White House # postsPolymarket historical data and price history
White House # posts: a Polymarket politics series with markets recurring daily. Marketlens has captured 29 markets since August 18, 2026, of which 29 resolved, with $278.1K 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 politics archive as a whole, see Polymarket election data.
Data as of 2026-10-05 · Polymarket series Whitehouse Daily Tweets · slug whitehouse-daily-tweets
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 29 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, 9, 12, tzinfo=timezone.utc)
result = client.backtest(
MyStrategy(), "whitehouse-daily-tweets",
after=end - timedelta(days=1), before=end, initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many White House # posts markets are in the archive?
29 markets from August 18, 2026 through September 11, 2026, of which 29 have resolved.
What data exists for each White House # posts 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 "whitehouse-daily-tweets" through the API and Python SDK, or downloadable as Parquet.
How often do White House # posts markets resolve No?
Of 29 resolved markets with a recorded outcome, 23 resolved No (79.3%) and 6 resolved Yes.
How much does a typical White House # posts market trade?
Average traded volume is $9.6K per market, $278.1K across the series.
Can I backtest strategies on White House # posts?
Yes. Pass the slug "whitehouse-daily-tweets" 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: Elon Musk # tweets, Will China invade Taiwan, Will the Iranian regime fall, Putin out as President of Russia, Trump out as President, Which party will win the House, or all politics series.
Try it
Pull White House # posts books in one call
The free tier includes 2M data rows and every market open in the last 7 days, no card required.
$ pip install marketlens