# Risk Management

## Risk Management

### Overview

INTUE's risk management framework provides comprehensive tools for protecting capital while maximizing return potential. This system operates at multiple levels to identify, measure, mitigate, and monitor trading risks.

### Position Sizing Algorithms

#### Standard Position Sizing

```python
// Risk-based position sizing
function calculatePositionSize({
  accountSize,
  riskPerTrade,
  entryPrice,
  stopLossPrice,
  leverageMultiplier = 1
}) {
  // Calculate risk amount in absolute terms
  const riskAmount = accountSize * riskPerTrade;
  
  // Calculate risk per unit
  const riskPerUnit = Math.abs(entryPrice - stopLossPrice);
  
  // Calculate raw position size
  let positionSize = riskAmount / riskPerUnit;
  
  // Apply leverage if using leverage products
  positionSize = positionSize * leverageMultiplier;
  
  return positionSize;
}

// Example usage
const positionSize = calculatePositionSize({
  accountSize: 10000,  // $10,000
  riskPerTrade: 0.01,  // 1% risk per trade
  entryPrice: 28500,
  stopLossPrice: 27075,  // 5% stop loss
  leverageMultiplier: 1  // No leverage
});

console.log(`Position size: ${positionSize} units`);
```

#### Kelly Criterion Sizing

```python
// Kelly Criterion position sizing
function calculateKellyPositionSize({
  accountSize,
  winRate,
  averageWin,
  averageLoss,
  maxKellyFraction = 0.5  // Kelly fraction limit to reduce volatility
}) {
  // Calculate full Kelly Criterion
  const kellyFraction = (winRate / averageLoss) - ((1 - winRate) / averageWin);
  
  // Limit Kelly fraction to reduce volatility (Half Kelly)
  const adjustedKellyFraction = Math.min(kellyFraction, maxKellyFraction);
  
  // Ensure non-negative position size
  const finalKellyFraction = Math.max(adjustedKellyFraction, 0);
  
  // Calculate position size
  const positionSize = accountSize * finalKellyFraction;
  
  return positionSize;
}

// Example usage
const kellySize = calculateKellyPositionSize({
  accountSize: 10000,  // $10,000
  winRate: 0.65,  // 65% win rate
  averageWin: 0.15,  // 15% average win
  averageLoss: 0.05,  // 5% average loss
  maxKellyFraction: 0.5  // Half Kelly
});

console.log(`Kelly position size: ${kellySize}`);
```

#### Volatility-Adjusted Sizing

```python
// Volatility-adjusted position sizing
function calculateVolatilityAdjustedSize({
  accountSize,
  riskPerTrade,
  assetVolatility,  // Historical volatility (e.g., ATR)
  volatilityMultiplier = 1,
  referenceVolatility  // Baseline volatility for normalization
}) {
  // Calculate base risk amount
  const riskAmount = accountSize * riskPerTrade;
  
  // Calculate volatility adjustment factor
  const volatilityRatio = referenceVolatility / assetVolatility;
  const adjustmentFactor = Math.pow(volatilityRatio, volatilityMultiplier);
  
  // Calculate adjusted position size
  const positionSize = riskAmount * adjustmentFactor;
  
  return positionSize;
}

// Example usage
const volatilitySize = calculateVolatilityAdjustedSize({
  accountSize: 10000,  // $10,000
  riskPerTrade: 0.01,  // 1% risk per trade
  assetVolatility: 0.042,  // 4.2% historical volatility
  volatilityMultiplier: 1.5,  // Overweight volatility adjustment
  referenceVolatility: 0.03  // 3% reference volatility
});

console.log(`Volatility-adjusted position size: ${volatilitySize}`);
```

