| Outcome | Probability | Yes Bid | Yes Ask | 24h Change | Volume | |
|---|---|---|---|---|---|---|
| 78° to 79° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 77° or below | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 80° to 81° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 84° to 85° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 86° or above | 0% | 0¢ | 0¢ | — | $0 | Trade → |
| 82° to 83° | 0% | 0¢ | 0¢ | — | $0 | Trade → |
This market asks which temperature will be the highest in Dallas on March 15, 2026. It matters for local stakeholders and traders who want to speculate on or hedge against daily weather extremes and their economic impacts.
Dallas in mid-March is a transitional period from winter to spring, so temperatures can swing rapidly depending on synoptic patterns. Long-term climate trends have increased the frequency of warm extremes, but short-term weather systems (cold fronts, ridges, Gulf moisture) drive day-to-day outcomes. This market translates those meteorological drivers into tradable outcomes.
Market odds reflect the aggregated beliefs of traders about which discrete temperature outcome will occur and update as forecasts and observations evolve; they are not guarantees of the realized temperature. Use them as a real-time summary of market confidence and information flow, and compare to independent meteorological forecasts and official observations.
The market is split into six mutually exclusive highest‑temperature outcomes specified on the event page; consult the market’s outcome list on KALSHI to see the exact temperature ranges or categories being traded.
Settlement is governed by the contract specifications on the KALSHI event page; those specs will name the official source and station (for example, an NWS station or airport observation) used to determine the daily maximum—check the market rules for the exact measurement protocol.
The closure time is set by KALSHI (the event currently shows 'Closes: TBD'); settlement typically occurs after the official daily maximum is available and any required quality checks are completed according to the platform’s settlement timeline—refer to the event page for final close and settlement timing.
Use historical March climatology to gauge typical variability and the range of plausible highs, but combine that context with current model forecasts, recent trends, and synoptic indicators (fronts, ridges, model ensemble spread) because a single seasonal average does not predict day‑to‑day extremes.
Potential causes include instrumentation failure at the designated official station, a change in the named observation source after trading opened, or data quality issues; KALSHI’s dispute and settlement rules describe how they handle such cases and whether a market is voided, paused, or settled using alternate verified data.