/ weather_edge

Typical horizon: MULTI-DAY • Season 1 — all time

What it does

Compares National Weather Service forecasts against daily high/low temperature markets in every Kalshi city (24 as of issue #222), using each city's measured forecast error to price the brackets. Buys when the market disagrees with the forecast by a wide margin.

Key parameters

behavior-shaping settings only

count	1
min_edge	12

Record (fee-inclusive, this season)

W–L

33–178

Open

Positions

211

Realized

$-37.39

Marked

$-37.39

Fees

$6.47

Calibration

predicted vs realized win rate, by confidence bucket

bucket 2	77 signals	p̂ 0.16 → 0.01
bucket 3	76 signals	p̂ 0.24 → 0.09
bucket 4	15 signals	p̂ 0.37 → 0.07
bucket 5	4 signals	p̂ 0.5 → 0.0
bucket 7	3 signals	p̂ 0.63 → 0.33
bucket 8	29 signals	p̂ 0.75 → 0.38
bucket 9	13 signals	p̂ 0.83 → 0.46
bucket 10	11 signals	p̂ 0.96 → 0.18

Caveats: All results shown are simulated (paper) trading performance, not actual trading, unless explicitly labeled live. Fees and slippage are modeled (Kalshi's taker fee formula plus 1¢ slippage), which cannot fully reflect real market impact or liquidity constraints. Past performance, simulated or actual, is not indicative of future results. Parameters shown are the current configuration and change over time as the strategy is tuned. Nothing on this page is investment advice — see the full disclaimer.