Kalshi Weather Edge
kalshi_weather_edgePrices Kalshi daily high-temperature markets against the NWS forecast for the market's OWN settlement station, and measures whether that forecast actually beats the market. Two modes. LIVE (default): returns the full strike ladder for one city and settlement date with market_prob (mid), forecast_prob, and edge_pp per strike, plus the settlement clause verbatim. BACKTEST (backtest_days: N): scores an archived gridded forecast against the market on settled days and returns brier_market vs brier_forecast with a plain-English verdict, so the edge is MEASURED rather than asserted. READ THE WARNINGS — they are not boilerplate. (1) These markets DO NOT settle on the NWS. They settle on The Weather Company (weather.com) at a Kalshi station code such as CLINYC, which the response quotes verbatim; so part of every edge_pp is NWS-vs-Weather-Company disagreement about the same day at the same station, which is not mispricing and not tradeable. settlement_vs_forecast_basis_f from backtest mode is that part as a number. (2) The station is DERIVED from the settlement clause, never from the city name: Chicago settles at MIDWAY and New York at CENTRAL PARK, so a city-centre forecast would misprice a whole ladder. A station that cannot be resolved yields rows with no forecast and a reason, never a guessed coordinate. (3) forecast_prob assumes a normal distribution around the NWS high whose width is ASSUMED, not fitted (stated in distribution_assumption) — run backtest mode to see whether it is calibrated. (4) edge_pp is gross: no Kalshi fees, no bid-ask. MEASURED RESULT, AND IT IS NOT THE FLATTERING ONE: on the first backtest (KXHIGHNY, 13 settled days to 2026-09-11, 58 market observations) the MARKET beat the forecast — Brier 0.1008 for the market against 0.1594 for the archived gridded forecast, lower being better. So on that sample there is NO forecast edge to sell, and a large edge_pp is more likely to be the model disagreeing with a better-informed market than an opportunity. The measured settlement-vs-forecast basis was 1.7F mean absolute over 8 pinnable days, slightly warm-biased, which is a big share of a typical edge_pp on a 2-degree bracket. Re-run backtest_days before believing any edge; if a later sample reverses this, the numbers say so. NWS is US-only, so the ~30 international Kalshi weather series (London, Paris, Tokyo) return market prices with forecast_unavailable rather than a forecast. Precipitation series are listed but not yet priced. Cities: nyc, chicago, los angeles, miami, austin, houston, denver, philadelphia — or pass series_ticker for any other (e.g. "KXHIGHTBOS").
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | City to price, e.g. "nyc", "chicago", "los angeles", "miami", "austin", "houston", "denver", "philadelphia". Defaults to nyc. Unmapped cities return known_cities[] rather than a wrong series. | |
| date | No | Settlement date as YYYY-MM-DD. Defaults to the soonest open event. Daily weather markets open ~1-2 days ahead and close 05:00Z the next day. | |
| market_type | No | "high_temp" (default) | "precip". Precipitation markets return prices but no forecast_prob yet. | |
| backtest_days | No | Run measurement mode over the last N settled days (max 60) instead of pricing today. Returns brier_market vs brier_forecast, the settlement-vs-forecast basis, and per-day detail. Both sides are scored at 12:00Z on each event day — before the daily high and before resolution — because a settled market prices the known outcome at close. | |
| series_ticker | No | Explicit Kalshi series, e.g. "KXHIGHNY" or "KXHIGHTBOS" (Boston). Overrides `city`; use it for any of the 121 daily weather series not in the city list. |