Highest temperature in TokyoPolymarket historical data and price history
Highest temperature in Tokyo: a Polymarket weather series with markets recurring daily. Marketlens has captured 756 markets since March 9, 2026, of which 734 resolved, with $1.2M 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 weather archive as a whole, see Polymarket weather market data.
Data as of 2026-09-17 · Polymarket series Tokyo Daily Weather · slug tokyo-daily-weather
Resolution outcomes
Outcomes across 734 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 756 markets.
Backtest this series
from marketlens import MarketLens
client = MarketLens()
result = client.backtest(
MyStrategy(), "tokyo-daily-weather",
after="2026-09-10", before="2026-09-18", initial_cash=1_000,
)
result.show() # inspect the run in the dashboardAvailable datasets
Common questions
How many Highest temperature in Tokyo markets are in the archive?
756 markets from March 9, 2026 through September 17, 2026, of which 734 have resolved and 22 are active.
What data exists for each Highest temperature in Tokyo 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 "tokyo-daily-weather" through the API and Python SDK, or downloadable as Parquet.
How often do Highest temperature in Tokyo markets resolve No?
Of 734 resolved markets with a recorded outcome, 668 resolved No (91.0%) and 66 resolved Yes.
How much does a typical Highest temperature in Tokyo market trade?
Average traded volume is $2.7K per market, $1.2M across the series.
Can I backtest strategies on Highest temperature in Tokyo?
Yes. Pass the slug "tokyo-daily-weather" 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.
Related series: Highest temperature in Hong Kong, Highest temperature in London, Highest temperature in Seoul (Incheon), Highest temperature in Shanghai, Highest temperature in NYC, Highest temperature in Paris, or all weather series.
Try it
Replay Highest temperature in Tokyo tick by tick
The free tier includes 1M rows per day with full API and full archive access, no card required.
$ pip install marketlens