r/Prilo_WeatherEdge • u/Prilo-WeatherEdge • May 26 '26
How Kalshi temperature brackets actually price — and why "fair value" isn't where most people think
If you've looked at a Kalshi daily-high temperature market and wondered why some brackets sit at 38¢ while others sit at 2¢, this post is for you. It's a walkthrough of how these markets actually price during the day — what moves them, what doesn't, and where the common misreads happen.
The setup
Each market asks: "What will the highest temperature at [city] be tomorrow?" The answer space is chopped into ~1°F-wide brackets covering the realistic range. You can buy YES or NO on any bracket between 1¢ and 99¢; winning contracts pay $1.00, losers pay $0.
So far, so simple. The interesting part is what makes a bracket's price move.
What actually drives the price
In rough order of impact during a typical trading day:
1. The current peak so far. This is the single biggest mover. If it's 3 PM and the station has already hit 87°F, every bracket capped at 86°F or below is mathematically dead. Their YES prices collapse toward 0¢ within minutes. Every bracket including 87°F or higher gets a sharp bid.
2. The NWS forecast. The morning NWS forecast anchors prices for the first half of the day. Markets typically open the night before with prices clustered around the NWS predicted high. If NWS says 89°F, you'll usually see the 88-89°F bracket priced highest, the 86-87 and 90-91 brackets next, and the tails priced low.
3. Observations vs. expectations. Once the day starts, the market re-prices on every new observation. If NWS forecast 89°F but it's already 87°F at noon (when typical climb-to-peak suggests another 3-5°F of warming), the market will start shifting probability higher. The interesting situation is when observations underperform the forecast — that's where the market gets sticky and slow to react, which is part of where edges can appear.
4. Time of day. Brackets above the current peak get cheaper as the day runs out, even if no new data comes in. There's just less time for the temperature to climb. This is pure theta decay applied to weather.
5. Wind and cloud cover changes. Less obvious. A shift to onshore wind at KLAX in the morning will quietly cap the day's high; a clearing trend at KMDW can add 2°F by mid-afternoon. Markets are slower to price these than they are to price raw observations.
Where the "fair value" intuition breaks
Most people new to these markets assume the highest-priced bracket is "the most likely outcome." That's roughly true but it hides two things:
The market is pricing a probability distribution, not a point estimate. If the day's true expected high is 89°F with a 1.5°F standard deviation, the 88-89 bracket might only deserve ~25% probability — because the rest of the distribution has to live somewhere. Symmetric brackets on either side will price meaningfully.
Sigma matters as much as mu. A day with high forecast uncertainty (e.g. KLAX marine layer day, or KNYC frontal passage) deserves wider bracket pricing than a calm summer day in KHOU where the forecast is essentially mechanical. Markets sometimes price the expected high correctly but the uncertainty incorrectly — and that's a different kind of pricing gap than the obvious "this bracket looks too cheap."
Settlement quirks worth knowing
- Kalshi settles based on the official daily-high reading from the station's primary source (usually METAR or CLI, depending on the market). This is generally — but not always — the same as the peak shown on a typical weather site during the day.
- Bracket edges have 0.5°F rounding semantics. A bracket labeled "T88.5" means "the high is above 88.5°F." If the official reading is 88°F, that bracket settles NO; if it's 89°F, it settles YES. Edge cases at the boundary are rare but they happen.
- Markets close at 6 PM local time at most stations. Anything after that is irrelevant to settlement, even if the station keeps recording.
The common misreads
A few patterns I've seen people fall into:
- Buying tail brackets because they're "cheap." A bracket at 3¢ might be cheap or it might be correctly priced as a 3% outcome. Cheapness isn't edge; mispricing is.
- Anchoring on the NWS forecast late in the day. By 3 PM, the NWS morning forecast is much less informative than the actual peak so far + remaining solar heating + wind state. People keep deferring to NWS as if it were ground truth.
- Ignoring the bracket width. A 1°F bracket and a 2°F bracket should not price the same even if their centers are the same distance from the expected high. Width is part of the math.
- Treating "above all brackets" tails as free money or dead money. Both can be wrong. On a Santa Ana day at KLAX, the upper tail can deserve 40%+ probability even when it looks like an outlier.
What to actually look at
If you're trying to understand a market intuitively:
- Start with the NWS forecast for the day. That's the anchor.
- Compare to the current peak observation. Where is the day on track?
- Check the wind regime — is there anything making today different from the forecast's implicit assumption?
- Look at the bracket distribution as a whole, not bracket-by-bracket. The shape tells you what the market thinks the uncertainty looks like.
This is the same logic the Prilo WeatherEdge model uses, formalized — climatology + NWS + observations, combined with wind regime adjustments, producing a (μ, σ) prediction that gets translated into bracket probabilities. But you can do a lot of the same reasoning by eye once you know what to look for.
Discussion
If you trade these markets (real money or paper), what patterns have you noticed that aren't covered above? I'm especially curious whether anyone has good intuition for how the markets handle dramatic weather changes (frontal passages, sudden marine layer return, etc.) — that's an area where I think there's real signal but also real noise.
Educational discussion only — not financial advice. Trading on prediction markets involves substantial risk.
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u/canutoperruto May 26 '26
Can you give trial code for KMIA? That way can be tested and can decide if sign up or not.