Services → Backtesting & Strategy Validation

Backtesting &

Strategy Validation

Rigorously test your trading strategies with institutional-grade statistical analysis. Know if your edge is real before risking capital.

Service Tiers

Retail-Grade Backtesting

Standard backtesting using MT4/MT5 strategy tester or similar platforms

Historical price data

Visual equity curves

Basic performance metrics

Trade-by-trade analysis

Best For:

Long-term systematic trading


Typical Pricing

$500 - $1,500

Timeline

3-7 days

Institutional-Grade Backtesting

Rigorous statistical validation with advanced methodologies

Tick-level precision

Statistical significance tests

Realistic slippage modeling

Out-of-sample validation

Best For:

Serious traders, funded accounts


Typical Pricing

$2,500 - $7,500

Timeline

2-4 weeks

Walk-Forward Analysis

Continuous optimization and testing to prevent overfitting

Rolling optimization windows

Robustness testing

Stability analysis

Degradation detection

Best For:

Long-term systematic trading


Typical Pricing

$3,500 - $10,000

Timeline

3-6 weeks

Monte Carlo & Stress Testing

Simulate thousands of scenarios to understand strategy risk

Monte Carlo simulation

Drawdown distribution

Market regime analysis

Risk of ruin calculations

Best For:

Risk assessment, position sizing


Typical Pricing

$2,000 - $6,000

Timeline

1-3 weeks

Our Methodology

01

Data Collection

High-quality historical data with proper bid/ask spreads and tick precision

02

Realistic Modeling

Account for slippage, commissions, latency, and market impact

03

Statistical Analysis

Sharpe ratio, drawdown analysis, win rate significance, and more

04

Validation Report

Comprehensive report with actionable insights and recommendations

Performance Metrics We Analyze

Total Return & CAGR

Maximum Drawdown

Sharpe Ratio

Sortino Ratio

Win Rate & Profit Factor

Average Trade Duration

Monthly Return Distribution

Correlation Analysis

Statistical Significance

Risk of Ruin

Monte Carlo Confidence Intervals

Out-of-Sample Performance

Common Backtesting Mistakes

Look-ahead bias: Using future information that wouldn\'t be available in real-time

Survivorship bias: Only testing on assets that still exist today

Overfitting: Optimizing until it works perfectly on past data but fails live

Unrealistic execution: Ignoring slippage, spreads, and latency

We design backtests to avoid these pitfalls, giving you realistic expectations for live trading.

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Ready to Validate Your Strategy?

Schedule a free consultation to discuss your backtesting requirements.