Largest Company historical data
Largest Company is a Polymarket economy series with markets recurring monthly. Marketlens has captured 82 markets since March 1, 2026, of which 29 resolved, with $10.7M in traded volume. Order books are stored at full depth, with every individual price change captured at millisecond resolution on the most actively traded markets, alongside trades, candles, and the final resolution outcome.
Data as of 2026-09-04 · series slug largest-company
Resolution outcomes
Outcomes across 29 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 82 markets.
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "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 Largest Company markets are in the archive?
82 markets from March 1, 2026 through August 31, 2026, of which 29 have resolved and 17 are active.
What data exists for each Largest Company market?
Full depth L2 order book snapshots at regular intervals, individual trades, OHLC candles, and the resolution outcome, with the full price change stream at millisecond resolution on the most actively traded markets in the series. All of it is queryable by the series slug "largest-company" through the API and Python SDK, or downloadable as Parquet.
How often do Largest Company markets resolve No?
Of 29 resolved markets with a recorded outcome, 28 resolved No (96.6%) and 1 resolved Yes.
How much does a typical Largest Company market trade?
Average traded volume is $130.3K per market, $10.7M across the series.
Can I backtest strategies on Largest Company?
Yes. Pass the slug "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, US Annual Inflation, Bank of Japan, ECB Interest Rates, Bank of England decision, Bank of Brazil decision, or all economy series.
Try it
Pull Largest Company books in one call
The free tier includes 25M rows per day with full API and full archive access, no card required.
$ pip install marketlens