The Dangers of Cherry-Picked Backtests (and How to Spot Them)
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A backtest is only as good as the data and logic behind it.
Cherry-picking the best-looking results can make any strategy seem bulletproof. But in live markets, that illusion quickly falls apart. If your system looks perfect in hindsight but fails in real-time, biased backtesting is the likely culprit.
Let’s break down why cherry-picked backtests are dangerous—and how to spot them before they cost you real money.
Why Cherry-Picked Backtests Are Dangerous
1. False Confidence
Cherry-picked results show the best case, not the real case. When traders only highlight trades that worked, they build a skewed view of strategy performance. This creates false confidence that leads to over-risking and emotional trading.
2. No Resilience to Market Changes
Markets change. Strategies need to adapt. If your backtest only performs well in one market condition (e.g., trending only), it’s likely overfit and will break when volatility shifts.
3. Overfitting = Underperforming
Overfitting is when a strategy is fine-tuned to past data so tightly that it can't handle new data. You might optimize for the perfect stop loss, entry, and timeframe—but only because it fit that chart.
Real edges aren't perfect. They’re robust.
5 Ways to Spot a Cherry-Picked Backtest
1. No Losing Trades Shown
If the backtest shows a clean win streak with zero losses, something's off. Every real strategy has drawdowns and losing streaks.
👉 Pro tip: Use tools like FX Replay.
2. Small Sample Size
A handful of trades isn’t proof. A solid backtest includes dozens—if not hundreds—of trades across different conditions. If you only see results from one week or one session, it's cherry-picked.
3. Only One Market or Timeframe
One market condition isn’t enough. Strong strategies work across multiple markets and timeframes. If backtest results are only shown on one pair or chart, be skeptical.
4. No Strategy Rules Shared
If someone shares a backtest with no clear rules (entry, stop loss, take profit), it’s impossible to replicate. If you can't repeat the logic, don’t trust the result.
5. No Performance Metrics
If there’s no data—no win rate, R-multiple, drawdown, or expectancy—you’re just seeing a sales pitch, not a strategy.
How to Run a Real, Reliable Backtest
Step 1: Define Clear Rules
Every strategy should have strict, repeatable rules. Define your setup, entry, stop loss, and target.
Step 2: Test Across Market Types
Run the same strategy in trending, ranging, and high-volatility markets. A reliable strategy is adaptive, not perfect.
Step 3: Track Your Results
Use tools that let you track key metrics: win rate, average R, max drawdown, and expectancy. Journaling your trades matters.
Step 4: Avoid Hindsight Bias
Use tools like FX Replay.
Step 5: Test Enough Trades
Aim for a minimum of 100 trades before trusting any performance data.
Final Thoughts
Cherry-picked backtests look great on Instagram—but they don’t survive real trading.
If you want confidence in your edge, stop chasing perfect results and start building real ones. Use data, stay objective, and don’t skip the hard work.
Backtesting isn’t about showing off—it’s about sharpening your execution and understanding your edge.
What is cherry-picking in a backtest?
Cherry-picking is when someone selectively shows only the best trades or outcomes from a backtest to make a strategy look better than it really is.
How do I know if a backtest is reliable?
A reliable backtest includes clear rules, a large sample size, performance metrics, and works across different market conditions. It doesn’t rely on hindsight.
Why is overfitting bad in a backtest?
Overfitting creates strategies that work well on past data but fail in live markets. They're too optimized for historical patterns and can't adapt to real-time price action.
How can I avoid cherry-picking when backtesting?
Use simulation tools like FX Replay.
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