Backtest Polymarket & Kalshi Strategies Without Writing Code
You should not need a data pipeline and a research notebook to find out whether an idea has an edge. The Backtest Lab runs the whole test in the browser, against the real recorded book.
The DepthFeed Backtest Lab is a no-code backtester built into the dashboard: pick a coin and a market window, choose a preset or write a short rule, and it replays your strategy against the recorded order book on already-resolved Polymarket and Kalshi up/down markets. Every fill is sized against the real ladder, so the P&L reflects the spread and slippage a live order would actually have paid — not a fill at the mid.
What the Backtest Lab is
Most prediction-market backtesting starts with a chore: pull the data, reconstruct the book, write a fill model, then finally test the idea. The Backtest Lab collapses that into a single screen. It loads a set of resolved up/down crypto markets, replays each one snapshot by snapshot in the browser, applies your entry rule, and settles every position at the market's real $0/$1 outcome — then shows you the equity curve, hit rate, and per-trade log.
Because the markets it tests on have already settled, results are instant and honest: there is no look-ahead, the outcome is the real one, and the book you fill against is the book that actually existed. It is the fastest way to answer the only question that matters early on — does this idea have an edge before costs, and does it survive them?
Presets, or your own rule
Start from a preset and adjust it, or write your own. The built-in presets are prediction-market-native, not repurposed TA: 'Late favorite' (buy the leading side in the final minutes), 'Fade the panic' (dip reversion after a sharp drop), 'Level cross' (enter when a price crosses a threshold), 'Spot leads the book' (act when the underlying moves before the contract reprices), and 'Cheap lottery' (small stakes on long-shot underdogs).
For anything the presets don't express, the Lab has a small JavaScript rule: a function called once per snapshot, oldest to newest, that sees only the past — window, minutes left, the up/down prices, the book — and returns a side to enter or nothing to pass. The custom script runs in a sandboxed worker, so untrusted code never touches the page, and one entry is allowed per market.
Fill models — from optimistic to honest
The fill model is where most backtests quietly lie, so the Lab makes it an explicit choice. 'Mid fill' fills at the snapshot midpoint — optimistic, useful as a best-case ceiling. 'Mid + slippage' adds a fixed slippage assumption to every entry. 'Book depth (VWAP)' walks the real recorded ladder at each entry, so a larger order pays a worse average price exactly as it would live.
Running the same rule under all three is the point: if an edge only exists at the mid and evaporates under depth-aware VWAP fills, it was never real. That gap — the difference between a fill at the touch and a fill that consumes resting size — is precisely what depth data exists to measure.
Coins, windows, and how much you test
The Lab covers all seven crypto assets (BTC, ETH, SOL, XRP, DOGE, BNB, HYPE) and every up/down window — 5-minute, 15-minute, 1-hour, 4-hour, and 24-hour. You choose how many resolved markets to replay, from a quick 25 up to 500, so you can sanity-check an idea in seconds and then stress it over a larger sample.
How many markets you can pull into a single run scales with your plan, the same gating as the data API — the free Explorer tier is enough to feel the tool out, and paid tiers widen both the sample and the history the run draws from.
From a backtest to a live paper track record
A backtest tells you how a rule would have done on markets that already settled. The obvious next question is how it does on markets that haven't happened yet — so when a rule survives, you deploy it straight from the Lab to Paper Trading. Time-window, level-cross, and dip rules map to the server-side paper worker, which then runs the rule forward against live quotes with a stake, take-profit/stop-loss, and a max-open cap.
That chain — backtest on the archive, then forward-test on live books — is the whole workflow the platform is built around. The Lab is where you kill bad ideas cheaply; paper trading is where the survivors earn a real, forward track record before a dollar is at risk.
Key takeaways
- 01The Backtest Lab is a no-code, in-browser backtester over resolved Polymarket & Kalshi up/down markets.
- 02It tests on already-settled markets, so results are instant, look-ahead-free, and settled at the real $0/$1 outcome.
- 03Use a prediction-market-native preset or a short sandboxed JavaScript rule — one entry per market.
- 04Three fill models — mid, mid + slippage, and depth-aware book VWAP — separate a real edge from a mid-price mirage.
- 05Survivors deploy in one click to Paper Trading to earn a forward track record on live books.
DepthFeed serves the full Polymarket & Kalshi order book over a REST API and live WebSocket. Free Explorer tier, no card.
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