Kalshi economics favourites show a gap between prices and outcomes
No new platform headline in the last 30 minutes changes the picture — news search recirculated only items already carried or held out today (the Alaska and Mississippi…
Outcomes trail implied probabilities
Kalshi economics markets priced at 75c or higher resolved YES less frequently than their prices implied. Across 148 settled markets, the YES settlement rate was 82.4%, compared with an implied probability of 85.6%.
Those figures come from the supplied headline accompanying a summary dated Nov 5, 2026, at 1:54 PM ET. No source links or underlying market-level data were provided, limiting independent assessment of the comparison.
A historical gap, with limited context
The result describes an aggregate shortfall for favourites in this sample—not evidence that every market was overpriced. The supplied material does not specify the observation period, when prices were measured or how the implied probability was calculated.
The accompanying summary says no new platform headline in the preceding 30 minutes changed the picture. It describes search results as recirculating items already covered or held out that day, but cuts off after references to Alaska and Mississippi, leaving those items unexplained.
What it means for prediction markets
- Calibration is the central issue: The sample’s 82.4% YES settlement rate fell below its 85.6% implied probability, indicating that observed outcomes did not fully match pricing.
- Scope matters: The comparison covers 148 settled Kalshi economics markets priced at 75c and above. It does not establish a pattern across other categories or price ranges.
- Methodology remains important: Without underlying data and price-measurement details, the supplied figures alone cannot establish whether the gap is statistically meaningful or likely to persist.
Sources & attribution
- Published
- Source
- Kalshikalshi.com
- Publisher
- https://kalshi.com/markets
- Source URL
- The feed did not publish this story's article address.
Full attribution under the Digital Millennium Copyright Act (DMCA), 17 U.S.C. § 512: this article is an original report by Infiniti Intelligence that summarizes the reporting of the publishers named above, links to their original work, and reproduces no protected expression beyond brief factual reference and in-line attribution (“according to Kalshi”). All rights in the underlying reporting remain with the publishers listed; nothing here implies endorsement by or affiliation with them. Rights holders may request correction, update or removal through the contact address published at infiniti.w3ai.io.
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