Will NYC have less than 2 inches of precipitation in May?

Polymarket traders currently assign a 13.0% probability to "Will NYC have less than 2 inches of precipitation in May?".

The market is pricing YES at 13.0¢ and NO at 84.0¢, reflecting current trader consensus.

Liquidity conditions are low, with approximately $113 in 24-hour trading activity.

Resolution Criteria

This market will resolve according to the total precipitation in inches in Central Park, New York City between May 1 and May 31, 2026, 11:59PM ET according to the National Oceanic and Atmospheric Administration (NOAA).

If the reported value falls exactly between two brackets, then this market will resolve to the higher range bracket.

The resolution source for this market will be NOAA, specifically the figure for May 2026 when the "Monthly summarized data" for "Central Park NY" is selected with the variable set to "Precipitation" at the https://www.weather.gov/wrh/climate?wfo=okx link once that figure is finalized for the whole month of May 2026.

The resolution source for this market measures precipitation to 2 decimal places (e.g., 1.54), thus, this is the level of precision that will be used when resolving this market. Any revisions to precipitation recorded after data is finalized for this market's timeframe will not be considered for this market's resolution.

Market Interpretation

Prediction markets function as real-time consensus engines.

Traders continuously buy and sell outcome shares based on:

• breaking news
• macro developments
• public narratives
• institutional positioning
• probability reassessments

As a result, market pricing reflects aggregate trader expectations rather than static forecasts or polling systems.

At the current pricing structure:

• YES trades near 13.0¢
• NO trades near 84.0¢
• Implied probability sits near 13.0%

These probabilities may shift rapidly as new information enters the market.

Liquidity & Conviction Analysis

As of May 13, 2026 at 04:29 PM, liquidity conditions act as a primary structural filter on prediction market signal quality.

Medium liquidity conviction suggests moderate participation depth, where price discovery is active but not fully saturated by institutional or high-frequency flow.

Higher liquidity environments typically produce:

• tighter spreads
• faster price discovery
• stronger informational efficiency
• lower pricing instability

Lower liquidity environments tend to exhibit:

• wider spreads
• delayed consensus formation
• increased volatility from isolated trades
• weaker signal reliability in short time windows

Overall, liquidity acts as a direct proxy for how “stable” the implied probability surface is at any given moment.

Why This Signal Exists in Prediction Markets

Prediction markets function as continuous consensus engines where probability is not stated — it is priced.

Each trade updates a live belief distribution, turning scattered human judgment into a single evolving likelihood curve.

Compared to static polling or narrative reporting, this structure adapts instantly to:

• regime shifts in geopolitics
• macroeconomic shocks and policy changes
• institutional order flow and positioning
• narrative acceleration or decay
• liquidity-driven sentiment swings
• information asymmetry correction

In practice, these markets behave less like betting tools and more like real-time probabilistic sensors for world events.

They compress collective intelligence into a dynamic signal that updates with every transaction.

Market Structure Transition

As of May 13, 2026 at 04:29 PM, prediction markets have evolved into persistent global probability infrastructure.

Polymarket and Kalshi now operate as high-throughput probability engines, with cumulative volumes exceeding $150B+ and sustained monthly flow above $7B.

Market activity has shifted from episodic speculation toward continuous liquidity formation, where geopolitical events, macroeconomic narratives, elections, AI milestones, and financial expectations are constantly repriced in real time.

This transformation has turned prediction markets into always-on consensus surfaces capable of reflecting crowd intelligence faster than traditional media, polling systems, or institutional forecasting pipelines.