Imagine a party.
The venue is great. The food is great. The music is great. The only problem is that there are only three people in the room, and they're standing in a corner making small talk.
“Once word gets around and people start coming,” you think, “this is going to be a really great party.”
So you approach the host.
“I'll give you $1 now if you'll give me $1.50 when the party fills up.”
The host laughs. “Sure. Nobody's here, and I don't really know if anyone is actually going to come.”
In due course, as you suspected, word gets around and people start arriving at the party. And as participation rises, the party becomes much better. Conversation flows. The caterers can do their jobs. The cash bar starts ringing. The party has become far more valuable to everyone involved, including the host.
At that point, you collect your $1.50 from the host, say your goodbyes, and head home before the party ends. You never needed to know how the evening would end. You only needed to know that the value of the party was likely to increase once participation increased.
This is ILL-a-quid's core thesis.
It's a prediction-market-native trading system that identifies new markets with odd shapes that can be improved by participation. We enter these thin, inefficient markets early using capacity-aware positions and then exit as liquidity increases, prices become more efficient, and market structure improves.