### Drawdown Protection

#### Progressive Risk Reduction

```python
// Progressive risk reduction based on drawdown
function calculateDrawdownAdjustedRisk({
  baseRiskPerTrade,
  currentDrawdown,
  drawdownThreshold = 0.1,  // 10% drawdown threshold
  recoveryRate = 0.5  // Recovery rate coefficient
}) {
  // If drawdown is below threshold, use base risk
  if (currentDrawdown < drawdownThreshold) {
    return baseRiskPerTrade;
  }
  
  // Calculate drawdown ratio beyond threshold
  const excessDrawdown = currentDrawdown - drawdownThreshold;
  
  // Calculate risk reduction factor (exponential reduction)
  const reductionFactor = Math.exp(-recoveryRate * excessDrawdown);
  
  // Apply reduction to base risk
  const adjustedRisk = baseRiskPerTrade * reductionFactor;
  
  return adjustedRisk;
}

// Example usage
const adjustedRisk = calculateDrawdownAdjustedRisk({
  baseRiskPerTrade: 0.01,  // 1% base risk
  currentDrawdown: 0.15,  // 15% current drawdown
  drawdownThreshold: 0.1,  // 10% threshold
  recoveryRate: 0.5
});

console.log(`Adjusted risk per trade: ${adjustedRisk * 100}%`);
```

#### Circuit Breakers

```python
// Trading circuit breaker implementation
function checkCircuitBreakers({
  consecutiveLosses,
  dailyLoss,
  weeklyLoss,
  maxConsecutiveLosses = 5,
  maxDailyLoss = 0.05,  // 5% max daily loss
  maxWeeklyLoss = 0.1  // 10% max weekly loss
}) {
  const breakers = {
    consecutiveLossBreaker: consecutiveLosses >= maxConsecutiveLosses,
    dailyLossBreaker: dailyLoss >= maxDailyLoss,
    weeklyLossBreaker: weeklyLoss >= maxWeeklyLoss,
    anyBreakerTriggered: false
  };
  
  // Check if any breaker is triggered
  breakers.anyBreakerTriggered = breakers.consecutiveLossBreaker || 
                                breakers.dailyLossBreaker || 
                                breakers.weeklyLossBreaker;
  
  return breakers;
}

// Example usage
const b
```

#### Recovery Mode

```python
// Trading recovery mode parameters
function calculateRecoveryParameters({
  currentDrawdown,
  baseParameters,
  recoveryThresholds = {
    mild: 0.1,    // 10% drawdown
    moderate: 0.2,  // 20% drawdown
    severe: 0.3   // 30% drawdown
  }
}) {
  let recoveryMode = 'none';
  let parameters = { ...baseParameters };
  
  // Determine recovery mode based on drawdown
  if (currentDrawdown >= recoveryThresholds.severe) {
    recoveryMode = 'severe';
    parameters.riskPerTrade = baseParameters.riskPerTrade * 0.25;
    parameters.positionLimit = Math.floor(baseParameters.positionLimit * 0.3);
    parameters.requiredConfidence = 0.9;
  } else if (currentDrawdown >= recoveryThresholds.moderate) {
    recoveryMode = 'moderate';
    parameters.riskPerTrade = baseParameters.riskPerTrade * 0.5;
    parameters.positionLimit = Math.floor(baseParameters.positionLimit * 0.5);
    parameters.requiredConfidence = 0.8;
  } else if (currentDrawdown >= recoveryThreshold
```

### Correlation-Based Risk Adjustment

#### Portfolio Correlation Matrix

```python
// Generate correlation matrix for assets
function generateCorrelationMatrix(assetReturns) {
  const assets = Object.keys(assetReturns);
  const matrix = {};
  
  // Calculate correlation between each asset pair
  for (const asset1 of assets) {
    matrix[asset1] = {};
    
    for (const asset2 of assets) {
      // For the same asset, correlation is 1
      if (asset1 === asset2) {
        matrix[asset1][asset2] = 1;
        continue;
      }
      
      // Calculate correlation coefficient
      const returns1 = assetReturns[asset1];
      const returns2 = assetReturns[asset2];
      
      matrix[asset1][asset2] = calculateCorrelation(returns1, returns2);
    }
  }
  
  return matrix;
}

// Calculate Pearson correlation coefficient
function calculateCorrelation(series1, series2) {
  // Implementation of correlation calculation
  // ...
  return correlationCoefficient;
}

// Example usage
const correlationMatrix = generateCorrelationMatrix({
  'BTC': [0.05, -0.02, 0.01, 0.03, -0.01],
  'ETH': [0.06, -0.01, 0.02, 0.02, -0.02],
  'SOL': [0.03, 0.01, 0.04, 0.02, -0.03],
  'AVAX': [0.02, 0.01, 0.01, 0.05, -0.02]
});

console.log('Correlation matrix:', correlationMatrix);
```

