Second Largest Company historical data
Second Largest Company is a Polymarket economy series with markets recurring monthly. Marketlens has captured 58 markets since July 16, 2026, of which 26 resolved, with $616.3K 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.
Data as of 2026-09-04 · series slug second-largest-company
Resolution outcomes
Outcomes across 26 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 58 markets.
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "second-largest-company",
after="2026-08-24", before="2026-09-01", initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many Second Largest Company markets are in the archive?
58 markets from July 16, 2026 through August 31, 2026, of which 26 have resolved and 9 are active.
What data exists for each Second Largest Company 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 "second-largest-company" through the API and Python SDK, or downloadable as Parquet.
How often do Second Largest Company markets resolve No?
Of 26 resolved markets with a recorded outcome, 25 resolved No (96.2%) and 1 resolved Yes.
How much does a typical Second Largest Company market trade?
Average traded volume is $10.6K per market, $616.3K across the series.
Can I backtest strategies on Second Largest Company?
Yes. Pass the slug "second-largest-company" to client.backtest() in the Python SDK. Execution mode replays order books against real historical depth; Alpha mode, one bar per market, covers every market in the series and suits its longer horizons.
Related series: FOMC, Largest Company, US Annual Inflation, Bank of Japan, ECB Interest Rates, Bank of England decision, or all economy series.
Try it
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$ pip install marketlens