POLYMARKET FEED

AI Bubble Prediction Market Simulator

Implied Probability 14.0%
Liquidity (b) $1,000
Portfolio Value $0.00
Order Placement & Controls
Macro Trigger Scenarios
LMSR Mechanics: Logarithmic Market Scoring Rule maintains liquidity by adjusting price according to: P(YES) = e^(q_yes/b) / (e^(q_yes/b) + e^(q_no/b)).
LMSR Market Depth & Pricing Mechanics
Status: Active Baseline
Simulated Order Book Depth (Bids / Asks Spectrum) Spread: $0.01
LMSR Price Impact Curve (Order Size vs Price Slip) Slippage Sensitivity
Portfolio Yield Matrix & Trade Log

Active Positions

Outcome Shares Avg Price Total Cost Payout if Win

Scenario Payout Analysis

Event Outcome Current Value Net Profit / Loss Return on Capital

A local scoring-rule market prices trades without real betting

Read the explanation

The saved simulator starts with assigned event probability fourteen percent and liquidity one thousand. One hundred YES shares at the initial marginal price fourteen cents would naively cost fourteen dollars. The logarithmic scoring cost function integrates changing price over the purchase, giving about fourteen dollars sixty two cents. At twenty pixels per dollar naive cost fourteen measures two hundred eighty, integrated rounded fourteen point six two two hundred ninety two point four and rounded difference point six two twelve point four. Buying shares changes only local quantity state. The event name and preset probabilities are saved examples, not live prediction market quotes or verified financial forecasts. No money, account, external order or real wager is involved. At liquidity one thousand, buying one hundred YES shares changes assigned probability from fourteen percent to about fifteen point two five. At liquidity two thousand with the same starting probability and order size, the ending value is about fourteen point six one. At fifteen pixels per rounded percentage point starting fourteen measures two hundred ten, lower liquidity ending fifteen point two five two hundred twenty eight point seven five and higher liquidity ending fourteen point six one two hundred nineteen point one five. Increasing liquidity flattens price movement for this local formula. It does not add actual collateral or market participants. Native listeners and JSON exports are registered before missing D3 drawing, so local trades can still update quantities and tables while chart errors remain. After changing liquidity to two thousand, reset sets the slider back to one thousand and recreates quantities using one thousand, but never resets stored liquidity. Export therefore still reports two thousand. At point one five pixels per liquidity unit intended one thousand measures one hundred fifty, retained two thousand three hundred and difference one thousand one hundred fifty. Reset clears positions and history, but displayed starting probability and quantities now disagree with stored liquidity until further updates. Scenario selection also replaces quantities while preserving existing positions. Preserve these original inconsistencies; do not turn a simulation profit table into a return forecast or call a local export a settled wager. The model describes saved source behavior only.

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