Backtesting
Test your trading strategies on historical market data before risking real capital.
Backtesting
Test your trading strategies on historical market data before risking real capital. Backtesting is your most valuable tool for validating strategies, optimizing parameters, and establishing realistic expectations.
What is Backtesting?
Backtesting runs your trading strategy against genuine historical market data to show how it would have performed in past market conditions. It's the method serious traders use to:
Fine-tune strategy logic — Identify weaknesses and optimize entry/exit rules
Eliminate costly mistakes — Catch flaws before deploying real capital
Establish realistic expectations — Understand potential returns and drawdowns
Stress-test strategies — See how approaches handle different market phases
Key Features
Market Data Coverage
Historical Period
Up to 2 years
Exchanges
10+ spot and futures exchanges
Trading Pairs
10,000+ pairs available
Data Types
Candlestick (OHLCV), order book snapshots, trade execution records
Technical Indicators
Access 80+ built-in technical indicators across all major categories:
Trend Indicators — MA, EMA, MACD, ADX, Parabolic SAR, SuperTrend
Momentum Oscillators — RSI, Stochastic, CCI
Volatility Indicators — Bollinger Bands, ATR
Volume Indicators — OBV, A/D Line
Chart Patterns — Double Top/Bottom, Head & Shoulders, Triangles
Candlestick Patterns — Hammer, Doji, Engulfing
Logic Operators
Combine indicators using AND, OR, NOT logic operators to create sophisticated multi-condition strategies without writing any code.
Realistic Simulation
Configure your backtests to mirror actual trading conditions:
Trading fees — Maker/taker commissions based on your exchange tier
Slippage — Account for execution delays and price impact
Volume-based adjustments — Customize based on your trading volume
How to Run a Backtest
Step 1: Build Your Strategy
Create your trading strategy using the Strategy Builder:
Select 2-3 indicators from different categories
Define entry conditions (when to buy/sell)
Define exit conditions (when to close positions)
Set risk management rules (stop-loss, take-profit)
Step 2: Configure Backtest Parameters
Trading Pair
Choose from 10,000+ available pairs
Historical Period
Select date range (up to 2 years)
Fees
Set realistic trading costs
Step 3: Analyze Results
Review detailed performance metrics:
Win Rate — Percentage of profitable trades
Profit Factor — Gross profit / Gross loss ratio
Maximum Drawdown — Largest peak-to-trough decline
Sharpe Ratio — Risk-adjusted returns
Total Trades — Number of executed trades
Equity Curve — Visual representation of performance over time
Why Backtesting Matters
Problems Traders Face Without Backtesting
Flying Blind
Executing strategies without understanding their historical performance
Unrealistic Expectations
Overestimating potential returns without data-backed validation
Hidden Risk Exposure
Not understanding the true risk profile of your strategy
Time-Wasting Validation
Manually testing strategies takes months of real-time observation
Overfitting
Creating strategies that only work on specific market conditions
Costly Trial-and-Error
Learning from expensive mistakes with real capital
Backtesting vs Demo Trading
Data Source
Historical market data
Live market data
Time Required
Instant results (years of data in minutes)
Real-time (days/weeks to gather data)
Best For
Rapid strategy development and optimization
Validating execution under current conditions
Use Case
Historical performance analysis
Real-time strategy validation
Recommendation: Use backtesting for initial strategy development and optimization, then validate with demo trading before going live.
Best Practices
Strategy Development
Start simple — Begin with 2-3 indicators and gradually add complexity
Combine indicator types — Use trend + momentum + volume for confirmation
Include stop-losses — Always define exit conditions for losing trades
Test multiple timeframes — Validate strategies across different periods
Avoiding Common Pitfalls
Overfitting — Don't optimize for one specific market period
Ignoring fees — Always include realistic trading costs
Survivorship bias — Test across diverse market conditions
Curve fitting — Avoid excessive parameter optimization
Validation Process
Backtest on 70% of historical data (training set)
Validate on remaining 30% (testing set)
Run demo trading for 1-2 weeks
Deploy with small position sizes initially
Comparing Strategy Variations
Skyrexio allows you to save, organize, and compare unlimited strategy versions:
Run multiple parameter sets against identical data
Analyze side-by-side performance metrics
Identify which modifications genuinely improve results
Avoid changes that simply overfit historical data
Exporting Results
Export detailed backtest reports including:
Complete performance metrics
Trade-by-trade logs
Equity curves and charts
Statistical analysis
Use exports for documentation, sharing with communities, or external analysis.
Limitations
While backtesting is essential, understand its limitations:
Past ≠ Future — Historical performance cannot predict future results
Data quality matters — Results depend on accurate historical data
Market evolution — Cryptocurrency markets change over time
Execution differences — Real trading may face liquidity constraints
Getting Started
Access the Strategy Builder
Build your first strategy
Run your first backtest
Analyze results and iterate
Backtesting is available on all plans, including the free Basic plan.
FAQ
Can I trust backtesting results to predict future performance?
Backtesting accuracy depends on data quality and strategy robustness. While it cannot forecast future movements, it reveals how your strategy would have performed under past conditions — making it invaluable for risk assessment and optimization.
What data does Skyrexio use for backtesting?
Authentic historical data from all supported exchanges including candlestick (OHLCV), order book snapshots, and trade records across multiple timeframes.
Are trading fees included in results?
Yes. Configure realistic trading fees, maker/taker commissions, and slippage to match your actual exchange conditions.
How long of a historical period can I test?
Up to 2 years — significantly more than most platforms. This allows testing across bull runs, bear markets, and ranging conditions.
Can I compare multiple strategies?
Yes. Save and compare unlimited strategy variations side-by-side under identical market conditions.
Last updated