Liquidity Stress in Simulated Event Markets
A committed PMarket Arena liquidity script showing how a bad-news shock and depth withdrawal make price tracking fragile.
Question
What failure mode appears when an event-market price faces bad news while available depth is deliberately withdrawn?
Mechanism
Liquidity stress turns a news shock into a larger tracking problem through spread widening, inventory pressure, one-sided flow, and delayed correction.
Setup
- Run liquidity_shock_playbook.json for 160 ticks with 100,000 simulated agents.
- At tick 25, inject a bad-news shock; at tick 45, cut liquidity for 60 ticks.
- At tick 75, add 4% arbitrageurs and track price, truth, liquidity stress, error, and correction share.
Selected ticks from the committed PMarket Arena liquidity template. Stress bars rise after the liquidity drop and remain elevated during the dislocation window.
Source artifact
PMarket Arena template scenarios/templates/liquidity_shock_playbook.json, run through the Node calibration harness for 160 ticks.
160
Rows
0.767
Max stress
76.9%
High error
74 ticks
Dislocated
0.460
Correction
25 ticks
Recovery
Result
The template run retained 160 rows, reached max liquidity stress of 0.767, and spent 74 ticks in dislocation. Average arbitrage correction share rose to 0.460, but the final price still remained 0.188 away from truth.
Boundary
This browser-template run is mechanism evidence for the public arena. It is not venue evidence, an execution-quality estimate, or a substitute for the Python manuscript pipeline.
Real Market Context
U.S. event contracts list by self-certification: under 17 CFR Part 40, a designated contract market can file at least one business day before listing, with no obligation to seed depth. New event markets therefore open thin, which is exactly the regime where this run's failure mode appears — a bad-news shock arriving while available depth is withdrawn.
17 CFR Part 40→