Market Transactions Real-time LMSR
| Actor / Event | Side | Shares | Implied P |
|---|
Your Active Exposure
| Position | Shares | Avg Price | Mark Value |
|---|---|---|---|
| AFFIRM | 0.0 | $0.00 | $0.00 |
| DISPUTE | 0.0 | $0.00 | $0.00 |
How Prediction Markets on the Past Function
Conventional prediction markets resolve upon an anticipated calendar deadline (e.g., election night, macroeconomic release, or sporting championship). By contrast, retrospective prediction markets like Verifact Markets price controversies where the event has already transpired in historical or scientific record, but epistemological certainty remains disputed.
In a retrospective market, traders act as distributed researchers. Buying shares signals private confidence in evidentiary weight. When a peer publishes new archival forensics, spectroscopic analysis, or provenance verification, the Bayesian prior updates instantly via trading pressure.
This simulator implements Robin Hanson’s Logarithmic Market Scoring Rule (LMSR) automated market maker, mathematically enforcing continuous liquidity, bounded maximum loss for market sponsors, and smooth price slippage proportional to market depth b.
Epistemic Settlement FAQ
What is an oracle for a past dispute?
Resolving disputed history requires specialized oracles: designated historiographical juries, pre-registered replication trials, or multi-university consensus thresholds (e.g., >85% peer agreement in designated journals).
How does the LMSR pricing equation work?
The cost function is C(q) = b · ln(e^(q_yes / b) + e^(q_no / b)). The instantaneous price for an affirmative outcome is P_yes = e^(q_yes / b) / (e^(q_yes / b) + e^(q_no / b)), guaranteeing that prices always sum exactly to $1.00.
Can this prevent historical misinformation?
By tying financial rewards to truth discovery and penalizing speculative bias upon oracle verification, retrospective prediction markets turn historical fact-checking from rhetorical debate into quantifiable capital allocation.