S&P 500 (SPY) closes abovePolymarket historical data and price history
S&P 500 (SPY) closes above: a Polymarket equities series with markets recurring daily. Marketlens has captured 11 markets since October 6, 2026, of which 11 resolved, with $45.5K in traded volume. Every market's order book is captured as full depth L2 snapshots at regular intervals, alongside trades, candles, and the final resolution outcome.
For the equities archive as a whole, see Polymarket price history.
Data as of 2026-10-12 · Polymarket series SPY Daily Close U/O · slug spy-daily-close-uo
Resolution outcomes
Outcomes across 11 resolved markets with a recorded winning outcome. Settlement in the archive is by winning outcome, not by final traded price.
Markets in this series
The most recently resolved of 11 markets.
Backtest this series
from datetime import datetime, timedelta, timezone
from marketlens import MarketLens, Strategy
class MyStrategy(Strategy):
def on_market_start(self, ctx, market, book):
ctx.buy_yes(size=10)
client = MarketLens()
end = datetime(2026, 10, 7, tzinfo=timezone.utc)
result = client.backtest(
MyStrategy(), "spy-daily-close-uo",
after=end - timedelta(days=1), before=end, initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many S&P 500 (SPY) closes above markets are in the archive?
11 markets from October 6, 2026 through October 6, 2026, of which 11 have resolved.
What data exists for each S&P 500 (SPY) closes above market?
Full depth L2 order book snapshots at regular intervals, individual trades, OHLC candles, and the resolution outcome. All of it is queryable by the series slug "spy-daily-close-uo" through the API and Python SDK, or downloadable as Parquet.
How much does a typical S&P 500 (SPY) closes above market trade?
Average traded volume is $4.1K per market, $45.5K across the series.
Can I backtest strategies on S&P 500 (SPY) closes above?
Yes. Pass the slug "spy-daily-close-uo" to client.backtest() in the Python SDK. Execution mode replays order books against real historical depth; Alpha mode, one bar per market, covers every market in the series and suits its longer horizons.
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Try it
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$ pip install marketlens