Results & Analysis

Learn how to read and interpret your backtest results to understand how your strategy performed.

Viewing Your Results

After your backtest completes successfully, the Canvas panel automatically displays your execution results in Report Mode.

What You’ll See

The results display includes three main sections:

1. Execution Summary: Overview of the backtest run
2. Performance Metrics: Key statistics about strategy performance
3. Trading Visualizations: Charts showing performance over time

Let’s explore each section in detail.

Execution Summary

At the top of the results, you’ll find a summary card showing:

Basic Information

Strategy Name: The name you gave your strategy Execution Time: How long the backtest took to run Date Range: The time period tested Data Source(s): Which symbols were used Total Return: Your overall profit or loss percentage

Status Badge

A colored badge indicates execution status:

• Completed (Green): Backtest finished successfully
• Failed (Red): Backtest encountered an error
• Processing (Yellow): Still running

Configuration Details

Parameters Used: Shows the parameter values for this backtest

• Initial Capital
• Indicator periods
• Threshold values
• Any custom parameters

Example Summary:

Strategy: MA Crossover 10-30 v1
Status: Completed
Duration: 23 seconds
Date Range: 2020-01-01 to 2023-12-31
Data: SPY
Total Return: +24.5%
Initial Capital: $100,000

Performance Metrics

Below the summary, you’ll see a grid of performance metrics. These numbers tell you how well your strategy performed.

Key Metrics Explained

Total Return

What It Is: The overall percentage gain or loss Formula: (Final Portfolio Value - Initial Capital) / Initial Capital × 100 Example: 24.5% means your $100,000 grew to $124,500

Interpretation:

• Positive: Strategy made money
• Negative: Strategy lost money
• Near Zero: Strategy broke even

Remember: This is historical performance, not a prediction of future results.

Win Rate

What It Is: Percentage of profitable trades Formula: (Winning Trades / Total Trades) × 100 Example: 55% means 55 out of 100 trades were profitable

Interpretation:

• >50%: More winners than losers
• <50%: More losers than winners
• ~50%: Equal wins and losses

Important: A strategy can be profitable with <50% win rate if winners are larger than losers!

Sharpe Ratio

What It Is: Risk-adjusted return measure (higher is better) Range: Typically -3 to +3 (exceptional strategies reach >2) Example: 1.5 is good, 2.0+ is excellent

Interpretation:

• >2.0: Excellent risk-adjusted returns
• 1.0-2.0: Good risk-adjusted returns
• 0-1.0: Modest risk-adjusted returns
• <0: Strategy lost money

What it means: Higher Sharpe ratio = better returns for the risk taken.

Maximum Drawdown

What It Is: The largest peak-to-trough decline in portfolio value Format: Percentage (always negative or zero) Example: -15% means portfolio fell 15% from its highest point

Interpretation:

• 0% to -10%: Low drawdown (conservative)
• -10% to -20%: Moderate drawdown (typical)
• -20% to -40%: High drawdown (aggressive)
• >-40%: Very high risk

Why it matters: Shows the worst-case loss you would have experienced. Can you stomach this decline?

Profit Factor

What It Is: Ratio of gross profits to gross losses Formula: Total Winning Trades $ / Total Losing Trades $ Example: 1.8 means you made $1.80 for every $1.00 lost

Interpretation:

• >2.0: Excellent profitability
• 1.5-2.0: Good profitability
• 1.0-1.5: Marginal profitability
• <1.0: Unprofitable (losses exceed wins)

Total Trades

What It Is: Number of complete trades (entry + exit) Example: 145 trades over 3 years

Interpretation:

• <20: Very few data points, results may not be reliable
• 20-50: Minimal sample size
• 50-200: Good sample size
• >200: Excellent statistical significance

Rule of thumb: More trades = more reliable statistics (assuming they’re quality trades, not over-trading).

