How high will US unemployment go in 2026?

According to the latest prediction market data for the query “How high will US unemployment go in 2026?”, traders have formed a strong consensus.

Currently, 5.0% is dominating the market with an overwhelming 18.1% chance of winning. 7.0% follows in second place at 7.3%, while 6.0% sits in third with 6%. The betting volume for this specific market has already reached $440.1K, reflecting intense industry interest.

To better assess where each potential outcome stands, the market can be segmented into three distinct trading tiers based on implied probability and contract pricing:

🥇 Tier 1: The Dominant Leader

• 5.0% (18.1%): Currently commanding the highest probability, 5.0% is heavily favored by the order book. Traders looking to back this outcome face a “Buy Yes” contract price of 18¢, signaling a high degree of market conviction. This contract alone has generated $117.7K in volume.

🥈 Tier 2: The Primary Challengers

• 7.0% (7.3%): Positioned as the most viable alternative, 7.0% maintains a 7.3% chance of resolving true. Its “Buy Yes” shares currently trade at 7¢.
• 6.0% (6%): Sitting in third place with a 6% probability, the market shows measured skepticism toward 6.0%, treating it as an outside wildcard unless momentum shifts.

🥉 Tier 3: The Long-Tail Options (Combining for ~68.7%)

Beyond the top three choices, a wide field of macro variables and long-shot outcomes are being tracked. While their individual probabilities hover low, they represent crucial hedges for speculative traders:

• Alternative Options: This includes 5.5% (5.4%), and 10.0% (1.4%).
• Speculative Volume: Despite low statistical likelihood, certain long-tail contracts like 5.5% are still attracting notable interest.

This market will resolve to “Yes” if any seasonally adjusted unemployment rate (total unemployed, as a percent of the civilian labor force, official unemployment rate denoted as U-3) reported by the Bureau of Labor Statistics in an “Employment Situation Report” for a reference month in 2026 is greater than or equal to the listed percentage. Otherwise, this market will resolve to “No”.

The relevant reports for this market are the Employment Situation Reports for January-December, 2026. This market may not resolve to “No” until the Employment Situation report for December 2026 is released. If no Employment Situation Report for December 2026 is released by January 31, 2027, 11:59 PM ET, however, this market will resolve at that time.

The resolution source for this market is the Monthly Employment Situation Report, published by the BLS every month at https://www.bls.gov/bls/news-release/empsit.htm, specifically the U-3 measure in Table A-15 for each month.

Note: the resolution source for this market reports unemployment to one decimal point. Thus, this is the level of precision that will be used when resolving the market.

While human consensus and speculative volume shape the broader prediction market, our quantitative algorithms offer a data-driven counter-perspective. By analyzing fundamental signals, underlying trends and historical distributions, our AI Valuation model calculates an independent “Fair Value” probability for each outcome.

Comparing this Fair Value against the current Trade Value uncovers major disparities — known as the Expected Value (EV) Gap. Contracts with a positive EV Gap represent statistically underpriced outcomes, whereas a negative EV Gap flags a potential market overreaction.

Top AI Alpha & Mispriced Arbitrage Opportunities

Based on the latest data model run, several key contracts stand out with significant deviations:

• The Best Value Play (Highest EV) Our model identifies 10.0% as the premium value opportunity on the board. While the market only assigns it a 1.4% trading probability, our AI’s Fair Value assessment sits at 50.6% — yielding an impressive +49.2% EV Gap.
• Under-the-Radar Dark Horses Other notable discrepancies include 7.0% (EV Gap: +45.1%) and 6.0% (EV Gap: +37.9%). These long-tail opportunities are heavily discounted by the live order books despite stronger statistical backing from our predictive model.