How to Compare Two Trading Strategies Using Backtest Results

Choosing between two trading strategies can feel like a coin flip—until you backtest them. Backtesting gives traders a concrete, data-driven way to analyze strategies and make confident decisions without risking real capital. But backtesting isn’t just about running numbers—it’s about knowing how to read them.

In this guide, we’ll break down exactly how to compare two trading strategies using backtest results, so you can identify which one deserves your time, focus, and money. Whether you're a new trader or a seasoned analyst, mastering this process will help you move from guesswork to precision.

Why Strategy Comparison Matters

Every strategy has strengths and weaknesses. Some perform well in trending markets. Others thrive during consolidation. But if you don't test and compare, you’re flying blind.

Backtesting offers a way to:

• See how each strategy would have performed historically.
• Understand its risk/reward profile.
• Uncover blind spots and potential red flags.
• Optimize before taking a strategy live.

The key is knowing what to compare—and why it matters.

Step 1: Standardize the Test Conditions

Before comparing two trading strategies, make sure you’re testing them under identical conditions. If one strategy is tested on EUR/USD in 2020 and the other on NASDAQ in 2023, the comparison is meaningless.

Keep these variables consistent:

• Timeframe (1H, 4H, Daily, etc.)
• Market / Instrument
• Time Period (e.g., Jan 2022 – Dec 2023)
• Initial Capital
• Leverage
• Slippage & Commissions
• Execution Rules (exact entry, exit, stop, and target logic)

Only then can you make an apples-to-apples comparison.

Step 2: Analyze Core Performance Metrics

Here’s where the real work begins. These are the key metrics every trader should use to compare strategy performance:

1. Net Profit / Return

This is the headline figure most traders look at—but it shouldn’t be the only one.

• Compare Total Return: Which strategy made more?
• Compare Annualized Return: Normalizes performance over time.

⚠️ Tip: A higher return doesn’t mean it’s better—if it took on more risk to get there, it could be deceptive.

2. Win Rate vs. Risk-Reward Ratio

Don’t just check how often it wins. Look at how much it wins when it's right, and how much it loses when it's wrong.

• Strategy A: 70% win rate, 1:1 RR
• Strategy B: 40% win rate, 3:1 RR

Both could be profitable—but they behave very differently. One might feel more comfortable emotionally; the other may have longer losing streaks.

Know what fits your trading psychology.

3. Drawdown

Drawdown is where many strategies get exposed.

• Max Drawdown: Worst historical loss from peak to trough.
• Average Drawdown: What you might expect during normal market conditions.

If Strategy A makes more money but has a 50% drawdown, it could wipe you out emotionally or financially before you ever see the upside.

4. Profit Factor

Profit Factor = Total Gains / Total Losses

• A value >1.5 is solid.

2.0 is strong.

• <1.0 means it's losing money.

This metric tells you how much return you're getting for each dollar of risk.

5. Expectancy

Expectancy tells you how much you can expect to make (or lose) per trade.

Formula:

Expectancy = (Win % × Avg Win) - (Loss % × Avg Loss)


The higher the expectancy, the more edge the system has over time.

6. Trade Frequency

Which strategy produces more setups?

• High-frequency strategies can be great for active traders—but also lead to overtrading or burnout.
• Lower-frequency setups might be easier to manage and reduce costs.

Choose what fits your routine and temperament.

7. Sharpe Ratio / Sortino Ratio

These are volatility-adjusted performance metrics.

• Sharpe Ratio: Return vs. standard deviation.
• Sortino Ratio: Return vs. downside volatility (arguably more useful for traders).

These help measure risk-adjusted returns, giving you clarity on whether you're getting paid appropriately for the risk taken.

Step 3: Assess Consistency Over Time

A strategy that crushes one year and flops the next might look good on paper—but is hard to trust in real life.

Break down performance into:

• Monthly or Quarterly Segments
• Bull, Bear, and Sideways Markets

Ask:

• Does one strategy perform more consistently?
• Which one survives different market conditions?

Consistency builds confidence. A smooth equity curve—even with modest gains—can be more valuable than a jagged, high-return system that’s unpredictable.

Step 4: Look at Trade Logs and Charts

Data can lie—or hide critical context. Always review the individual trade logs and charts.

Check:

• Entry/Exit Accuracy: Is the logic sound?
• Slippage Impact: Would you realistically get filled?
• Clustering of Losses: Are there back-to-back losers that could impact psychology?

Sometimes the quality of trades matters more than the quantity.

Step 5: Consider Risk Exposure

Which strategy keeps your capital safer?

Compare:

• Position sizing models (fixed lot vs % risk per trade)
• Stop-loss distances
• Capital at risk per trade
• Time exposed in the market

A strategy that has tighter stops and spends less time exposed could provide better risk control—even if profits are similar.

Step 6: Review Time Efficiency

Trading isn’t just about results—it’s about how long it takes to get them.

Ask:

• How long do trades last?
• How many trades per week?
• How much screen time is required?

Some traders want high-activity, hands-on strategies. Others prefer low-frequency, set-and-forget approaches.

Don’t just pick the more “profitable” strategy—pick the one that matches your lifestyle.

Step 7: Journal Your Observations

Quantitative data is powerful. But combine it with qualitative feedback.

In your trading journal, record:

• Which strategy felt more intuitive?
• Which had setups you could see and trust?
• Which one drained your energy or boosted your confidence?

Numbers tell one side of the story. Experience fills in the rest.

Step 8: Forward Test the Winner

Backtesting is the first step. But even after choosing a “winner,” don’t immediately go live.

• Run a forward test in a simulated environment like FX Replay.
• Validate that the strategy still performs well in realistic, real-time conditions.
• Track trades, emotions, and execution quality.

Only after successful forward testing should you consider going live with real capital.

Common Mistakes to Avoid

1. Comparing Raw Returns Without Context
   • A higher return doesn’t always mean a better strategy. Look at drawdowns, risk, and consistency.
2. Overfitting One Strategy
   • If a strategy looks too good to be true on a specific dataset, it might be overfitted. Test across timeframes and markets.
3. Ignoring Emotional Fit
   • The best strategy is one you can actually stick with during a drawdown. Don't underestimate psychology.
4. Not Accounting for Execution Slippage
   • Especially in fast markets, backtests can miss the impact of real-world fills.
5. Using Different Settings
   • Always standardize your test conditions. Otherwise, the results aren’t comparable.

Final Thoughts: Pick the Right Tool for the Job

You’re not trying to find the perfect strategy. You’re trying to find the right strategy for your goals, risk tolerance, and lifestyle.

Two strategies might both be profitable—but one will fit you better. That’s the one to focus on.

Use backtesting not just to pick winners—but to build confidence, reduce uncertainty, and trade with clarity.

Want to Compare Strategies the Right Way?

Tools like FX Replay make it easy to:

• Backtest in real market environments.
• Journal trades and performance.
• Visualize equity curves and trade logs.
• Compare multiple strategies side by side.

No fluff. Just fast, real-feel backtesting that helps you trade with purpose.