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.
What's in the archive
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.
History and live in one format
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.
Inspect a real historical slice before integrating
Start with a bounded recorded-book sample, verify timestamps and ladder shape, then create a key when the schema fits the research job.
Questions, answered.
Plans serve rolling 7-, 30-, and 90-day windows, and Desk can query the full archive actually held. Availability remains bounded by each venue, asset, market series, and capture start; exact floors are published in the coverage docs.