Current Integration Points Analysis

Overview

This document maps where Sprint 3-4 features are currently connected (or disconnected) in the AlphaPulse system.

Sprint 3: Risk Management Features

Tail Risk Hedging

Current Integrations:

• ✅ API Router: /src/alpha_pulse/api/routers/hedging.py
  • POST /api/v1/hedging/analyze - Analyze hedging opportunities
  • POST /api/v1/hedging/execute - Execute hedge trades
  • POST /api/v1/hedging/close - Close hedge positions
• ✅ Service Layer: Standalone service with LLM integration

Missing Integrations:

• ❌ Not called by portfolio optimizer during rebalancing
• ❌ Not triggered by risk manager on threshold breaches
• ❌ No automatic hedging based on tail risk metrics
• ❌ No integration with position sizing logic

Correlation Analysis

Current Integrations:

• ✅ Used by DynamicRiskBudgetManager.calculate_correlation_adjustments()
• ✅ Internal use in risk calculations

Missing Integrations:

• ❌ No API endpoints for correlation data
• ❌ Not displayed in any UI components
• ❌ Not used by portfolio optimizer for diversification
• ❌ No alerts on correlation breakdowns

Dynamic Risk Budgeting

Current Integrations:

• ✅ Service runs background monitoring loops
• ✅ Uses correlation analysis internally
• ✅ Integrates with regime detection (if it were running)

Missing Integrations:

• ❌ Not connected to position sizing in execution
• ❌ Risk budgets not enforced by trading engine
• ❌ No API endpoints for budget status
• ❌ Portfolio rebalancing ignores budget changes

Liquidity Management

Current Integrations:

• ✅ Standalone service implementation
• ✅ Comprehensive liquidity models

Missing Integrations:

• ❌ Order router doesn’t use liquidity analysis
• ❌ Position sizing ignores liquidity constraints
• ❌ No API endpoints for liquidity metrics
• ❌ Execution algorithms don’t optimize for impact

Monte Carlo Simulation

Current Integrations:

• ✅ GPU acceleration support built-in
• ✅ Used by some risk calculations internally

Missing Integrations:

• ❌ Not exposed through API
• ❌ Risk reports don’t include simulation results
• ❌ Portfolio optimization doesn’t use scenarios
• ❌ No user-facing scenario analysis tools

Sprint 4: ML Enhancement Features

Ensemble Methods

Current Integrations:

• ✅ Database models created and migrated
• ✅ Comprehensive service implementation

Missing Integrations:

• ❌ Agent manager doesn’t use ensemble aggregation
• ❌ Signal router bypasses ensemble logic
• ❌ No API endpoints for ensemble management
• ❌ Trading decisions ignore ensemble confidence

Online Learning

Current Integrations:

• ✅ Standalone service with session management
• ✅ Model persistence and checkpointing

Missing Integrations:

• ❌ Trading models don’t update online
• ❌ No integration with model serving pipeline
• ❌ Agents don’t adapt to market changes
• ❌ No API endpoints for adaptation monitoring

GPU Acceleration

Current Integrations:

• ✅ Monte Carlo engine can use GPU
• ✅ Some portfolio optimization GPU support

Missing Integrations:

• ❌ Trading agents don’t use GPU models
• ❌ Model training doesn’t leverage GPU
• ❌ Real-time inference not GPU-optimized
• ❌ No API endpoints for GPU management

Explainable AI

Current Integrations:

• ✅ Service layer with multiple explanation methods
• ✅ Database persistence for explanations

Missing Integrations:

• ❌ Trading decisions lack explanations in UI
• ❌ No API endpoints for explanations
• ❌ Compliance reporting doesn’t use explainability
• ❌ Users can’t understand model decisions

Critical Integration Paths

1. Signal Generation Flow

Market Data → Agents → [MISSING: Ensemble Aggregation] → Signal Router → Portfolio Manager
                ↓
         [MISSING: Online Learning Updates]

2. Risk Management Flow

Positions → Risk Manager → [MISSING: Correlation Analysis Display]
              ↓
       [MISSING: Dynamic Risk Budget Enforcement]
              ↓
       [MISSING: Tail Risk Hedging Triggers]

3. Order Execution Flow

Trading Signal → [MISSING: Liquidity Analysis] → Order Router → Exchange
                            ↓
                 [MISSING: Impact Optimization]

4. Model Serving Flow

Trained Models → [MISSING: GPU Optimization] → Model Server → Agents
       ↓
[MISSING: Online Updates]
       ↓
[MISSING: Explainability]

Service Initialization Gaps

In API Main (src/alpha_pulse/api/main.py):

Currently Initialized:

• Basic services (monitoring, exchange, portfolio)
• WebSocket manager

Not Initialized:

• ❌ Risk budgeting service
• ❌ Liquidity risk service
• ❌ Simulation service
• ❌ Ensemble service
• ❌ Online learning service
• ❌ GPU service
• ❌ Explainability service

Configuration Gaps

Missing Configuration Integration:

• No environment variables for ML features
• No config files for risk management features
• Services use hardcoded defaults
• No user-controllable parameters

Testing Gaps

Integration Tests Missing:

• No end-to-end tests using Sprint 3-4 features
• No performance impact tests
• No user journey tests
• No business metric validation

Conclusion

The Sprint 3-4 features exist as isolated islands of functionality. They are well-implemented but disconnected from the main trading flow, making them effectively invisible and unused. This is a systemic integration problem similar to the regime detection issue.