SPYA stock price history
STOCKListed1, 5, 15, 30-minute, hourly & daily bars
| Symbol | SPYA |
|---|---|
| History | 2025-06-03 to 2026-10-13 (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
SPYA last closed at $31.04 on 2026-10-13, +12.9% over the past year. Its deepest fall from a prior high in this history was -9.5%, reached on 2026-03-30.
| Last close | $31.04 (2026-10-13) |
|---|---|
| 1-year change | +12.9% |
| Annualized since 2025-06-03 | +16.4% |
| 52-week range | $25.79 – $31.04 |
| Deepest drawdown | -9.5% (2026-03-30) |
| Avg. daily dollar volume (3 months) | $8,029 |
| Daily bars in history | 113 |
Split- and dividend-adjusted closes. Computed by FinzData from its own daily bars.
Institutional ownership (13F, 2026Q2)
| Managers holding | 1 |
|---|---|
| Shares held | 140 ($4,209 reported value) |
| Quarter flows | 0 new, 1 added, 0 trimmed, 0 exited; +94 shares vs the prior quarter |
From SEC Form 13F filings. Every holder, line by line, and the full history since 2013: yf.Client().holders("SPYA") on the look-back bundles. Top holders of SPYA · All 13F managers
Short interest (2026-10-15)
| Shares short | 35 (+0.0% vs prior report) |
|---|---|
| Days to cover | 1.00 |
SPYA short interest history · Unclassified (ETFs, funds, other) sector
SPYA FAQ
How far back does SPYA price history go?
2025-06-03 to 2026-10-13
Is SPYA still trading?
Yes. SPYA is listed and updated every trading day.
What was SPYA's last close?
$31.04 on 2026-10-13, +12.9% over one year
How do I download SPYA historical data in Python?
pip install finzdata, then yf.Ticker("SPYA").history(start="2025-06-03")
Get it in Python
import finzdata as yf
df = yf.Ticker("SPYA").history(start="2025-06-03", interval="1d")
m15 = yf.Ticker("SPYA").history(period="5d", interval="15m") # also 1m, 5m, 30m, 1h
df.tail()