Simulate the entire market
Don't predict the outcome. Predict how the market will move.
Other tools ask the wrong question
Traditional prediction tools ask "Will this happen?" and try to guess the binary outcome. That's a coin flip with extra steps.
YorN's Crowd Simulation asks "How will traders reprice this contract?" — and simulates the answer by modeling how real market participants behave when catalysts hit.
The result isn't a guess. It's a simulated price trajectory that reveals where the market is heading before it gets there. When the crowd's consensus diverges from the current price, that's your edge.
Binary answer. 50/50 guess. No edge.
Simulated price movement. Actionable signal. Real edge.
A market in a bottle
Crowd Simulation spawns up to 10,000 virtual market participants — each with unique behavioral DNA: how much they herd, how they react to events, whether they fade the crowd or amplify it. Choose from three robustness tiers: Scout (fast, 1 run), Analyst (balanced, 3 ensemble runs), or Strategist (thorough, 5 ensemble runs with 8 steps/hour).
These participants are connected via a Watts-Strogatz small-world graph — the same topology that models real social networks — and then run forward through simulated time as they influence each other's beliefs.
The simulation is entirely rule-based. No LLM calls per participant. One single LLM call at the end interprets the crowd's emergent consensus into an actionable signal.
- Up to 10,000 participants with 7 behavioral archetypes
- 1–24 hour simulation horizon, configurable
- Event seeds from real catalysts (FOMC, CPI, sports)
- Deterministic with seed — reproducible results
Four steps. Under one second.
The entire simulation runs in milliseconds. The LLM interpretation adds ~300ms.
Spawn Crowd
Allocate up to 10,000 participants across 7 behavioral archetypes with configurable population weights. Three robustness tiers control simulation depth: Scout (1 ensemble, 2 steps/hr), Analyst (3 ensembles, 4 steps/hr), Strategist (5 ensembles, 8 steps/hr).
Build Graph
Connect via Watts-Strogatz small-world topology — local clusters with random long-range links
Run Forward
Simulate 1–24 hours: herding, contrarian fading, event reactions, mean reversion, noise
Interpret
One LLM call reads the crowd's final consensus vs. current price and outputs a directional signal
Three levels of simulation depth
Trade off speed vs. confidence. Scout runs in milliseconds; Strategist runs multiple independent ensembles and averages results to minimize noise.
| Tier | Ensemble Runs | Steps / Hour | Participants | Best For |
|---|---|---|---|---|
| Scout | 1 | 2 | 10 – 1,000 | Quick directional check, live scanning |
| Analyst | 3 | 4 | 100 – 5,000 | Pre-trade analysis, signal confirmation |
| Strategist | 5 | 8 | 1,000 – 10,000 | High-conviction research, strategy validation |
Every market has these players
Each archetype has unique behavioral coefficients that determine how they react to neighbors, events, momentum, and noise. Together they reproduce the dynamics of a real prediction market.
150x cheaper than deliberation
Rule-based simulation means almost zero LLM cost. One Haiku call at the end does the interpretation.
3–5 LLM calls per agent
Multi-round debate
1 LLM call per agent
Weighted voting
0 LLM calls during sim
1 Haiku call to interpret
Two sliders. Zero complexity.
No agents to configure. No prompts to write. Just set the number of participants and simulation horizon, and the crowd does the rest.
- Participants: 20–100 (slider, step 10)
- Time Horizon: 1–24 hours
- No agent_ids required — the crowd IS the team
- Works with event calendar for automatic catalyst injection
"mode": "crowd_sim",
"crowd_sim_participants": 50,
"crowd_sim_hours": 6,
"agent_ids": [],
"name": "Election Crowd"
}
"signal": "buy",
"side": "yes",
"probability": 0.62,
"confidence": 0.78,
"ci": [0.55, 0.69],
"herding_index": 0.73,
"participants": 50,
"cost": "$0.003"
}
Simulate Your First Crowd
Two sliders. Under a second. 150x cheaper. No agents required.