Kalshi Market Data
A last price hides the spread and displayed size behind it. DepthFeed serves stored the complete yes/no book — up to 100 levels per side, a market-implied price derived from the book, and a preceding Binance reference price when a valid join exists.
Kalshi market data in DepthFeed combines recorded book observations, a price derived from the visible ladder, and a separately sourced reference series. REST serves history and WebSocket serves normalized current-book updates; cadence and fields remain venue-specific.
Kalshi market 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 a Kalshi market, then request recorded market data
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 Kalshi market data covers
The full book, price, and underlying — one snapshot
A stored observation carries the complete yes/no book — up to 100 levels per side and the market price derived from that ladder. Historical queries ASOF-align the nearest preceding Binance price for the underlying (BTC, ETH, SOL, XRP, DOGE, BNB, and HYPE) when available; a missing join remains null rather than becoming a fabricated value.
Depth, not a last price
A last-price feed cannot show the depth available to a simulated order. DepthFeed captures paced REST polling; realized cadence varies with active-market load and Kalshi's upstream quota, letting a model walk the ladder recorded at a particular observation while remaining explicit about activity between stored rows.
Volume is activity, not executable size
Kalshi volume describes trading activity over the venue's stated measurement window. It does not tell you how much size is available at the current best price, how far a new order would walk the ladder, or whether the same liquidity existed earlier. Keep venue-reported volume, current displayed depth, spread, and open interest as separate fields and use the recorded book for execution research.
Four views, one schema
The same recorded books support the order-book, price, historical, and API views. REST and WebSocket share normalized book concepts, with their exact response contracts documented separately.
Inspect markets before choosing a delivery path
Browse current markets first, then move to REST history or normalized WebSocket books when the identifiers and fields match your workflow.
Questions, answered.
Stored full-book observations, up to 100 levels per side on Kalshi; a market-implied price derived from the visible ladder; a millisecond observation timestamp; and a preceding Binance reference price when a valid join exists.