Derived Kalshi microstructure tables for quote freezes, recovery curves, spread compression, leader-lag clusters, and price-discovery research.
Full schema & known gaps →· Sold as-is — but if a file is broken or won't open, email [email protected] and we'll send a fixed file or refund you. No hassle.
Inspect the free sample rows and schemas before buying.
Frozen artifact delivery: the product page and shipped documentation state the exact coverage, row counts and known limitations. A purchase delivers the advertised frozen artifact; no future refresh is promised unless the checkout terms explicitly say so.
Competition-season mapping and the complete fixture denominator are unverified. This is not a complete-season archive.
This pack contains derived quote-event tables and research summaries, rather than a raw order-book history. Its source observation window is not recorded in the reviewed metadata.
UTC timestamps retain their recorded precision; dates alone identify UTC days. The data card's release timestamp is not an observation boundary.
Scheduled event times are not inferred from capture windows or combo trade dates.
The schema and coverage notes identify this artifact's record types: sampled quotes or depth, trade prints, derived outcomes or analysis, depending on the product. Observation time, exchange event time and artifact vintage are different clocks. Read the documented fields, gaps and joins before deciding whether the file fits your research; a quote observation does not establish a fill.
~587K derived event rows across 6 event libraries (largest 178K quote-freezes) + summary tables + 20+ charts, computed from 20M+ raw Kalshi ticks
Work from derived freeze events rather than rebuilding the detector before testing a research question.
Compare how quickly prices and spreads normalized after the captured event classes.
Use leader-lag and spread-compression tables with the published methodology.
Load the Parquet tables and rerun the documented aggregations with your own filters.
We publish real sample rows — not a marketing mockup. Load them in DuckDB, inspect the schema and coverage contract, then decide.