Backtest crypto strategies on history — no code, no local install.
Describe a strategy as rules, replay it bar by bar over Binance spot and USDT-M futures history, and get a report that is honest about fees, funding, drawdowns and overfitting.
100+
indicators & patterns
60+
report metrics
1–125×
futures leverage
Since 2020
Binance market history
// how it works
From an idea to evidence in four steps
- 01
Describe
Combine indicators and rules in the visual editor, start from a template, or describe the idea to an AI assistant. The result is a declarative config — no code.
- 02
Backtest
The engine replays the strategy bar by bar on the server — spot or futures, with fees, slippage, funding and liquidation.
- 03
Read the report
Equity and drawdowns, every trade on the chart, monthly returns, regimes and Monte Carlo — 60+ metrics in one place.
- 04
Stress-test
Compare runs with a significance test, sweep parameters with walk-forward and keep only what survives out of sample.
// strategy as data
A strategy is a config, not a script
Every strategy is a declarative JSON document: readable, diffable, versioned — and safe to run on a shared server, because nothing in it is executable.
- AND / OR / NOT groups, crosses, ranges, rising / falling and look-back windows
- Higher timeframes and other symbols inside the same rule — without look-ahead
- Several entry layers, pyramiding, DCA grids, resting stop and limit orders
- Take-profit and stop-loss in %, ATR or R — ladders, break-even, trailing, time exits
- Five sizing modes up to volatility targeting, plus daily loss and drawdown guards
- Named parameters, version history and a dry run before the full backtest
1{2 "name": "Trend pullback",3 "market": { "type": "spot", "exchange": "binance" },4 "instrument": { "symbol": "BTCUSDT", "timeframe": "4h" },5 "sides": ["LONG"],6 "risk": { "feesPct": 0.1 },7 "entries": [{8 "id": "pullback", "side": "LONG", "sizePct": 50,9 "conditions": { "operator": "AND", "list": [10 { "left": { "indicator": "EMA", "params": { "period": 50 } },11 "op": "GT",12 "right": { "indicator": "EMA", "params": { "period": 200 } } },13 { "indicator": "RSI", "params": { "period": 14 },14 "op": "CROSS_UP", "value": 30 }15 ] }16 }],17 "exit": {18 "atrRef": { "indicator": "ATR", "params": { "period": 14 } },19 "stopLossAtrMult": 2,20 "takeProfitR": 321 }22}
// features
Everything for testing a strategy, in one workspace
From the first rule to a robustness check — with the market data already loaded.
Strategy builder
100+ indicators in 14 groups — from RSI, MACD and Ichimoku to market structure, candle and chart patterns, open interest and funding. A preview chart shows where the rules fire as you edit.
Backtest engine
Spot and USDT-M perpetual futures: long and short, 1–125× leverage, isolated or cross margin, historical funding every 8 hours and liquidation by the Binance formula.
Backtest report
Sharpe, Sortino, Calmar, max drawdown, profit factor, expectancy, buy-and-hold alpha and more. Bar-by-bar trade replay, regime breakdowns, a printable tear-sheet and CSV export.
Compare & batch
Put up to four runs side by side with a significance test, shift the start date or sweep a symbol matrix in one batch, and preview how several runs combine as a portfolio.
Optimizer
Grid and random search over up to 12 parameters, walk-forward with rolling or anchored windows, robustness scoring and sensitivity heatmaps. Promote a winner as a new strategy version.
Research Lab
Event studies and feature scans against forward returns, with multiple-testing correction, a held-out half and edge after costs — a filter for ideas before they become strategies.
Analog Lab
Finds the moments in history that looked like the current one and shows what followed: a fan of paths against a baseline, and a TP/SL plan tested on every episode.
Market data
Binance candles since 2020 plus funding, open interest, long/short and taker ratios — delisted perpetuals included. Export candles, indicators and labels as CSV datasets.
Strategies written by AI
Describe an idea in plain words to ChatGPT, Claude or another assistant: with the strategy reference Janorium publishes, it writes a config you paste into the editor. Scoped API keys open the same API to your own scripts.
// honest by design
Built not to flatter your strategy
A backtest is only useful if it is hard to fool yourself with. This is what the engine and the report do about it.
Real costs
Maker / taker fees, constant, ATR-scaled or volume-impact slippage, a cap on the share of bar volume, historical funding.
No look-ahead
Higher-timeframe reads only see closed bars; orders fill at the bar close or the next open.
Pessimistic by default
When one bar touches both the stop and the target, the stop counts first — or the 1m / 5m bars inside it decide.
No survivorship bias
Hundreds of delisted perpetuals stay in the data, so a symbol universe can include coins that later died.
Overfitting checks
A Deflated Sharpe note that counts how many variants were tried, q-values and held-out halves in Research Lab, a randomized-entry baseline.
Fragility on display
Monte Carlo resampling, drawdown episodes and regime breakdowns show how much a result depends on luck or on one market phase.
// why janorium
A candle with a J cut out of it
The candle is the basic unit of every price chart. The J stands for Janorium — and for Janus, the Roman god who looks into the past and the future at once. Janorium is about the first look: what a strategy would have done on real history, so the decisions about what comes next rest on evidence rather than hope.
// faq
Questions people ask first
What is backtesting?
Backtesting means running a strategy's rules over historical market data to see how it would have traded: every entry and exit, the fees it paid, the drawdowns along the way. It shows whether an idea held up in the past before you put money behind it — not that it will hold up in the future.
Read the full guideCan I look around before signing up?
Yes. Open any strategy from the leaderboard. Public ones open in full — config, version history, every run and the complete report with trades — exactly as their owner sees them. Private ones show their results without their rules: headline metrics, equity curves and the summary of every run. An account lets you run your own backtests, clone public strategies and use the labs.
Do I need to write code?
No. A strategy is a declarative config: you build it in the visual editor or paste JSON. Nothing you submit is ever executed as code.
Which markets and data are covered?
Binance spot and USDT-M perpetual futures with history from 2020: 1h and 4h bars for every tracked symbol, down to 5m for the major pairs. Futures also carry funding rates, open interest, long/short and taker ratios; BTC and ETH add mark and index prices and order-book depth.
Does a good backtest mean the strategy will make money?
No. A backtest shows how a set of rules would have behaved on past data. Janorium works hard to make that picture honest — costs, funding, no look-ahead, overfitting checks — but markets change, and nothing here is financial advice.
How is the leaderboard ranked?
By the Janorium score, not by the best return. It multiplies the quality of the typical run — median annual return, Sharpe, average drawdown, share of profitable runs — by the evidence behind it: how many distinct backtests, across how many symbols, timeframes and years, with how many trades. Only runs of the current version that paid fees count, so one lucky fee-free run cannot top the table.
Can an AI write a strategy for me?
Yes. Give ChatGPT, Claude or another assistant the strategy reference Janorium publishes and describe your idea in plain words — it writes the JSON config. Paste it into the editor and press Apply; if Janorium reports an error, send it back to the assistant to fix.
Read the full guideIs it free?
Yes. Janorium is an independent portfolio project — sign up and run backtests at no cost.
Have a trading idea? Find out how it would have done.
Create an account, pick a template or write your own rules, and read your first report.
Create account and run your first backtest