This event group tracks whether the S&P 500 Index closes higher or lower on March 18, 2026 compared to the prior trading day (Polymarket) versus absolute price thresholds (Kalshi). The two platforms use fundamentally different resolution mechanics: Polymarket measures directional movement relative to the previous close, while Kalshi resolves based on fixed price levels.
Polymarket uses relative directional resolution (vs prior close), while Kalshi uses absolute price level thresholds. These represent two distinct event definitions that may produce conflicting outcomes depending on the March 18 closing price and prior trading day close.
Hero Tip:
Do not assume these markets are fungible. Polymarket Up/Down is a directional bet; Kalshi thresholds are absolute level bets. A market that moves up in absolute terms but down relative to the prior close will resolve differently on each platform. Cross-platform arbitrage is possible but requires careful threshold mapping.
Critical Divergence Points:
Polymarket: Resolves based on directional comparison: Up if March 18 close > prior trading day close; Down if < prior close; 50-50 if equal or no trade. Uses WSJ Historical Prices as official source. Handles shortened sessions and trading halts by using last valid on-exchange trade price.
Kalshi: Resolves based on 60 absolute price thresholds, each independently resolving Yes if end-of-day SPX > threshold value (e.g., above 6999.9999, above 7024.9999, etc.). No relative comparison; no directional logic. All thresholds use identical resolution criteria.
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.
Follow the signals, not the noise
Get insights on market conviction, notable shifts, and what the data is quietly signaling.