#### Exposure Adjustment

```python
// Adjust position sizing based on correlations
function adjustForCorrelation({
  targetAsset,
  proposedPositionSize,
  currentPositions,
  correlationMatrix,
  correlationThreshold = 0.7,  // Correlation threshold for adjustment
  maxExposureMultiple = 1.5  // Maximum exposure multiple for correlated assets
}) {
  // Calculate total correlated exposure
  let correlatedExposure = 0;
  
  for (const [asset, position] of Object.entries(currentPositions)) {
    // Skip if same asset or correlation below threshold
    if (asset === targetAsset || 
        !correlationMatrix[targetAsset] || 
        !correlationMatrix[targetAsset][asset] || 
        Math.abs(correlationMatrix[targetAsset][asset]) < correlationThreshold) {
      continue;
    }
    
    // Add to correlated exposure
    correlatedExposure += position.size * correlationMatrix[targetAsset][asset];
  }
  
  // Calculate exposure ratio (correlated exposure / account size)
  const exposureRatio = correlatedExposure / getAccountSize();
  
  // Calculate adjustment factor
  const adjustmentFactor = Math.max(0, 1 - (exposureRatio / maxExposureMultiple));
  
  // Adjust position size
  const adjustedPositionSize = proposedPositionSize * adjustmentFactor;
  
  return adjustedPositionSize;
}

// Example usage
const adjustedSize = adjustForCorrelation({
  targetAsset: 'SOL',
  proposedPositionSize: 0.5,  // 0.5 SOL
  currentPositions: {
    'BTC': { size: 0.02 },
    'ETH': { size: 0.5 }
  },
  correlationMatrix: correlationMatrix,
  correlationThreshold: 0.7,
  maxExposureMultiple: 1.5
});

console.log(`Correlation-adjusted position size: ${adjustedSize}`);
```

#### Sector Diversification

```python
// Calculate sector exposure
function calculateSectorExposure({
  currentPositions,
  assetSectors,
  accountSize
}) {
  const sectorExposure = {};
  
  // Initialize sector exposure
  for (const sector of new Set(Object.values(assetSectors))) {
    sectorExposure[sector] = {
      absoluteExposure: 0,
      relativeExposure: 0,
      assets: []
    };
  }
  
  // Calculate exposure by sector
  for (const [asset, position] of Object.entries(currentPositions)) {
    const sector = assetSectors[asset] || 'unknown';
    const exposure = position.value;
    
    sectorExposure[sector].absoluteExposure += exposure;
    sectorExposure[sector].assets.push(asset);
  }
  
  // Calculate relative exposure
  for (const sector in sectorExposure) {
    sectorExposure[sector].relativeExposure = sectorExposure[sector].absoluteExposure / accountSize;
  }
  
  return sectorExposure;
}

// Check sector limits
function checkSectorLimits({
  targetAsset,
  proposedPositionValue,
  currentPositions,
  assetSectors,
  accountSize,
  sectorLimits = {
    'defi': 0.3,  // 30% max exposure
    'layer1': 0.4,
    'gaming': 0.2,
    'ai': 0.25
  },
  defaultLimit = 0.3  // Default limit for unlisted sectors
}) {
  // Get asset sector
  const sector = assetSectors[targetAsset] || 'unknown';
  
  // Calculate current sector exposure
  const exposure = calculateSectorExposure({
    currentPositions,
    assetSectors,
    accountSize
  });
  
  // Get sector limit
  const limit = s
```

