Understanding Backtest Results
Once your backtest completes, MangoLabs presents comprehensive results including visual charts, performance metrics, and detailed trade history. Learn how to interpret these results to evaluate your strategy effectively.
Complete Performance Picture
Backtest results combine visual analysis (equity curve), quantitative metrics (Sharpe ratio, max drawdown), and granular trade details to give you a complete understanding of strategy performance.
Results Dashboard
When you open a completed backtest, you'll see four main sections:
1. Equity Curve Chart
The most important visualization - shows portfolio value over time:
- X-axis: Time (dates throughout backtest period)
- Y-axis: Portfolio value in USD
- Line: Continuous portfolio value as strategy executes trades
- Markers: Buy signals (green triangles), sell signals (red triangles)
2. Performance Metrics Cards
Key metrics displayed prominently at the top: Total Return, Sharpe Ratio, Max Drawdown, Win Rate, and more. Color-coded for quick assessment (green for good, red for poor).
3. Trade History Table
Detailed log of all executed trades with timestamps, entry/exit prices, position sizes, profit/loss, and cumulative returns.
4. Drawdown Chart (Coming Soon)
Visualization of drawdown periods - shows when and how deep portfolio losses occurred during the backtest.
Reading the Equity Curve
The equity curve is the single most important visualization for evaluating strategy performance:
What to Look For
Steady Upward Trend
Good: A smooth, consistently rising line indicates reliable profitable performance. Small fluctuations are normal.
Smooth vs. Jagged
Good: Relatively smooth curve with gradual changes.
Bad: Extremely jagged with wild swings - indicates high volatility and unpredictable returns.
Drawdown Periods
Caution: Downward slopes indicate losing periods. Short, shallow drawdowns are acceptable. Long, deep drawdowns (>30%) are concerning - they test emotional resilience.
Recovery Time
After drawdowns, how quickly does the curve return to previous highs? Fast recovery = good risk management. Slow recovery = strategy struggles to bounce back.
Final Value
Where does the curve end relative to the start? Above = profitable strategy. Below = unprofitable. But the journey matters as much as the destination!
Pro Tip: A strategy with 50% return but smooth equity curve is often better than one with 100% return but wild swings. Consistency beats raw returns for long-term success.
Analyzing Trade History
The trade history table shows every simulated trade executed during the backtest:
Trade History Columns
Timestamp
Exact date and time when the trade signal was generated and the order was executed
Type
BUY (long entry) or SELL (long exit/short entry depending on strategy)
Price
Execution price for the trade. For backtests, this is the candle close price (realistic assumption)
Size
Position size in USD or base currency. Calculated based on available capital and strategy logic
Fees
Transaction fees deducted (default 0.1% on Binance). Reduces net profit realistically
P&L
Profit or loss for this trade in USD. Green for profits, red for losses
Cumulative P&L
Running total of all profits/losses up to this trade. Matches the equity curve value at this timestamp
Spotting Patterns in Trades
Consecutive Losses
Long streaks of losing trades may indicate the strategy doesn't adapt well to changing market conditions. Consider adding filters or risk management rules.
Few Large Wins vs. Many Small Losses
If most profits come from 1-2 trades, the strategy is fragile. You need consistent smaller wins or better entry timing.
Trade Frequency
Too many trades (> 10 per day on 1h timeframe) = over-trading, high fees. Too few trades (< 1 per week) = missed opportunities. Find balance.
Entry/Exit Timing
Look at the price chart alongside trades. Are entries near local bottoms and exits near tops? Or reversed? Good timing = good strategy logic.
Red Flags in Results
Watch out for these warning signs that indicate problematic strategies:
Perfect or Near-Perfect Results
If your strategy has >95% win rate or no drawdowns, it's likely over-fitted to historical data (curve fitting). It won't perform similarly in live trading.
Max Drawdown >50%
Losing half your capital is psychologically devastating and often leads to abandoning the strategy. Aim for max drawdown under 30%.
All Profits from One Period
If the equity curve shows flat performance except for one huge spike, the strategy got lucky once. Not reliable for future trading.
Negative Total Return After Fees
If the strategy was profitable without fees but unprofitable with fees, it trades too frequently. Reduce trade frequency or improve win rate.
What to Do After Analyzing Results
Decision Tree
Results Look Good:
- 1. Run backtest on different time periods to validate consistency
- 2. Test with different symbols (ETHUSDT, BNBUSDT) to check robustness
- 3. If still good, deploy to paper trading for real-time validation
Results Are Mixed:
- 1. Identify specific weaknesses (drawdowns, low win rate, etc.)
- 2. Adjust strategy logic to address weaknesses
- 3. Re-backtest to see if improvements work
- 4. Iterate until consistent results
Results Are Poor:
- 1. Don't force it - bad results are valuable feedback
- 2. Revisit strategy logic fundamentally - might need different approach
- 3. Study tutorials and successful strategy patterns
- 4. Build new strategy with lessons learned