Predict & Profit Blog

A ninety percent win rate means nothing if your position sizing is flawed.

Submitting a market order does not guarantee full execution.

Kalshi weather contracts settle based on specific NOAA ASOS station readings.

Statistical edge in Kalshi weather markets is found in the convergence of independent simulations.

A perfect backtest is usually the first sign something is wrong.

GFS runs four times a day.

Volume is a lagging indicator.

The Kalshi fee formula peaks at 50-cent contracts — exactly where most volume trades.

A 429 error while holding an open position is a real problem.

Most prediction market trading bots fail not because the signal is wrong but because of five implementation mistakes that destroy edge before any trade settles.

A practical Kalshi API Python tutorial for signed requests, RSA-PSS authentication, rate limits, pagination, positions, and trading-bot integration patterns.

CFTC regulation, binary contract structure, NOAA ASOS settlement, bid-ask spread, fees, and why weather is the best asset class for an automated trading bot.

I combined NOAA's 31-member GFS physics ensemble with the new 31-member AIGEFS AI ensemble to build a 62-member grand ensemble.