Backtesting Overview

Test your trading strategies against historical data before risking real capital.

What is Backtesting?

Backtesting allows you to:

Validate Strategy Logic - Ensure your strategy behaves as expected
Evaluate Performance - See historical returns, win rates, and drawdowns
Optimize Parameters - Fine-tune settings for better results
Build Confidence - Understand how your strategy performs in different market conditions

Testing Modes

TradeStaq offers two backtesting modes:

Feature	Quick Test	Full Backtest
Duration	Fixed 7-day window	Custom date range
Save Required	No	Yes (strategy must be saved)
Metrics	Basic (Return, Win Rate, Trades, Drawdown, PF)	Full suite including advanced ratios
Chart	Trade markers on candlestick	Full equity curve + drawdown
Access	AI Builder editor panel	Backtests page
Speed	Instant (seconds)	Minutes (depending on data range)
Results Stored	In-memory only	Saved with versioning

Quick Test

Available directly from the AI Strategy Builder editor. Select an exchange, symbol, and timeframe — the engine runs a 7-day instant backtest and returns results in seconds. No strategy save required. Ideal for rapid iteration during strategy development.

Full Backtest

Run from the Backtests page with full configuration options: custom date range, detailed metrics, equity curve visualization, trade list export, and result comparison. Requires saving your strategy first. Auto-versions strategy code so you can track changes over time.

How It Works

┌─────────────────────────────────────────────────────────────┐
│                    BACKTESTING FLOW                         │
│                                                             │
│  ┌──────────┐    ┌──────────────┐    ┌─────────────────┐   │
│  │ Strategy │───▶│  Historical  │───▶│  Simulated      │   │
│  │  Config  │    │    Data      │    │  Execution      │   │
│  └──────────┘    └──────────────┘    └────────┬────────┘   │
│                                               │             │
│                                               ▼             │
│                                      ┌─────────────────┐   │
│                                      │    Results &    │   │
│                                      │    Metrics      │   │
│                                      └─────────────────┘   │
└─────────────────────────────────────────────────────────────┘

The Process

Select Strategy - Choose a TradeStaq strategy to test
Configure Parameters - Set trading pair, timeframe, date range
Run Simulation - Strategy executes against historical candles
Analyze Results - Review performance metrics and equity curve

Key Metrics

Metric	Description	Good Value
Total Return	Overall profit/loss percentage	Positive
Win Rate	Percentage of profitable trades	> 50%
Profit Factor	Gross profit / Gross loss	> 1.5
Max Drawdown	Largest peak-to-trough decline	< 20%
Sharpe Ratio	Risk-adjusted returns	> 1.0
Sortino Ratio	Downside risk-adjusted returns	> 1.5
Total Trades	Number of completed trades	Varies

Subscription Requirements

Feature	Free	Pro	Trader	Whale
Run Backtests	-	✓	✓	✓
Quick Test (AI Builder)	-	✓	✓	✓
Advanced Metrics	-	-	✓	✓
Multi-Timeframe	-	-	✓	✓
CSV/PDF Export	-	-	✓	✓
Public Sharing	-	-	-	✓
Parameter Optimization	-	-	-	✓
Backtest Comparison	-	-	-	✓

Note: For live tier values, see the Plans Comparison page.

AI Builder Integration

The AI Strategy Builder includes a built-in Quick Test feature for rapid iteration. Describe your strategy idea, let the AI generate code, then instantly test it — all within the same interface. See AI Builder Testing for details.

Important Limitations

Note: Past performance does not guarantee future results. Backtesting has inherent limitations.

What Backtesting Cannot Simulate

Factor	Real Trading	Backtesting
Slippage	Price moves between signal and execution	Assumes instant fill at signal price
Liquidity	Large orders may not fill completely	Assumes unlimited liquidity
Market Impact	Your orders affect the market	No market impact
Latency	Network delays exist	Instant execution
Exchange Issues	Downtime, rate limits	Perfect availability

Best Practices

Don't Over-Optimize - Avoid curve-fitting to historical data
Use Out-of-Sample Testing - Test on data not used for optimization
Consider Transaction Costs - Factor in fees and spread
Test Multiple Periods - Verify across different market conditions
Start Small Live - Paper trade before going live

Backtest States

Status	Description
Pending	Queued for execution
Running	Currently processing historical data
Completed	Finished successfully with results
Failed	Error during execution
Cancelled	Manually stopped by user

Next Steps

Running a Backtest - Step-by-step guide
Interpreting Results - Understanding metrics
Best Practices - Optimization tips
AI Builder Testing - Quick Test from AI Builder

Related Guides

Trading Bots — deploy strategies after backtesting
Available Strategies — browse strategies to backtest
AI Strategy Builder — create custom strategies with AI
Connect an Exchange — set up for live trading after paper testing