Kalshi Paper Trading
Forward-test Kalshi strategies with virtual cash before risking real money. Your fills are priced from DepthFeed's live order books — buys at the ask, sells at the bid, positions settled automatically at market resolution — and every strategy gets its own equity curve, open-position view, and full trade log in the dashboard.
DepthFeed Paper Trading is a forward-testing environment in the DepthFeed dashboard: strategies hold virtual cash and trade live Kalshi markets at real order-book prices. Signals arrive from your own system via a per-strategy webhook, or from a deployed Backtest Lab rule, and results are tracked as an equity curve with realized and unrealized P&L.
Kalshi paper trading at a glance
- Fills
- Live book — buys at ask, sells at bid
- Settlement
- Automatic at resolution ($0 / $1)
- Signal webhook
- POST /paper/hook/{token} · 120/min
- Strategies per plan
- 1 free · 5 Quant · 15 Research · 40 Desk
- Starting balance
- $100–$1,000,000 virtual (default $10,000)
- Mark cadence
- ~90 seconds
How paper trading works
Bring your own bot — signals over webhook
Each strategy gets a secret webhook URL. Your system — a bot, a cron job, a notebook — POSTs buy/sell/close signals with a market id and a dollar size, and DepthFeed fills them at the live book at signal time. A payload can never set its own price, so the track record is honest by construction. Idempotency keys make retries safe, and the token rotates on demand.
Or deploy a rule from the Backtest Lab
The Backtest Lab backtests entry rules on resolved up/down markets — time-window entries, level crosses, dip reversion — with depth-aware VWAP fills against the recorded ladder. When a rule survives the backtest, deploy it to paper trading with a stake, take-profit/stop-loss, and a max-open cap; it then runs server-side against live quotes, no infrastructure on your end.
A real track record, not a spreadsheet
Positions are marked from the live book on a ~90-second cadence and settle to $0/$1 automatically when the market resolves — the same settlement data the API serves. The equity curve, realized vs unrealized P&L, and per-trade log give a strategy the forward evidence a backtest alone can't: how it behaves on markets that hadn't happened yet.
Inspect the data before integrating
Start with a bounded sample, verify the fields and timestamps, then choose the API or research workflow that matches the job.
Questions, answered.
Every fill is priced from DepthFeed's live order book at the moment the signal arrives: buys pay the best ask, sells hit the best bid, and positions settle to $0 or $1 automatically when the market resolves. Signals can never supply their own price, so a paper track record can't be gamed. One honest caveat: paper fills use real displayed liquidity for pricing but don't consume it, so a large live order could see more slippage than the top-of-book paper fill.