Compare Tech Layoffs Up or Down in 2026? prediction market odds side by side across Kalshi, Polymarket. Platforms show similar odds, with an average spread of just 0.0pp. Close agreement often signals strong market consensus. With $19.3K in combined trading volume across 2 outcomes, this is one of the notable cross-platform prediction markets.
Descriptions normalized for comparison (outcome names replaced with [OUTCOME])
If there are more than 494,000 layoffs in the information sector in 2026, then the market resolves to Yes.
Important information: This market was listed using an incorrect underlying value for tech layoffs in 2025. The correct floor strike is 447,000 layoffs, not 494,000 as currently specified. If the final layoff count falls between those two numbers, we will pay out $1.00 to all traders with an open position as of March 13, 2026 at 5:00 PM ET. The rulebook variable has been updated accordingly. Trades executed after this time are not eligible for reimbursement.
This market will resolve to "Up" if, according to Federal Reserve Economic Data (FRED), there are more layoffs in the information sector in 2026 than in 2025 (447,000 layoffs). This market will resolve to "Down" if there are more layoffs in the information sector in 2025 than in 2026. This market will resolve to 50-50 if the totals are the same in 2025 and 2026. If not all relevant data points are published by June 30, 2027, ET, data published up until this point will be used to determine the 2026 total. Revisions to previous data points after all relevant data points have been released will not be considered. This market's resolution source will be the Federal Reserve Economic Data (FRED), specifically the monthly 'Layoffs and Discharges: Information' within the Job Openings and Labor Turnover (Not Seasonally Adjusted) (https://fred.stlouisfed.org/series/JTU5100LDL). Changes in the methodology by which the Bureau of Labor Statistics reports data will have no bearing on the resolution of this market. The resolution source reports the values as whole numbers (thousands of persons). Thus, this is the level of precision that will be used when resolving the market.
Different platforms may use different resolution criteria, data sources, and settlement timelines.
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