Five Prediction Markets, Five Definitions of Price: The Normalization Problem Nobody Talks About
Kalshi, Polymarket, and other prediction markets expose similar-looking prices that can represent different quotes, fees, contracts, and timestamps.
Five different prediction market platforms define the price of an event differently, causing inconsistencies when comparing prices across platforms. This "normalization problem" is often overlooked, leading to inaccurate comparisons and potentially misguided decisions.
Polymarket calculates price as a midpoint between the best bid and ask, but switches to reporting the last trade price when the spread exceeds $0.10. Kalshi prices YES and NO independently, which may not sum to $1.00, requiring separate handling. Opinion's taker fee curve changes based on the probability of the event, making the displayed price a probability plus a variable fee.
Finally, markets on Limitless and Predict.Fun can settle on different blockchains with varying block times, causing timestamp inconsistencies when comparing prices across platforms.
To avoid errors, developers should implement a normalization function that converts raw prices to a consistent probability scale, accounting for each platform's unique pricing structure and fee schedules. This critical step is often missed, leading to misleading comparisons and potential misinformed decisions based on faulty data.
Written by urgent.news from HackerNoon's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
