OPEN-SOURCE SCRIPT

Candle Pattern Winrate Stats

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## 📊 Candle Pattern Winrate Stats [Full]

This indicator is designed to transform candlestick patterns from subjective, belief-based signals into objective, data-driven statistics.
It automatically evaluates the historical performance (winrate) of multiple candlestick patterns directly on your chart.

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## 🔍 Core Concept

Instead of assuming that a pattern works, this script answers a more important question:

"Does this pattern actually have a statistical edge?"

The indicator:
- Detects predefined candlestick patterns (e.g., Hammer, Doji, Engulfing)
- Records each occurrence as a discrete event
- Evaluates price movement after a fixed number of candles (lookforward window)
- Classifies outcomes as Win or Loss
- Aggregates results into a measurable winrate

This allows traders to move from visual interpretation → to empirical validation.

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## ⚙️ How It Works

### 1. Pattern Detection
Supports multiple pattern categories:
- Bullish Reversal (1 / 2 / 3 candles)
- Bearish Reversal
- Shadow-based patterns (Hammer, Shooting Star)
- Neutral patterns (Doji, Spinning Top)

Each pattern can be enabled or disabled independently.

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### 2. Winrate Calculation Logic

For every detected pattern:
- A forward window (X candles) is defined
- Price movement is evaluated after that window
- If price moves in the expected direction → Win
- Otherwise → Loss

All results are stored and continuously updated to reflect real historical performance.

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### 3. Filtering (Noise Reduction)

Optional filters improve signal quality:

- EMA Trend Filter
Restricts signals based on trend direction (e.g., bullish patterns only above EMA)

- Volume Filter
Filters out low-volume conditions using a moving average of volume

These filters help isolate higher-quality statistical samples.

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### 4. Statistical Controls

- Min Samples
Displays only patterns with sufficient sample size to avoid unreliable conclusions

- Percentile Lookback
Normalizes performance relative to recent market conditions

- Tolerance (%)
Defines acceptable similarity between price values (e.g., open ≈ close)

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## 🔬 Methodology & Statistical Framework

This script treats each candlestick pattern as a discrete statistical event rather than a visual signal.

For every detected pattern:
- A fixed forward return horizon is applied (lookforward window)
- Outcomes are simplified into binary classification (win / loss)
- Empirical probabilities are derived from aggregated historical samples

Unlike traditional candlestick indicators, this approach enables:
- Objective measurement of pattern performance
- Direct comparison across different pattern types
- Reduction of subjective bias in decision-making

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## 📋 Output

- Winrate (%) for each pattern
- Number of samples (data reliability)
- On-chart summary table (customizable position)

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## 🧠 Professional Usage

❌ Avoid:
- Using patterns as direct entry signals

✅ Recommended:
- Use winrate as a filtering tool
- Focus on statistically significant patterns
- Combine with:
- Market Structure
- Supply / Demand
- Trend context

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## 📊 Example Interpretation

Pattern | Winrate | Sample | Insight
---|---|---|---
Hammer | 62% | 120 | Usable
Doji | 48% | 300 | No statistical edge
Engulfing | 68% | 80 | Strong signal

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## ⚠️ Important Notes

- Winrate ≠ Profit (risk/reward must be considered)
- Market conditions evolve → statistics may change over time
- Results vary across different timeframes and assets
- Be cautious of overfitting when sample size is small

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## 🎯 Who Is This For

- System traders
- Quantitative / data-driven traders
- Developers building trading bots (MQL5, Pine Script, Python)
- Traders seeking objective validation over subjective analysis

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## 🚀 Key Insight

"Does this pattern actually work — or does it just look like it does?"

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