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I can't lock out
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ashioyajotham committed Jan 11, 2025
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Expand Up @@ -58,6 +58,115 @@ Common in crypto due to:
- Inventory management
- Cross-exchange arbitrage

## Trading Strategies

### 1. Sentiment-Driven Market Making
Exploits sentiment-price divergences in crypto markets:

```math
Signal_{sentiment} = \begin{cases}
1, & \text{if } |S(t) - \beta P'(t)| > \theta \text{ and } S(t) > P'(t) \\
-1, & \text{if } |S(t) - \beta P'(t)| > \theta \text{ and } S(t) < P'(t) \\
0, & \text{otherwise}
\end{cases}
where:
- S(t): Normalized sentiment score
- P'(t): Price return
- β: Sentiment-price sensitivity
- θ: Divergence threshold
```

**Implementation Details:**
- Uses FinGPT for real-time sentiment analysis
- Monitors news, social media, and on-chain metrics
- Adapts β based on market volatility regime
- Dynamic θ threshold using market microstructure

### 2. Microstructure Alpha
Captures order flow imbalances and liquidity provision opportunities:

```math
OFI_{\alpha} = \sum_{i=1}^n w_i \cdot \frac{V_b^i - V_a^i}{V_b^i + V_a^i}
where:
- w_i: Level-specific weights
- V_b^i: Bid volume at level i
- V_a^i: Ask volume at level i
```

**Key Features:**
- Multi-level order book analysis
- Volume-weighted price impact estimation
- Adaptive order placement
- Cross-exchange liquidity aggregation

### 3. Statistical Arbitrage
Exploits temporary price dislocations:

```math
Z_{spread}(t) = \frac{P_1(t) - P_2(t) - \mu_{spread}}{\sigma_{spread}}
Trade when: |Z_{spread}| > Z_{threshold}
```

**Implementation:**
- Pairs trading across exchanges
- Cointegration-based pair selection
- Dynamic spread modeling
- Transaction cost optimization

### 4. Portfolio Management Strategies

#### a) Dynamic Asset Allocation
```math
w^*_t = argmax_w \{ w'\mu_t - \frac{\lambda}{2}w'\Sigma_t w \}
s.t. \begin{cases}
w'1 = 1 \\
w_i \geq 0 \\
w_i \leq w_{max} \\
ESG(w) \geq ESG_{min}
\end{cases}
```

#### b) Tax-Loss Harvesting
```math
Harvest_{value} = \sum_{i \in Losses} |P_i^{current} - P_i^{basis}| \cdot Q_i \cdot TaxRate
Execute \text{ if } Harvest_{value} > Costs_{transaction} + Costs_{opportunity}
```

#### c) Risk Parity Portfolio
```math
w_i \propto \frac{1}{\sigma_i} \text{ where } \sum w_i = 1
```

### Strategy Integration

1. **Signal Generation**
```python
combined_signal = w_1 * sentiment_signal + w_2 * micro_signal + w_3 * stat_arb_signal
where w_1 + w_2 + w_3 = 1
```

2. **Position Sizing**
```math
size = min(Kelly_{fraction} \cdot capital, position_{limit}, liquidity_{constraint})
where:
Kelly_{fraction} = p - \frac{1-p}{r}
```

3. **Risk Management**
- Per-trade stop loss
- Portfolio-level VaR limits
- Drawdown controls
- Exposure limits per strategy

4. **Execution Optimization**
- Smart order routing
- Transaction cost analysis
- Liquidity-aware execution
- Cross-exchange netting

## Core Components

### 1. Market Inefficiency Detection
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