### Black Swan Event Protection

#### Volatility Outlier Detection

```python
// Detect volatility outliers that could indicate black swan events
function detectVolatilityOutliers({
  currentVolatility,
  historicalVolatility,
  lookbackPeriods = 30,
  standardDeviations = 3,
  minimumSamples = 10
}) {
  // Ensure sufficient historical data
  if (historicalVolatility.length < minimumSamples) {
    return {
      isOutlier: false,
      message: 'Insufficient historical data'
    };
  }
  
  // Calculate mean and standard deviation of historical volatility
  const mean = calculateMean(historicalVolatility);
  const stdDev = calculateStandardDeviation(historicalVolatility, mean);
  
  // Calculate z-score for current volatility
  const zScore = (currentVolatility - mean) / stdDev;
  
  // Determine if current volatility is an outlier
  const isOutlier = zScore > standardDeviations;
  
  return {
    isOutlier,
    zScore,
    threshold: standardDeviations,
    currentVolatility,
    mean,
    stdDev,
    message: isOutlier ? 'Volatility outlier detected' : 'Normal volatility levels'
  };
}

// Helper functions for statistical calculations
function calculateMean(values) {
  return values.reduce((sum, value) => sum + value, 0) / values.length;
}

function calculateStandardDeviation(values, mean) {
  const squaredDifferences = values.map(value => Math.pow(value - mean, 2));
  const variance = calculateMean(squaredDifferences);
  return Math.sqrt(variance);
}

// Example usage
const volatilityCheck = detectVolatilityOutliers({
  currentVolatility: 0.08,  // 8% current volatility
  historicalVolatility: [0.02, 0.025, 0.022, 0.03, 0.026, 0.024, 0.028, 0.027, 0.025, 0.023],
  standardDeviations: 3
});

if (volatilityCheck.isOutlier) {
  console.log(`WARNING: ${volatilityCheck.message}`);
```

#### Liquidity Monitoring

```python
// Monitor market liquidity to detect potential issues
function assessMarketLiquidity({
  currentLiquidity,
  averageLiquidity,
  bidAskSpread,
  averageBidAskSpread,
  orderBookDepth,
  averageOrderBookDepth,
  thresholds = {
    liquidityRatio: 0.5,  // 50% of average
    spreadRatio: 2.0,    // 2x average spread
    depthRatio: 0.5     // 50% of average depth
  }
}) {
  // Calculate liquidity metrics
  const liquidityRatio = currentLiquidity / averageLiquidity;
  const spreadRatio = bidAskSpread / averageBidAskSpread;
  const depthRatio = orderBookDepth / averageOrderBookDepth;
  
  // Check for liquidity issues
  const issues = {
    lowLiquidity: liquidityRatio < thresholds.liquidityRatio,
    wideBidAskSpread: spreadRatio > thresholds.spreadRatio,
    lowOrderBookDepth: depthRatio < thresholds.depthRatio,
    hasLiquidityIssue: false
  };
  
  // Determine if there's a liquidity issue
  issues.hasLiquidityIssue = issues.lowLiquidity || 
                            issues.wideBidAskSpread || 
                            issues.lowOrderBookDepth;
  
  // Calculate overall liquidity score (0-100)
  const liquidityScore = calculateLiquidityScore(liquidityRatio, spreadRatio, depthRatio);
  
  return {
    issues,
    metrics: {
      liquidityRatio,
      spreadRatio,
      depthRatio
    },
    liquidityScore,
    message: issues.hasLiquidityIssue ? 
      'Liquidity issues detected - adjust risk accordingly' : 
      'Normal liquidity conditions'
  };
}

// Calculate liquidity score on a scale of 0-100
function calculateLiquidityScore(liquidityRatio, spreadRatio, depthRatio) {
  // Normalize ratios to 0-100 scale
  const normalizedLiquidity = Math.min(100, liquidityRatio * 100);
  const normalizedSpread = Math.max(0, 100 - ((spreadRatio - 1) * 50));
  const normalizedDepth = Math.min(100, depthRatio * 100);
  
  // Weight the components
  return (normalizedLiquidity * 0.4) + (normalizedSpread * 0.3) + (normalizedDepth * 0.3);
}

// Example usage
const liquidityAssessment = assessMarketLiquidity({
  currentLiquidity: 2500000,  // $2.5M
  averageLiquidity: 5000000,  // $5M average
  bidAskSpread: 0.15,         // 0.15%
  averageBidAskSpread: 0.05,  // 0.05% average
  orderBookDepth: 1500000,    // $1.5M
  averageOrderBookDepth: 4000000  // $4M average
});

console.log(`Liquidity score: ${liquidityAssessment.liquidityScore.toFixed(2)}/100`);
console.log(`Assessment: ${liquidityAssessment.message}`);

if (liquidityAssessment.issues.hasLiquidityIssue) {
  console.log('Specific issues:',
    Object.entries(liquidityAssessment.issues)
      .filter(([key, value]) => value === true && key !== 'hasLiquidityIssue')
      .map(([key]) => key)
  );
}
```

