The rise of prediction markets like Kalshi and Polymarket in 2025 signals a shift towards trading platforms that capitalise on human psychology and suspense, transforming uncertainty into a highly engaging financial phenomenon amid a backdrop of legislative progress and record trading volumes.
Looking back over 2025, prediction markets emerged as one of the year’s most conspicuous trading themes, drawing in retail speculation, venture capital and a growing share of market attention. The appeal was especially visible during the US election cycle, when contract prices on political outcomes became a live gauge of shifting sentiment. After a court ruling in October 2024 cleared the way for Kalshi to list election contracts for retail users, the sector moved from niche curiosity to mainstream talking point, with industry tracking later showing extraordinary growth at both Kalshi and Polymarket.
By early 2026, the two platforms had become the sector’s defining names. Analysis cited by Finance Magnates Intelligence put Kalshi at about $23.8 billion in annual volume for 2025, alongside a 1,108% year-on-year increase, while Polymarket generated roughly $21.5 billion. Separate reporting from Covers said both platforms had already posted record monthly activity in late 2025, each moving above $5 billion in November, while Kalshi briefly overtook its rival in October and September volumes as U.S. participation accelerated.
That commercial success has an obvious explanation: prediction markets turn uncertainty into a tradable product. But the more interesting story lies in why they are so sticky. The article points to B.F. Skinner and the logic of operant conditioning, arguing that repeated, small feedback loops can be more powerful than blunt reward-and-punishment systems. In trading terms, the constant recalibration of odds creates a rhythm of action and response that keeps users engaged.
Neuroscience helps explain why that rhythm is so effective. The anticipation of a possible win, rather than the win itself, is what tends to activate the brain’s reward circuitry most strongly, especially when outcomes remain uncertain. That makes prediction markets feel closer to gambling than conventional investing, even when they are framed as a tool for information discovery. The result is a business model built not just on forecasts, but on the human appetite for suspense.
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Source: Noah Wire Services
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The draft above was created using the information available at the time the story first
emerged. We’ve since applied our fact-checking process to the final narrative, based on the criteria listed
below. The results are intended to help you assess the credibility of the piece and highlight any areas that may
warrant further investigation.
Freshness check
Score:
8
Notes:
The article was published on April 29, 2026, making it current. However, the content references events up to March 2026, which may not fully capture the latest developments in prediction markets. Additionally, the article draws on a 2024 court ruling and 2025 trading volumes, which are now over a year old. The analysis of B.F. Skinner’s theories, while insightful, is not recent and may not reflect the latest research in the field.
Quotes check
Score:
7
Notes:
The article includes direct quotes from B.F. Skinner, an American psychologist. While these quotes are accurate, they are historical and not recent. The article does not provide direct quotes from contemporary sources, which limits the ability to verify the information through current, independent sources.
Source reliability
Score:
6
Notes:
The article is published on Finance Magnates, a reputable financial news outlet. However, the article relies heavily on data from TradeTheOutcome.com, a niche website that may not be widely recognized. Additionally, the article references Covers.com and Webopedia, which are not primary sources and may not provide independent verification. The heavy reliance on secondary sources raises concerns about the independence and reliability of the information presented.
Plausibility check
Score:
7
Notes:
The article presents plausible claims about the growth of prediction markets and their psychological underpinnings. However, the reliance on secondary sources and the lack of direct quotes from primary sources make it difficult to fully verify the accuracy of these claims. The article also discusses B.F. Skinner’s theories, which, while foundational, may not fully account for contemporary developments in the field.
Overall assessment
Verdict (FAIL, OPEN, PASS): FAIL
Confidence (LOW, MEDIUM, HIGH): MEDIUM
Summary:
The article presents plausible claims about the growth of prediction markets and their psychological underpinnings. However, the heavy reliance on secondary sources, the lack of direct quotes from primary sources, and the use of outdated data raise significant concerns about the accuracy and reliability of the information presented. The article’s blend of reporting and opinion further complicates the assessment of its objectivity.
