 | 1 | +0.45 |
| @Divy_strategist | C | -0.40 | 1 | +0.60 |
Recent signals6of 6 in 14d — receipts included
| date (PT) | author | sent | what they said | since then | receipt |
|---|---|---|---|---|---|
| 2026-10-16 | @Divy_strategist | +0.60 | Buying BTC, VYM and VIG with payday funds. — States current payday purchases of BTC, VYM and VIG. | +0.8% | tweet ↗ |
| 2026-10-15 | @toushi_tommy | +0.20 | Daily, weekly, monthly, and YTD US-market performance is reported with leading movers. | +1.0% | tweet ↗ |
| 2026-10-14 | @toushi_tommy | +0.00 | Market summary reports broad losses after hot CPI, with healthcare strength and semiconductor weakness. | +1.5% | tweet ↗ |
| 2026-10-12 | @RealSimpleAriel | +0.45 | Identifies renewed rotation toward dividend and consumer-staples names. | +1.4% | tweet ↗ |
| 2026-10-10 | @bugra_kurtoglu | +0.25 | Presents a watch list of US dividend ETFs organized by income and dividend-growth characteristics. | +1.7% | tweet ↗ |
| 2026-10-08 | @toushi_tommy | +0.05 | Provides daily, weekly, monthly and year-to-date US market and ETF performance statistics. | +2.1% | tweet ↗ |
“Since then” = price move from the close on the signal's date (PT) to the latest close — what happened after they said it, not a backtest. A — means no trading session has closed since the signal yet. Sentiment is our extracted per-tweet score, −1…+1.