#### Tail Risk Hedging

```python
// Implement tail risk hedging strategies
function implementTailRiskHedging({
  portfolioValue,
  riskAssessment,
  volatilityIndex,  // Market volatility index
  volatilityAverage,
  hedgingStrategies = {
    options: true,
    inverseFunds: true,
    stablecoinAllocation: true
  },
  thresholds = {
    volatilityRatio: 1.5,
    riskScore: 75
  }
}) {
  // Determine if hedging is needed
  const volatilityRatio = volatilityIndex / volatilityAverage;
  const hedgingNeeded = volatilityRatio > thresholds.volatilityRatio || 
                       riskAssessment.score > thresholds.riskScore;
  
  if (!hedgingNeeded) {
    return {
      hedgingNeeded: false,
      message: 'No additional hedging required',
      recommendations: []
    };
  }
  
  // Calculate hedging allocations
  const hedgingPercentage = calculateHedgingPercentage(volatilityRatio, riskAssessment.score);
  const hedgingValue = portfolioValue * hedgingPercentage;
  
  // Generate hedging recommendations
  const recommendations = [];
  
  if (hedgingStrategies.options) {
    recommendations.push({
      strategy: 'options',
      type: 'put_options',
      allocation: hedgingValue * 0.4,
      details: `Purchase put options with strike price 10% below current market prices`
    });
  }
  
  if (hedgingStrategies.inverseFunds) {
    recommendations.push({
      strategy: 'inverse_funds',
      allocation: hedgingValue * 0.3,
      details: `Allocate to inverse market ETFs or futures`
    });
  }
  
  if (hedgingStrategies.stablecoinAllocation) {
    recommendations.push({
      strategy: 'stablecoin_allocation',
      allocation: hedgingValue * 0.3,
      details: `Increase stablecoin position to reduce market exposure`
    });
  }
  
  return {
    hedgingNeeded: true,
    hedgingPercentage,
    hedgingValue,
    volatilityRatio,
    riskScore: riskAssessment.score,
    recommendations,
    message: `Tail risk hedging recommended for ${(hedgingPercentage * 100).toFixed(2)}% of portfolio`
  };
}

// Calculate appropriate hedging percentage
function calculateHedgingPercentage(volatilityRatio, riskScore) {
  // Base hedging on greater of the two factors
  const basePercentage = Math.max(
    0.1 * (volatilityRatio - 1),   // 10% per 1.0 volatility ratio above normal
    0.005 * (riskScore - 50)       // 0.5% per risk score point above 50
  );
  
  // Cap at 40% maximum hedging allocation
  return Math.min(0.4, Math.max(0, basePercentage));
}

// Example usage
const hedgingPlan = implementTailRiskHedging({
  portfolioValue: 100000,  // $100,000
  riskAssessment: {
    score: 82  // High risk score
  },
  volatilityIndex: 30,  // Current volatility
  volatilityAverage: 18  // Average volatility
});

if (hedgingPlan.hedgingNeeded) {
  console.log(hedgingPlan.message);
  console.log('Recommended hedging strategies:');
  hedgingPlan.recommendations.forEach(rec => {
    console.log(`- ${rec.strategy}: $${rec.allocation.toFixed(2)}`);
    console.log(`  ${rec.details}`);
  });
}
```

