On-Demand Combinatorial Event Markets on Kalshi: Instantiation, Concentration, and Effective Market Breadth

Kalshi's multivariate-event architecture produces market objects on demand from exact selected legs. Across a registered seven-day interval, 190 independently validated temporal shards yield 7,611,594 unique REST MVE market tickers after excluding 5,777 boundary-overlap observations; the population was created at an average rate of 1.087 million objects per day, with strong hourly burstiness. The hierarchy is sharply compressed relative to the market-object count: 5,262,526 exact event keys, three collection keys, 83,701 selected-leg primitives, and 66,344,938 selected-leg occurrences. The largest collection accounts for 7,217,085 objects (94.82 percent), with an effective collection count of 1.11; the effective primitive count is approximately 720. REST and WebSocket are distinct observation surfaces: 1,487,330 created-notification tickers intersect the REST population in only 276,177 exact tickers. All three observed collection keys have current endpoint confirmation without establishing historical collection or rule versions. The exact structural signature yields 7,611,594 unique signatures with zero collision groups. At retrieval, 2,692,787 objects (35.38 percent) have positive cumulative volume or open interest; all observed 24-hour-volume values are zero and trade-count fields are unavailable. This is current-snapshot activity eligibility, not historical trading. The central result is that a very large on-demand market-object population is generated by a concentrated collection layer and reused primitive vocabulary; economic breadth must be measured at several hierarchical levels rather than by ticker count alone. Exact public endpoint evidence is available for 7,357,576 MVE objects, whereas only 126,806 have an exact determination-to-endpoint pair: terminal-state coverage and lifecycle-path coverage are distinct statistical objects.