Rational Inattention
In prediction markets, participants face a constant flow of news, data, and price changes. Rational inattention occurs when traders deliberately limit what they pay attention to, even if more information is available.
Instead of tracking every update, participants focus on high-impact signals such as major news, large trades, or clear price trends. This behavior is not careless; it reflects a trade-off between information value and effort.
Rational inattention can lead to delayed reactions. Prices may not fully adjust until enough participants decide the information is worth processing. This behavior is more common in complex or low-liquidity markets. When information is hard to interpret or the potential payoff is small, many traders simply wait.
For analysts, rational inattention helps explain why some prediction markets update slowly despite new information. It highlights the limits of attention as a factor shaping prediction markets data.
Why It Matters
Rational inattention affects how quickly and accurately markets react to information. Understanding it helps users interpret slow or uneven probability updates more realistically.
What is rational inattention in prediction markets?
In prediction markets, rational inattention means traders selectively ignore some information. They do this because analyzing every signal is costly or inefficient. Markets may react only after information becomes obvious or widely discussed. This behavior shapes price adjustment speed.
How does rational inattention affect prediction markets data?
Rational inattention can create flat periods or delayed probability shifts in prediction markets data. Prices may remain stable even when new information exists. Once attention increases, adjustments can happen quickly. Analysts must account for this lag when evaluating market responsiveness.
Why is rational inattention important when using prediction markets APIs?
Prediction markets APIs provide detailed data that may update faster than participant attention. Analysts need to distinguish between data availability and actual market reaction. Rational inattention explains gaps between events and price movement. APIs help measure these attention-driven delays at scale.
Real-World Example
On Polymarket, a technical policy update may initially receive little trading activity. As media coverage grows, traders pay attention and probabilities adjust, reflecting earlier rational inattention.
Rational Inattention and FinFeedAPI
FinFeedAPI’s Prediction Markets API provides time-stamped prediction markets data useful for studying rational inattention. Analysts can compare external event timing with delayed probability updates and volume changes. This supports attention modeling, responsiveness analysis, and signal timing research. The API enables systematic analysis of attention effects across prediction markets.