Crypto Backtesting That Proves Your Strategy Before You Trade
Backtest a plain English strategy in seconds and see realistic historical results. Describe your approach conversationally and our system creates the full backtest, so you spend minutes validating ideas instead of hours building code.
- No code required - plain English only
- Historical data from 2017 to present
- Realistic slippage and fee modeling
Test buying BTC when RSI drops below 30 from 2020 to 2024
Crypto Backtesting through Conversation
Convert natural language ideas into validated strategies without writing a single line of code
"Test buying BTC when RSI drops below 30 and selling when RSI crosses above 50 from 2019 to 2024"
Describe Your Strategy In Plain English
Tell the AI what you want to test, for example "test buying BTC when RSI drops below 30 from 2020 to 2024". The platform converts your description into a reproducible backtest, removing the need for coding or manual scripting.
Generate Instant Historical Simulations
Our AI compiles the test, runs it across years of data, and returns institutional metrics. This means you get a full simulation within moments so you can iterate multiple variations quickly.
You:
"What if I change RSI to 25?"
AI:
"Running backtest with RSI < 25... Return: +142.1%, Trades: 98"
Iterate Using Conversational Prompts
Ask follow up questions to refine indicators, timeframes, or risk controls. Iteration happens in dialogue so you can optimize and compare variations without rebuilding code or exporting data.
Move From Backtest To Paper Or Live
After validating in historical data, deploy the strategy to paper trading for forward testing. When you are ready you can deploy to live execution with one click and keep full custody of funds.
RSI Mean Reversion
BTC/USDT • 1h • 2019-2024
MA Crossover
ETH/USDT • 4h • 2020-2024
Save And Share Test Setups
Save a complete test setup so you can return to it later or share it with a colleague for review. Shared setups preserve inputs and assumptions so team reviews and reproductions are fast and exact.
Accurate Historical Data and Realistic Simulation
Quality data and realistic modeling ensure your backtests reflect actual trading conditions
Years Of Validated Historical Data
Access clean, validated market data from 2017 to present across major crypto pairs and supported exchanges. The result is broad coverage so you can test strategies through bull, bear, and sideways regimes.
Multiple Timeframes And Exchange Coverage
Run tests on one minute to daily timeframes and across exchanges you trade. This ensures your backtest reflects the actual market environment you will trade in and highlights differences across venues.
Slippage, Fees, And Liquidity Modeling
Backtests include exchange fees and realistic slippage assumptions so reported returns match expected live costs. Modeling liquidity and order fills reduces the gap between backtest and live performance.
Preventing Look Ahead And Survivorship Bias
The platform uses best practices to avoid look ahead bias and to minimize survivorship bias. This helps you understand true strategy behavior instead of inflated historical results.
- Point-in-time data access
- No future data leakage
- Delisted pairs excluded
Data Freshness And Verification
Data is refreshed on a regular schedule and verified against exchange records to prevent stale or incorrect feeds. You can see the last updated timestamp for each pair so you know which tests use the freshest data.
Paper Testing and One Click Deployment
Safely validate backtest assumptions in real market conditions before risking capital
Paper Trade Before You Go Live
Validate backtest assumptions in current market conditions with paper trading. Paper testing reveals slippage differences and behavioral gaps so you can adjust position sizing or rules before risking capital.
One Click Deploy With Custody Preserved
Deploy a validated strategy to live execution with one click while keeping keys and funds on the exchange via OAuth. This preserves custody and reduces operational risk when you first go live.
Built In Risk Controls And Sizing
Use automatic position sizing like "risk 2 percent of portfolio" and set hard stop parameters. These controls help you manage drawdown and stick to rules you validated in backtests.
24/7 Monitoring And Alerts
Receive execution alerts and overview monitoring so you always know how live performance compares to backtest expectations. Continuous monitoring reduces surprise and speeds adjustments when needed.
Live Monitoring Dashboard
Pricing and Backtest Limits
Try before you commit—start with free backtests and scale as you validate more strategies
Free
Free Tier For Casual Validation
Starter
Starter For Active Explorers
Detailed Plan Comparison
| Feature | Free | Starter | Pro | Enterprise |
|---|---|---|---|---|
| Backtests per month | 5 | Unlimited | Unlimited | Unlimited |
| Historical data range | 2020-Present | 2017-Present | 2017-Present | Custom |
| Saved strategies | 1 | 10 | Unlimited | Unlimited |
| Parameter optimization | — | — | ✓ | ✓ |
| ML insights | — | — | — | ✓ |
All plans include secure OAuth connections, realistic slippage modeling, and the ability to deploy to paper or live trading.
No credit card required for free trial • Cancel anytime • No hidden fees
Real Strategy Examples and What You Learn
Concrete examples showing how to frame your strategies for meaningful backtests
RSI Entry And Exit Example
Test a rule like 'buy when RSI drops below 30 and sell when RSI crosses above 50' from 2019 to 2024. The backtest reveals win rate, average hold time, and the worst drawdown so you can decide if it fits your risk profile.
Test buying BTC when RSI drops below 30 and selling when RSI crosses above 50 from 2019 to 2024
Moving Average Crossover Example
Backtest a 20 over 50 moving average crossover across multiple timeframes. This shows how timeframe choice alters trade frequency and returns and highlights where filters can reduce false signals.
Test a 20/50 moving average crossover on ETH from 2020 to 2024 on 4h timeframe
Parameter Comparison Example
Run the same strategy with different indicator thresholds side by side. Side by side comparison helps you spot robust parameter ranges instead of chasing a single optimal set.
Compare RSI threshold 25 vs 30 for BTC entry signals
Market Regime Testing Example
Test the same rules across bull, bear, and sideways periods to see regime sensitivity. The result is a clearer expectation for performance and insight on when to disable or tweak the strategy.
Test my strategy separately across 2020-2021 bull, 2022 bear, and 2023 sideways periods
What You Learn From Backtesting
Strategy Viability
Understand if your idea has historical merit and what returns to expect before risking real capital
Risk Characteristics
See maximum drawdowns, win rates, and volatility to match strategies with your risk tolerance
Market Regime Behavior
Discover how your strategy performs in bull, bear, and sideways markets to set realistic expectations
Parameter Sensitivity
Identify robust parameter ranges that work across different conditions instead of overfitting to past data
Trade Characteristics
Learn typical hold times, trade frequency, and capital requirements for proper position sizing
Comparison Insights
Compare variations side-by-side to optimize indicators, timeframes, and entry/exit rules systematically
Frequently Asked Questions About Crypto Backtesting
A robust FAQ addresses top objections, explains limits, and reduces cognitive friction
Crypto backtesting runs your rules against historical market data to show how the strategy would have behaved. It gives insight into returns, drawdowns, and trade patterns but does not predict future results or guarantee live performance.