ILL-a-quid is an automated, prediction-market-native research system studying how short-dated markets form, break, repair, and converge as settlement approaches — and how regime “weather” changes the reliability of those shapes.
ILL-a-quid is reading the latest terminal advisory snapshot.
Short-dated contracts do not simply drift toward settlement. Their topology changes: liquidity disappears and returns, local structures form, wounds repair or fail, and the same apparent geometry behaves differently under different market weather.
ILL-a-quid treats those changes as measurable market structure. The system observes terminal price paths, repair behavior, entry-cell geometry, family breadth, and regime conditions, then tests whether repeatable forms carry useful information about convergence.
The objective is not to become better at telling stories about outcomes. It is to understand when convergence is trustworthy, how much capital the geometry can support, and how deterministic systems can respond without confusing confidence with certainty.
Which shapes recur as a short-dated contract enters terminal settlement?
Does the same geometry behave differently in broad, repairing, selective, or fragile environments?
Can deterministic systems convert the evidence into selective entry and dynamic capital without overfitting the weather?
Binary settlement creates an unusually clean environment for studying terminal convergence. ILL-a-quid currently operates natively in 15-minute prediction markets, measuring geometry, regime conditions, local entry structure, repair, and capital behavior.
The larger research question is whether the framework survives outside prediction markets: 0DTE options, short-dated futures options, and expiring futures all impose a clock that transforms payoff geometry as expiration approaches.
The project publishes enough context for a first-time visitor — or an AI research agent — to understand the experimental frame without mistaking the site for an event-tip service.
An independent automated research project studying terminal-market intelligence: the geometry and microstructure of short-dated prediction markets as they approach settlement.
A regime classification describing the structural environment around terminal contracts. It asks whether convergence geometry is broad, repairing, selective, fragile, or unresolved. It is not a prediction of the underlying event outcome.
They compress the entire lifecycle of uncertainty into a short, observable window. That makes them a useful laboratory for studying convergence, repair, liquidity, and the interaction between geometry and regime.
That is a central question. The closest analogues are 0DTE options, short-dated futures options, and expiring futures, where the clock also forces deterministic payoff transformation.
If you work in prediction markets, derivatives, market microstructure, systematic trading, capital allocation, or adjacent research, I’d be glad to hear what you are seeing — and compare approaches.