Live market data

Describe a strategy.
See if it works.

Type a trading idea in plain English. Our AI translates it to a validated strategy. You get an institutional-grade tearsheet in minutes.

backtester.run — compose

Your strategy

>_

Backtest results — BTCUSDT 1h · 2022–2024

Total Return

+184%

vs BH +61%

Sharpe

1.84

annualised

Max DD

−18.3%

peak-to-trough

Win Rate

61.4%

142 trades

Equity curve

Infrastructure

Live crypto data
Live equity data
Distributed object storage
Institutional backtest engine
AI strategy generation
Managed database

How it works

From idea to tearsheet
in three steps

No Python. No config files. No manual indicator math. Just describe what you want.

01

Describe your strategy

Type it exactly how you think about it. "Long BTC when 1h RSI crosses below 30, exit at 2× ATR profit or 1× ATR stop."

02

AI validates it

Our AI translates your prompt into a structured spec, validates every indicator, signal, and exit rule — then runs 8 semantic checks before a single bar is processed.

03

Get the tearsheet

Equity curve, drawdown, monthly heatmap, trade-level FIFO P&L, Sharpe, Sortino, max drawdown, win rate, profit factor — all computed on real minute-bar data.

Example strategies

Start from one of these,
or write your own

Real backtests on real data. Hypothetical results for illustration.

Crypto · Momentum

Long BTC when the 12-period EMA crosses above the 26-period EMA on the daily chart, exit when it crosses back or at a 5% stop loss

Return

+184%

Sharpe

1.84

Max DD

−18%

Try this strategy →
Equity · Mean Reversion

Buy SPY when price closes below the lower Bollinger Band (20, 2σ), exit when price reaches the middle band or after 20 bars

Return

+91%

Sharpe

1.42

Max DD

−12%

Try this strategy →
Crypto · RSI + ATR

Long ETH on 1h when RSI(14) crosses below 30 and volume is in the top 10th percentile. Exit at 2× ATR profit or 1× ATR stop

Return

+247%

Sharpe

2.11

Max DD

−22%

Try this strategy →

The platform

Everything a systematic trader needs

Built on the same engine used for internal algo development at Lapunga.

Full TA-Lib library

All 158 TA-Lib functions — momentum, overlap, volatility, volume, statistical, and 61 candlestick pattern recognisers. Exact TA-Lib numerical parity: bit-for-bit identical to the C library, not a pure-Python approximation.

RSIMACDCDL PatternsStat Functions+140

Institutional tearsheet

Equity curve, underwater drawdown chart, monthly P&L heatmap, returns distribution, FIFO trade-level P&L table. Everything a quant fund would want to see.

SharpeSortinoCalmarMaxDDWinRate

No code runs

Your strategy is a validated spec — never arbitrary code. The whitelist-only DSL means zero attack surface. Multi-tenant isolation enforced at the Postgres RLS layer.

DSL whitelistRow-level securityClerk auth

Minute-bar history

Back to 2020 on top crypto pairs and S&P 500 components. Six timeframes from 1m to 1d. Data stays warm in Redis and cold in R2 for fast repeated runs.

CryptoEquity1m–1dFrom 2020

Pricing

Simple, honest pricing

Start free. Upgrade when you need more runs. Cancel any time.

Free

$0

forever

  • 1 backtest / month
  • 3 AI generations / month
  • Full tearsheet
  • Crypto + equity data
  • 5-min wall-clock cap
  • 1 concurrent run
Get started free
Most popular

Pro

$29

per month · or $278/yr (save 20%)

  • 50 backtests / month
  • 150 AI generations / month
  • Full tearsheet + exports
  • 10-min wall-clock cap
  • 2 concurrent runs
  • Robustness add-on (v1.1)
Start Pro trial

Quant

$79

per month · or $758/yr (save 20%)

  • 500 backtests / month
  • 1,000 AI generations / month
  • Full tearsheet + exports
  • 20-min wall-clock cap
  • 4 concurrent runs
  • Robustness add-on (v1.1)
Start Quant trial

Annual billing saves up to $158/year — cancel any time, no questions asked.

FAQ

Common questions

Crypto: 10 top pairs including BTC, ETH, SOL, BNB, XRP and more. Equity: top 20 S&P 500 names. Six timeframes from 1-minute to daily. Data goes back to 2020 and refreshes continuously from live broker feeds.

Get started

Your first backtest is free.

No credit card. No Python environment. No waiting for a quant to review your idea. Just type and run.

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Backtest results are hypothetical and do not guarantee future performance.