SWSSW stock price history

STOCKDelisted1, 5, 15, 30-minute, hourly & daily bars

SymbolSWSSW-DELISTED
History2021-09-23 to 2025-12-30 (about 4 years)
Bar sizes1-minute, 5-minute, 15-minute, 30-minute, hourly and daily
AdjustmentsUnadjusted, split-adjusted or split-and-dividend-adjusted, chosen on read
SurvivorshipDelisted: kept in full, so backtests see the whole history
Free tierLast 12 months of daily bars

Price history at a glance

SWSSW last closed at $0.00 on 2025-12-30, -50.0% over the past year. Its deepest fall from a prior high in this history was -100.0%, reached on 2025-05-07.

Last close$0.00 (2025-12-30)
1-year change-50.0%
Annualized since 2021-09-23-86.6%
52-week range$0.00 – $0.01
Deepest drawdown-100.0% (2025-05-07)
Avg. daily dollar volume (3 months)$0.77
Daily bars in history459

Split- and dividend-adjusted closes. Computed by FinzData from its own daily bars.

Institutional ownership (13F, 2026Q2)

Managers holding1
Shares held11,000 ($1 reported value)
Quarter flows0 new, 0 added, 0 trimmed, 0 exited; +0 shares vs the prior quarter

From SEC Form 13F filings. Every holder, line by line, and the full history since 2013: yf.Client().holders("SWSSW") on the look-back bundles. Top holders of SWSSW · All 13F managers

Short interest (2026-09-30)

Shares short90 (+0.0% vs prior report)
Days to cover999.99

SWSSW short interest history · Financial Services sector

SWSSW FAQ

How far back does SWSSW price history go?

2021-09-23 to 2025-12-30

Is SWSSW still trading?

No. SWSSW was delisted; its last bar is 2025-12-30, and FinzData keeps the full history so backtests stay survivorship-free.

What was SWSSW's last close?

$0.00 on 2025-12-30, -50.0% over one year

How do I download SWSSW historical data in Python?

pip install finzdata, then yf.Ticker("SWSSW-DELISTED").history(start="2021-09-23")

Get it in Python

import finzdata as yf
df = yf.Ticker("SWSSW-DELISTED").history(start="2021-09-23", interval="1d")
m15 = yf.Ticker("SWSSW-DELISTED").history(period="5d", interval="15m")  # also 1m, 5m, 30m, 1h
df.tail()

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