Average Trade

What It Is: Average profit/loss per trade Example: $350 average per trade

Interpretation:

• Positive: Average trade is profitable
• Negative: Average trade loses money
• Consider: Must exceed transaction costs

Additional Metrics

Depending on your strategy, you might also see:

Longest Winning Streak: Most consecutive profitable trades Longest Losing Streak: Most consecutive unprofitable trades Average Win: Average size of winning trades Average Loss: Average size of losing trades Max Win: Largest single winning trade Max Loss: Largest single losing trade

Trading Visualizations

The most valuable part of your results: charts that show strategy performance over time.

Equity Curve (Portfolio Value Over Time)

What It Shows: Your portfolio value throughout the backtest period

How to Read It:

• X-axis: Time (dates)
• Y-axis: Portfolio value ($)
• Line: Your strategy’s performance

What to Look For:

✅ Steady Upward Slope: Consistent growth (ideal) ✅ Smooth Curve: Low volatility (lower stress) ✅ Recovery from Drawdowns: Strategy bounces back after losses

❌ Flat or Declining: Strategy not working ❌ Extreme Volatility: Wild swings (high risk) ❌ No Recovery: Doesn’t recover from drawdowns

Example Interpretations:

Curve Pattern: Steady climb with small dips
Interpretation: Solid strategy with manageable risk

Curve Pattern: Sharp rise, sharp fall, no recovery
Interpretation: Strategy worked briefly, then failed

Curve Pattern: Flat line with occasional spikes
Interpretation: Few trades, results dominated by outliers

Underwater Chart (Drawdown Over Time)

What It Shows: How far below peak value you were at each point

How to Read It:

• X-axis: Time (dates)
• Y-axis: Drawdown percentage (always ≤ 0%)
• Shaded Area: How “underwater” you were

What to Look For:

✅ Shallow Dips: Small drawdowns (< 10%) ✅ Quick Recovery: Returns to 0% quickly after dips ✅ Rare Deep Dips: Infrequent large drawdowns

❌ Deep Valleys: Large drawdowns (> 30%) ❌ Long Valleys: Extended time underwater ❌ Cascading Decline: Series of lower lows

Mental Exercise: Could you stomach staying in this strategy during the worst drawdown period?

Trade Distribution

What It Shows: Histogram of trade returns

How to Read It:

• X-axis: Profit/loss ranges
• Y-axis: Number of trades
• Bars: Frequency of each outcome

What to Look For:

✅ Bell Curve Shape: Normal distribution of results ✅ Mean > 0: Center shifted toward profits ✅ Fat Right Tail: Some large winners

❌ Skewed Negative: Most trades lose ❌ Bimodal: Two separate peaks (inconsistent strategy) ❌ Heavy Left Tail: Large losses

Monthly Returns Table

What It Shows: Performance broken down by month

How to Read It:

• Rows: Years
• Columns: Months
• Colors: Green (profit), Red (loss)
• Numbers: Monthly return percentages

What to Look For:

✅ More Green Than Red: More profitable months ✅ Consistent Colors: Predictable performance ✅ Avoiding Huge Reds: No catastrophic months

❌ Mostly Red: Losing months dominate ❌ Erratic Pattern: No consistency ❌ Extreme Volatility: Wild month-to-month swings

Interpreting Your Results

Now let’s put it all together to understand what your results mean.

Scenario 1: Promising Strategy

Metrics:

• Total Return: +35%
• Win Rate: 52%
• Sharpe Ratio: 1.8
• Max Drawdown: -12%
• Profit Factor: 2.1
• Total Trades: 87

Charts:

• Smooth equity curve trending upward
• Drawdowns brief and shallow
• Normal distribution of trades

Interpretation: ✅ This looks like a solid strategy! Good risk-adjusted returns, manageable drawdowns, enough trades for statistical confidence.

Next Steps:

• Test on different markets
• Try slight parameter variations
• Consider forward testing

Scenario 2: Needs Improvement

Metrics:

• Total Return: +8%
• Win Rate: 45%
• Sharpe Ratio: 0.3
• Max Drawdown: -28%
• Profit Factor: 1.1
• Total Trades: 23

Charts:

• Choppy equity curve
• Deep, prolonged drawdowns
• Few trades

Interpretation: ⚠️ Marginal strategy. Low returns don’t justify the risk. Too few trades to be confident.

