Strategy · Event-Driven
TEMPERATURE RANGE SPREAD
NeutralDefined riskIntermediate
Overview
On Kalshi temperature contracts (high temp in major cities), buy a tight range bucket aligned with the GFS/ECMWF forecast and sell the adjacent ranges that the market over-prices.
Setup
- 1.Pull 7-day forecasts from at least 2 weather models.
- 2.Estimate the probability density of temperature outcomes.
- 3.Compare to bucket prices on the contract.
- 4.Buy the highest-edge bucket; consider selling adjacent buckets to fund it.
- 5.Cap basket cost at 2% of PM capital per event.
- 6.Exit 24h before resolution to avoid model-update risk.
Max profit
Bucket payout minus net cost; typical winning trades return 2-4x.
Max loss
Total basket cost minus credit from short legs.
Breakeven
Sum of probabilities your model assigns × payouts > basket cost.
When to use
When weather models converge and the market over-weights uncertainty.
When to avoid
When forecasts disagree sharply. On contracts that resolve more than 10 days out.