This event group tracks whether the S&P 500 Index closes higher or lower on February 23, 2026 compared to the prior trading day (Polymarket) versus specific price level bands on that same date (Kalshi). Both markets reference the same underlying asset and settlement date but use fundamentally different resolution methodologies.
Polymarket and Kalshi employ incompatible resolution methodologies for the same underlying event. Polymarket measures directional movement relative to the prior trading day, while Kalshi uses absolute price level bands that appear to cover all possible outcomes.
Hero Tip:
These markets serve different purposes and cannot be treated as equivalent. Polymarket traders are betting on momentum (up vs down day). Kalshi's structure with 30 Yes conditions and no visible No conditions suggests a potential design issue—verify the complete ruleset and No resolution criteria before committing capital.
Critical Divergence Points:
Polymarket: Directional comparison framework. Resolves Up if Feb 23 close exceeds the most recent prior trading day close, Down if lower. Handles edge cases: 50-50 if equal, if no trade during regular session, or if either day has no official close (uses last valid on-exchange trade). Source: Wall Street Journal Historical Prices Close values.
Kalshi: Absolute price level framework. Resolves Yes if end-of-day SPX value falls within any of 30 predefined bands spanning 6500 to 7200+. All 30 conditions resolve to Yes; no explicit No resolution criteria provided in source data. Appears to create universal coverage.
Our PredictionHero Resolution Divergence Alerts (RDA) are there to help users identify potential differences across platforms. They do not replace or supersede the official rules and description of any prediction market. Users are solely responsible for reviewing and understanding the applicable rules and resolution criteria before placing any trade or bet. If you notice a potential inconsistency, discrepancy, or error in an alert, please report it to our team so we can review and improve the accuracy of our data.
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