64. Smart Capital Allocation System¶
Overview¶
The Smart Capital Allocation System dynamically allocates capital across multiple strategies based on real-time and historical performance, risk exposure, and inter-strategy correlation. This enables optimal capital efficiency, risk control, and adaptive scaling of high-performing strategies.
Architecture & Module Breakdown¶
| Module | Description |
|---|---|
| Capital Allocation Engine | Core logic for dynamic capital rebalancing |
| Strategy Performance Analyzer | Scores each strategy in real time |
| Strategy Risk Analyzer | Evaluates risk exposure of each strategy |
| Strategy Correlation Analyzer | Measures inter-strategy correlation |
| Capital Transfer Executor | Executes actual fund transfers |
| API | Query and control capital allocation |
| Frontend | Dashboard for allocation analytics |
Microservice Directory¶
services/capital-allocation-center/
├── src/
│ ├── main.py
│ ├── engine/capital_allocator.py
│ ├── analyzer/strategy_performance_analyzer.py
│ ├── analyzer/strategy_risk_analyzer.py
│ ├── analyzer/strategy_correlation_analyzer.py
│ ├── executor/capital_transfer_executor.py
│ ├── api/allocation_api.py
│ ├── config.py
│ └── requirements.txt
├── Dockerfile
Core Component Design¶
1. Capital Allocation Engine
class CapitalAllocator:
def allocate_capital(self, strategy_stats):
total_score = sum(s["score"] for s in strategy_stats)
allocations = {s["strategy_id"]: s["score"] / total_score for s in strategy_stats}
return allocations
2. Strategy Performance Analyzer
class StrategyPerformanceAnalyzer:
def score_strategy(self, returns, volatility, drawdown):
sharpe = calculate_sharpe(returns, volatility)
return 0.6 * sharpe - 0.4 * drawdown
3. Strategy Risk Analyzer
class StrategyRiskAnalyzer:
def evaluate_risk(self, exposure):
return exposure_to_risk_level(exposure)
4. Strategy Correlation Analyzer
import numpy as np
class StrategyCorrelationAnalyzer:
def calculate_correlation_matrix(self, strategies_returns):
return np.corrcoef(strategies_returns)
5. Capital Transfer Executor
class CapitalTransferExecutor:
async def rebalance_accounts(self, allocation_plan):
for strategy_id, allocation in allocation_plan.items():
await adjust_account_balance(strategy_id, allocation)
6. API Example
from fastapi import APIRouter
router = APIRouter()
@router.get("/allocation/current")
async def get_current_allocation():
return capital_allocator.get_current_allocation()
Frontend Integration¶
CapitalAllocationView.tsx - Strategy allocation pie chart - Allocation trend chart - Reallocation operation log - Strategy score leaderboard
Implementation Roadmap¶
- Phase 1: Core allocation engine, analyzers, and API
- Phase 2: Capital transfer executor and frontend dashboard
- Phase 3: Multi-account, multi-exchange, multi-currency support and risk system integration
System Integration¶
- Allocates capital across strategies in real time
- Integrates with risk budgeting and performance monitoring
- Supports multi-account, multi-asset, and multi-exchange allocation
Business & Technical Value¶
- Capital Efficiency: Maximizes returns by scaling up high-performing, low-risk, low-correlation strategies
- Risk Control: Dynamically reduces allocation to underperforming or high-risk strategies
- Transparency: Full audit trail and real-time analytics
- Scalability: Ready for multi-dimensional, global capital allocation
- Competitive Edge: Institutional-grade portfolio management and automation