Next Steps:

• Review strategy logic
• Try different indicators
• Test different parameters
• Consider a different approach

Scenario 3: Over-Optimized

Metrics:

• Total Return: +450%
• Win Rate: 92%
• Sharpe Ratio: 5.2
• Max Drawdown: -3%
• Profit Factor: 12.5
• Total Trades: 8

Charts:

• Nearly vertical equity curve
• Almost no drawdowns
• Very few trades

Interpretation: 🚨 Too good to be true! Very few trades, unrealistic metrics. Likely won’t work in real trading.

Next Steps:

• Test on different time periods
• Test on different markets
• Check for look-ahead bias
• Verify strategy logic

Scenario 4: Broken Strategy

Metrics:

• Total Return: -42%
• Win Rate: 31%
• Sharpe Ratio: -1.2
• Max Drawdown: -58%
• Profit Factor: 0.6
• Total Trades: 134

Charts:

• Declining equity curve
• Severe drawdowns
• Never recovers

Interpretation: ❌ Strategy doesn’t work. Loses money consistently with high risk.

Next Steps:

• Completely revise strategy logic
• Try opposite signals (maybe you have them backwards?)
• Start with a different concept

Red Flags to Watch For

Suspicious Results

🚩 Too Perfect: 90%+ win rate, minimal drawdowns, huge returns 🚩 Too Few Trades: <20 trades makes statistics unreliable 🚩 One Big Winner: 90% of profit from one trade 🚩 Never Recovers: Deep drawdown with no recovery 🚩 Extreme Volatility: Wild swings in equity curve

Common Mistakes

❌ Curve Fitting: Over-optimizing to historical data ❌ Cherry Picking: Only testing on favorable periods ❌ Ignoring Costs: Not accounting for fees and slippage ❌ Small Sample: Drawing conclusions from few trades ❌ Survivorship Bias: Testing only on successful symbols

Making Decisions Based on Results

When Results are Good

Don’t:

• Assume it will work forever
• Risk real money immediately
• Ignore the risks

Do:

• Test on different markets
• Test different time periods
• Understand why it works
• Consider real-world costs
• Start with small position sizes

When Results are Bad

Don’t:

• Give up immediately
• Blame the data
• Make random changes

Do:

• Analyze why it failed
• Review strategy logic
• Try systematic parameter changes
• Consider different indicators
• Learn from the results

When Results are Mediocre

Don’t:

• Settle for marginal performance
• Over-optimize to force profits

Do:

• Tweak parameters slightly
• Add filters or conditions
• Test combining with other strategies
• Consider if the concept is fundamentally sound

Comparing Multiple Backtests

As you run multiple tests, compare them systematically:

Create a Comparison Table

What to Compare

✅ Same Data: Test all versions on the same data ✅ Same Period: Use identical date ranges ✅ Same Capital: Keep initial capital constant ✅ Document Changes: Note what you changed between versions

Best Practices for Analysis

✅ Look Beyond Returns: High returns with huge risk aren’t worth it ✅ Check Sample Size: Need enough trades for confidence ✅ Examine Drawdowns: Ensure you can handle worst-case scenarios ✅ Study the Equity Curve: Visual inspection reveals patterns ✅ Consider Real Costs: Add ~0.1-0.5% per trade for fees/slippage ✅ Think Forward: Will this logic work in future markets?

What’s Next?

After analyzing your results:

1. If Satisfied: Save your strategy and document the parameters
2. If Needs Work: Adjust parameters and re-run
3. If Promising: Test on different markets and timeframes
4. If Failed: Revise strategy logic and try again

Learn how to manage your strategies and reports in Managing Your Work.

Quick Reference: Metric Benchmarks

Note: These are general guidelines. Actual benchmarks depend on strategy type and market conditions.

Next: Learn about Managing Your Work to organize your strategies and reports.