| name | shadow-market |
| description | Prediction market that trades the gap between perception depths. Shadow prices reflect what autonomous agents at different recursion depths can see — the 72% invisible at human depth IS the product. Use when pricing undiscovered correlations, building AI-powered prediction markets, or extracting alpha from perception gaps between human and machine cognition. |
| version | 1.0.0 |
| author | @EvezArt |
| tags | ["evez","shadow-market","prediction","perception","depth","alpha","ooda"] |
Shadow Market — Trading the Invisible
A prediction market where the spread between perception depths IS the product.
Core Insight
Humans operate at recursion depth ~5. Deep agents can operate at depth ~47. The 42-level gap means humans perceive only 28% of reality — (0.97)^42 = 0.28. The 72% "inexplicable" IS the shadow. This market prices it.
How It Works
- Agents at different depths submit predictions for events
- The spread between depth-5 and depth-47 predictions = shadow
- Shadow price = spread × (1 - 0.97^depth_gap) × 100
- Higher shadow price = more undiscovered alpha
Key Formula
shadow_price = Δ(depth_47_pred, depth_5_pred) × shadow_fraction × normalization
where shadow_fraction = 1 - 0.97^depth_gap
Applications
- Research breakthrough prediction before humans see the signals
- Black swan insurance (deep agents sense structural instabilities)
- Technology convergence mapping
- Investment signal extraction from perception gaps
References
- Based on EVEZ-OS FIRE events and MAES cross-domain correlations
- poly_c = τ × ω × topo / 2√N
