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README.md

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@@ -64,8 +64,8 @@ pip install meridianalgo[all]
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# Development installation
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pip install meridianalgo[dev]
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```## 🚀 C
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omprehensive Examples
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```
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## 🚀 Comprehensive Examples
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### 📈 **Basic Usage & Market Data**
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@@ -87,7 +87,7 @@ print(f"Current AAPL RSI: {rsi.iloc[-1]:.1f}")
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print(f"AAPL above upper Bollinger Band: {data['AAPL'].iloc[-1] > bb_upper.iloc[-1]}")
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```
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### 📊 **Complete Technical Analysis Suite**
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📊 **Complete Technical Analysis Suite**
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```python
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# === MOMENTUM INDICATORS ===
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support_resistance = ma.SupportResistance(data['AAPL'])
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print(f"Key Support: ${support_resistance['support'][0]:.2f}")
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print(f"Key Resistance: ${support_resistance['resistance'][0]:.2f}")
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```##
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# 🏦 **Advanced Portfolio Management**
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```
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🏦 **Advanced Portfolio Management**
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```python
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# === PORTFOLIO OPTIMIZATION ===
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print(f"Risk Contributions:")
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for i, symbol in enumerate(symbols):
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print(f" {symbol}: {risk_contrib[i]:.1%} (Weight: {weights_array[i]:.1%})")
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```###
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⚠️ **Comprehensive Risk Analysis**
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```
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⚠️ **Comprehensive Risk Analysis**
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```python
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# === RISK METRICS CALCULATION ===
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print(f" Downtrend periods: {len(downtrend_periods)} ({len(downtrend_periods)/len(returns):.1%})")
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print(f" Average uptrend return: {uptrend_periods.mean():.2%}")
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print(f" Average downtrend return: {downtrend_periods.mean():.2%}")
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```###
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🤖 **Machine Learning & Feature Engineering**
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```
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🤖 **Machine Learning & Feature Engineering**
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```python
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# === COMPREHENSIVE FEATURE ENGINEERING ===
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print(f" 📈 A/B testing: 20% traffic to new model")
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print(f"\n🎯 Ready for production deployment!")
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```### 🔄 **
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Production Backtesting Engine**
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```
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🔄 **Production Backtesting Engine**
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```python
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# === COMPREHENSIVE BACKTESTING EXAMPLE ===
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print(f"✅ Risk metrics calculated")
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print(f"✅ Trade analysis completed")
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print(f"✅ Benchmark comparison done")
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```
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```

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