Will Groupon (GRPN) beat quarterly earningsPolymarket historical data and price history
Will Groupon (GRPN) beat quarterly earnings: a Polymarket equities series with markets recurring monthly. Marketlens has captured 2 markets since March 10, 2026, of which 2 resolved, with $13.2K in traded volume. Every market's order book is stored in full: periodic L2 snapshots plus every individual price change with a millisecond timestamp, alongside trades, candles, and the final resolution outcome.
For the equities archive as a whole, see Polymarket price history.
Data as of 2026-09-17 · Polymarket series GRPN Earnings · slug grpn-earnings
Markets in this series
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "grpn-earnings",
after="2026-07-29", before="2026-08-06", initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many Will Groupon (GRPN) beat quarterly earnings markets are in the archive?
2 markets from March 10, 2026 through August 5, 2026, of which 2 have resolved.
What data exists for each Will Groupon (GRPN) beat quarterly earnings market?
Full L2 order book history (snapshots plus every price change at millisecond resolution), individual trades, OHLC candles, and the resolution outcome. All of it is queryable by the series slug "grpn-earnings" through the API and Python SDK, or downloadable as Parquet.
How much does a typical Will Groupon (GRPN) beat quarterly earnings market trade?
Average traded volume is $6.6K per market, $13.2K across the series.
Can I backtest strategies on Will Groupon (GRPN) beat quarterly earnings?
Yes. Pass the slug "grpn-earnings" to client.backtest() in the Python SDK. Execution mode replays every market's order book tick by tick and fills simulated orders against real historical depth with queue priority, latency, and fee modelling; Alpha mode replays one bar per market for slower signals over long windows.
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Try it
Replay Will Groupon (GRPN) beat quarterly earnings tick by tick
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$ pip install marketlens