Kalshi historical data
Kalshi Historical Data
A last-price series does not show the spread or displayed size a strategy faced. DepthFeed stores the complete yes/no book — up to 100 levels per side for the markets and date ranges listed in its coverage documentation.
Kalshi historical order-book data is a sequence of recorded full-book observations over time. DepthFeed uses continuous full-depth polling of Kalshi's public REST orderbook and serves the stored observations through REST; it does not claim observations for markets, timestamps, or gaps outside the documented archive.
Kalshi historical data at a glance
- Capture
- Paced full-depth REST polling
- Depth
- Up to 100 levels per side (yes/no)
- Series
- KX{ASSET}15M · KX{ASSET} · KX{ASSET}D
- Market windows
- 15-min · hourly · daily · weekly
- Assets
- 7 — BTC · ETH · SOL · XRP · DOGE · BNB · HYPE
- Timestamps
- Millisecond observation time; venue-specific source stamps
- Underlying price
- Nearest preceding Binance reference when available
- History
- 7/30/90-day windows + full archive (Desk)
- Delivery
- REST history + normalized live WebSocket frames
- Resolution
- Raw stored observations or ?interval= 1s–1d
Discover the ticker before pulling Kalshi history
Kalshi series names and market tickers are different identifiers. Discover venue-native tickers for the requested time window, then pass one exact ticker to the book or snapshot endpoint.
curl -s "https://api.depthfeed.com/v3/kalshi/markets?series=KXBTC15M&start_time=2026-07-01T00:00:00Z&end_time=2026-07-02T00:00:00Z" \
-H "Authorization: Bearer df_your_key"
curl -s "https://api.depthfeed.com/v3/kalshi/<exact_market_ticker>/snapshots?include_orderbook=true" \
-H "Authorization: Bearer df_your_key"- Do not synthesize historical market tickers from UTC timestamps; use the identifiers returned by discovery.
- DepthFeed normalizes prices to 0–1 dollars while retaining the venue-native ticker and Yes/No book semantics.
Kalshi historical data
What's in the archive
Daily Parquet downloads or historical REST requests
Use a listed daily file when a research job repeatedly scans a fixed archive, and REST when market filters, bounded time windows or pagination suit the workflow. The public bulk catalogue shows actual available dates, native schemas and pricing. Inspect those entries before buying; a synthetic sample demonstrates the file format and is not proof of captured coverage.
The full book, not a last price
A historical last price does not expose the spread or displayed size. DepthFeed's archive holds the complete yes/no book — up to 100 levels per side for supported kalshi markets, so you can inspect the recorded ladder and model an order against the liquidity visible at that observation.
Resolution that survives short-dated markets
Short-dated crypto markets can settle within minutes, so an hourly archive may capture only a small part of their path. DepthFeed uses paced REST polling; realized cadence varies with active-market load and Kalshi's upstream quota; use the returned timestamps and documented series floors to determine whether a particular study has sufficient resolution.
REST history and live updates: separate contracts
Pull stored depth through the REST API and subscribe to normalized current-book frames over WebSocket. The two surfaces share documented book concepts but can have different envelopes and venue-specific fields. Plans serve rolling 7-, 30-, and 90-day windows; Desk is bounded by the archive actually held.
Choose daily files or the historical API
Inspect available dates, native schemas and prices in the public file catalogue, or use the snapshot API for bounded requests. Choose the delivery path that fits the research job.
