TIPD stock price history
STOCKListed1, 5, 15, 30-minute, hourly & daily bars
| Symbol | TIPD |
|---|---|
| History | 2025-08-22 to 2026-10-27 (about 1 years) |
| Bar sizes | 1-minute, 5-minute, 15-minute, 30-minute, hourly and daily |
| Adjustments | Unadjusted, split-adjusted or split-and-dividend-adjusted, chosen on read |
| Survivorship | Included in the survivorship-free universe |
| Free tier | Last 12 months of daily bars |
Price history at a glance
TIPD last closed at $93.80 on 2026-10-27, -9.4% over the past year. Its deepest fall from a prior high in this history was -12.9%, reached on 2026-10-06.
| Last close | $93.80 (2026-10-27) |
|---|---|
| 1-year change | -9.4% |
| Annualized since 2025-08-22 | -6.3% |
| 52-week range | $90.16 – $103.23 |
| Deepest drawdown | -12.9% (2026-10-06) |
| Avg. daily dollar volume (3 months) | $158,408 |
| Daily bars in history | 66 |
Split- and dividend-adjusted closes. Computed by FinzData from its own daily bars.
Institutional ownership (13F, 2026Q2)
| Managers holding | 2 |
|---|---|
| Shares held | 12,067 ($1.2m reported value) |
| Quarter flows | 0 new, 0 added, 2 trimmed, 0 exited; -23,229 shares vs the prior quarter |
From SEC Form 13F filings. Every holder, line by line, and the full history since 2013: yf.Client().holders("TIPD") on the look-back bundles. Top holders of TIPD · All 13F managers
Short interest (2026-10-15)
| Shares short | 3,333 (+796.0% vs prior report) |
|---|---|
| Days to cover | 7.15 |
TIPD short interest history · Unclassified (ETFs, funds, other) sector
TIPD FAQ
How far back does TIPD price history go?
2025-08-22 to 2026-10-27
Is TIPD still trading?
Yes. TIPD is listed and updated every trading day.
What was TIPD's last close?
$93.80 on 2026-10-27, -9.4% over one year
How do I download TIPD historical data in Python?
pip install finzdata, then yf.Ticker("TIPD").history(start="2025-08-22")
Get it in Python
import finzdata as yf
df = yf.Ticker("TIPD").history(start="2025-08-22", interval="1d")
m15 = yf.Ticker("TIPD").history(period="5d", interval="15m") # also 1m, 5m, 30m, 1h
df.tail()