NSA stock price history
STOCKDelisted1, 5, 15, 30-minute, hourly & daily bars
| Symbol | NSA-DELISTED |
|---|---|
| History | 2015-04-24 to 2026-07-21 (about 11 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 | Delisted: kept in full, so backtests see the whole history |
| Free tier | Last 12 months of daily bars |
Price history at a glance
NSA last closed at $43.41 on 2026-07-21, +38.0% over the past year and -20.1% over five years. Its deepest fall from a prior high in this history was -60.2%, reached on 2025-12-23.
| Last close | $43.41 (2026-07-21) |
|---|---|
| 1-year change | +38.0% |
| 5-year change | -20.1% |
| Annualized since 2015-04-24 | +11.2% |
| 52-week range | $27.53 – $46.04 |
| Deepest drawdown | -60.2% (2025-12-23) |
| Avg. daily dollar volume (3 months) | $58.9m |
| Daily bars in history | 2,826 |
Split- and dividend-adjusted closes. Computed by FinzData from its own daily bars.
Institutional ownership (13F, 2026Q2)
| Managers holding | 335 |
|---|---|
| Shares held | 71,511,223 ($3.2bn reported value) |
| Quarter flows | 51 new, 128 added, 104 trimmed, 49 exited; +125,811 shares vs the prior quarter |
From SEC Form 13F filings. Every holder, line by line, and the full history since 2013: yf.Client().holders("NSA") on the look-back bundles. Top holders of NSA · All 13F managers
NSA FAQ
How far back does NSA price history go?
2015-04-24 to 2026-07-21
Is NSA still trading?
No. NSA was delisted; its last bar is 2026-07-21, and FinzData keeps the full history so backtests stay survivorship-free.
What was NSA's last close?
$43.41 on 2026-07-21, +38.0% over one year
How do I download NSA historical data in Python?
pip install finzdata, then yf.Ticker("NSA-DELISTED").history(start="2015-04-24")
Get it in Python
import finzdata as yf
df = yf.Ticker("NSA-DELISTED").history(start="2015-04-24", interval="1d")
m15 = yf.Ticker("NSA-DELISTED").history(period="5d", interval="15m") # also 1m, 5m, 30m, 1h
df.tail()