Backtesting Overview
Vantixs backtesting simulates your strategy on historical market data using a Rust-powered engine capable of processing 50,000+ bars per second. Validate your ideas with realistic execution modeling before risking any capital.
During the BETA period, backtesting and paper trading are fully available. Live trading with real capital is planned for a future release.
Why Backtest?
Benefits of Backtesting
Validate Ideas
Prove your strategy works on historical data before committing capital
Measure Performance
Get concrete metrics — Sharpe Ratio, Max Drawdown, Win Rate, and more
Understand Risk
Know your worst-case drawdown scenarios through Monte Carlo simulation
Optimize Parameters
Find the best indicator settings with walk-forward optimization
Build Confidence
Trade paper accounts with conviction based on data-driven results
Save Time
Months of market exposure simulated in seconds at 50K bars/sec
Vantixs Backtesting Features
High-performance event-driven simulation built in Rust:
- 50,000+ bars per second processing speed
- True bar-by-bar processing that simulates realistic order execution
- Slippage modeling based on historical volume profiles
- Configurable commission impact (default 0.1% per trade)
- Market impact estimation for larger order sizes
- Historical data from 8 supported exchanges: Binance, Coinbase, Kraken, OKX, Bybit, KuCoin, Bitget, and Gate.io
Running a Backtest
Complete Backtest Workflow
Design Strategy
Complete your node connections on the canvas. Ensure all nodes show green status indicators.
Click Backtest
Find the Backtest button in the top toolbar. A configuration panel will open.
Configure Settings
Choose your parameters: - **Date range**: e.g., last 6-12 months of historical data - **Initial capital**: e.g., $10,000 (virtual) - **Commission model**: e.g., 0.1% per trade - **Slippage**: e.g., 0.05% per fill - **Exchange data source**: Select from 8 supported exchanges
Click Run
The Rust engine processes at 50K+ bars/sec. Most backtests complete in seconds.
Analyze Results
Review the equity curve, trade log, and performance statistics. Look for consistent growth with manageable drawdowns.
Key Metrics
| Metric | Description | Good Target |
|---|---|---|
| Sharpe Ratio | Risk-adjusted return (higher = better risk/reward) | > 1.5 |
| Max Drawdown | Largest peak-to-trough decline | < 20% |
| Win Rate | Percentage of profitable trades | > 50% |
| Profit Factor | Gross profit / Gross loss | > 1.5 |
| CAGR | Compound annual growth rate | > 15% |
| Total Trades | Number of trades executed in the period | Varies by strategy |
No single metric tells the whole story. A strategy with a 40% win rate can still be highly profitable if its average win is much larger than its average loss (high Profit Factor). Always evaluate metrics together.
Avoiding Common Pitfalls
These mistakes can make your backtest results misleading
Look-ahead Bias
Using future data that wouldn't be available at trade time. Vantixs prevents this by processing bars sequentially, but be careful with indicator lookback periods.
Survivorship Bias
Only testing assets that still exist today. Include a variety of trading pairs and time periods in your testing.
Overfitting
Optimizing too many parameters to perfectly fit past data. Use walk-forward validation to ensure your strategy generalizes.
Unrealistic Costs
Ignoring slippage and commissions. Vantixs models these by default — keep them enabled for accurate results.