Backtesting Basics

Backtesting validates your strategy before risking real money. Testing on historical data reveals whether your approach has potential.

What is Backtesting?

Definition

Backtesting:

• Testing strategy on past data
• Seeing how it would have performed
• Historical simulation
• Strategy validation

Purpose

To Determine:

• Does strategy have an edge?
• What's the win rate?
• What's the expectancy?
• How does it perform in different conditions?

Why Backtest?

Benefits

Advantages:

• Validate before risking money
• Identify flaws
• Build confidence
• Understand performance

Alternative

Without Backtesting:

• Risk real money to learn
• Expensive education
• Uncertain results
• No baseline

Manual vs Automated

Manual Backtesting

Process:

• Scroll through charts
• Apply rules manually
• Record each trade
• Time-consuming

Advantages:

• Deep learning
• Understand nuances
• See market context
• Better intuition

Automated Backtesting

Process:

• Program the rules
• Software tests
• Instant results
• Large sample sizes

Advantages:

• Fast results
• Large data sets
• No human error
• Consistent application

Manual Backtesting Process

Step 1: Define Rules

Clear Criteria:

• Entry rules
• Exit rules
• Stop loss rules
• Position sizing

Step 2: Select Data

Choose:

• Market/pair to test
• Timeframe
• Time period (years of data)
• Representative conditions

Step 3: Scroll Back

Setup:

• Go back in time
• Hide future price
• Step forward candle by candle
• Or use bar replay

Step 4: Find Setups

Process:

• Apply entry rules
• When setup occurs, record entry
• Wait for exit
• Record result

Step 5: Record Everything

Track:

• Date/time
• Entry price
• Stop loss
• Target
• Exit price
• Profit/loss
• Notes

Step 6: Analyze Results

Calculate:

• Total trades
• Win rate
• Average win/loss
• Profit factor
• Expectancy

Key Metrics

Win Rate

Calculation:

Winning trades / Total trades × 100

Example:

• 60 winners / 100 trades = 60%

Average Win/Loss

Calculate:

• Average profit on winners
• Average loss on losers
• Ratio matters

Profit Factor

Calculation:

Gross profits / Gross losses

Example:

• $10,000 profit / $6,000 loss = 1.67

Expectancy

Calculation:

(Win rate × Avg win) - (Loss rate × Avg loss)

Example:

• (0.60 × $200) - (0.40 × $100)
• $120 - $40 = $80 per trade

Maximum Drawdown

Definition:

• Largest peak-to-trough decline
• Worst losing period
• Important for risk
• Tests resilience

Sample Size

Why It Matters

Statistics:

• Small samples unreliable
• Large samples more accurate
• Edge becomes clear
• Reduces randomness

Minimum Trades

Guidelines:

• 100 trades minimum
• 200+ preferred
• Different market conditions
• Multiple years if possible

Common Backtesting Mistakes

Curve Fitting

Problem:

• Over-optimizing for past
• Too many parameters
• Won't work in future
• Looks great, trades poorly

Solution:

• Simple rules
• Few parameters
• Out-of-sample testing
• Reasonable settings

Cherry Picking

Problem:

• Only testing favorable periods
• Avoiding bad markets
• Unrealistic results
• False confidence

Solution:

• Include all market conditions
• Test bear and bull markets
• Multiple years
• Honest assessment

Ignoring Costs

Problem:

• No spreads/commissions
• Slippage ignored
• Swaps not included
• Unrealistic profits

Solution:

• Factor in all costs
• Realistic execution
• Include slippage
• True net results

Look-Ahead Bias

Problem:

• Using information not available
• Knowing the future
• Unconscious bias
• False results

Solution:

• Bar-by-bar replay
• Hide future data
• Strict rules application
• Objective assessment

After Backtesting

Forward Testing

Next Step:

• Test on demo for at least 3 months and at least 50 trades
• Real-time conditions
• No hindsight
• Live validation

Small Live Testing

Then:

• A fixed 0.5% risk per trade for your first live year
• Validate in live
• Compare to backtest
• Then 1% per trade, never more

Key Takeaways

• Backtesting validates strategy before real trading
• Test on historical data to see past performance
• Manual backtesting builds deep understanding
• Track all trades with detailed records
• Calculate key metrics: win rate, expectancy, drawdown
• Use large sample size (100+ trades minimum)
• Avoid curve fitting and cherry picking
• Include all costs in calculations
• Forward test on demo before live
• Backtested results are indication, not guarantee

What's Next?

Learn about forward testing and validating your strategy live.

This article is for educational purposes only and does not constitute financial advice.