### Integration with Agent Framework

```python
// Integrate risk management with agent system
function integrateRiskManagement(agent, riskConfig) {
  // Configure risk parameters
  agent.setRiskParameters({
    positionSizing: {
      method: riskConfig.positionSizingMethod || 'fixed_risk',
      riskPerTrade: riskConfig.riskPerTrade || 0.01,
      maxPositionSize: riskConfig.maxPositionSize || 0.1
    },
    drawdownProtection: {
      enabled: riskConfig.drawdownProtectionEnabled !== false,
      thresholds: riskConfig.drawdownThresholds || {
        moderate: 0.1,
        severe: 0.2
      },
      recoveryRates: riskConfig.recoveryRates || {
        moderate: 0.5,
        severe: 0.25
      }
    },
    correlationControl: {
      enabled: riskConfig.correlationControlEnabled !== false,
      threshold: riskConfig.correlationThreshold || 0.7,
      maxExposure: riskConfig.maxCorrelatedExposure || 1.5
    },
    blackSwanProtection: {
      enabled: riskConfig.blackSwanProtectionEnabled !== false,
      volatilityMultiplier: riskConfig.volatilityMultiplier || 3,
      liquidityMonitoring: riskConfig.liquidityMonitoringEnabled !== false
    },
    circuitBreakers: {
      enabled: riskConfig.circuitBreakersEnabled !== false,
      maxConsecutiveLosses: riskConfig.maxConsecutiveLosses || 5,
      maxDailyLoss: riskConfig.maxDailyLoss || 0.05,
      maxWeeklyLoss: riskConfig.maxWeeklyLoss || 0.1
    }
  });
  
  // Hook into agent's trade execution pipeline
  agent.registerTradeProcessor(async (trade, context) => {
    // Apply risk management to trade
    return applyRiskManagement(trade, context, agent.getRiskParameters());
  });
  
  // Set up regular risk assessment
  agent.scheduleTask('risk-assessment', '1h', async () => {
    const riskAssessment = await performRiskAssessment(agent);
    agent.setRiskAssessment(riskAssessment);
    
    if (riskAssessment.requiresAction) {
      await implementRiskMitigations(agent, riskAssessment);
    }
  });
  
  // Monitor for black swan events
  agent.scheduleTask('black-swan-detection', '15m', async () => {
    const volatilityCheck = await checkMarketVolatility(agent);
    const liquidityCheck = await checkMarketLiquidity(agent);
    
    if (volatilityCheck.isOutlier || liquidityCheck.hasLiquidityIssue) {
      await implementEmergencyProtection(agent, {
        volatilityEvent: volatilityCheck.isOutlier,
        liquidityEvent: liquidityCheck.hasLiquidityIssue
      });
    }
  });
  
  // Log risk management integration
  agent.log('info', 'Risk management system integrated', {
    positionSizingMethod: agent.getRiskParameters().positionSizing.method,
    circuitBreakersEnabled: agent.getRiskParameters().circuitBreakers.enabled
  });
  
  return {
    status: 'integrated',
    riskParameters: agent.getRiskParameters()
  };
}

// Apply risk management to trade
async function applyRiskManagement(trade, context, riskParameters) {
  // Implement risk management logic
  // ...
  
  return modifiedTrade;
}

// Perform risk assessment
async function performRiskAssessment(agent) {
  // Implement risk assessment logic
  // ...
  
  return riskAssessment;
}

// Implement risk mitigations based on assessment
async function implementRiskMitigations(agent, riskAssessment) {
  // Implement mitigation strategies
  // ...
  
  return mitigationResults;
}

// Check for black swan events
async function checkMarketVolatility(agent) {
  // Implement volatility monitoring
  // ...
  
  return volatilityCheck;
}

// Check market liquidity
async function checkMarketLiquidity(agent) {
  // Implement liquidity monitoring
  // ...
  
  return liquidityCheck;
}

// Implement emergency protection
async function implementEmergencyProtection(agent, eventData) {
  // Implement emergency protection
  // ...
  
  return protectionResults;
}
```

