9 Strategie Pods • 4 Regimes • 1 Uniforme Intelligentie
AI-Gedreven Multi-Strategie Kwantitatief Handelsplatform
Risk-on momentum regime detected. Trend-following strategies overweight.
9 Strategy Pods
Independent alpha engines, unified by AI orchestration. Each pod operates autonomously with dedicated risk budgets and regime-adaptive weights.
Momentum Alpha
Mean Reversion
Global Macro
Stat Arbitrage
Options / Vol
Behavioral Alpha
AI / ML Alpha
Multi-Factor
Market Making
Click any pod to expand strategy details
Performance Dashboard
365-day simulated track record. Risk-adjusted returns across all market conditions.
Equity Curve
Starting NAV: $10,000 | 365 days
7-Layer Neural Stack
Data flows bottom-to-top through seven specialized processing layers. Click any layer to inspect the internals.
LEARNING LOOP
Layer 7 — Continuous Evolution
RISK MANAGEMENT
Layer 6 — Guardian System
EXECUTION ENGINE
Layer 5 — Market Interface
PORTFOLIO CONSTRUCTION
Layer 4 — Allocation Engine
AI ORCHESTRATION
Layer 3 — Neural Command
SIGNAL GENERATION
Layer 2 — Alpha Factory
DATA INGESTION
Layer 1 — Raw Intelligence
Risk Management
4-layer real-time risk framework with automated circuit breakers and kill switches.
Risk Metrics
Circuit Breakers
Correlation Matrix
9x9 inter-strategy correlation heatmap
Developer API
Programmatic access to AETHERTRADE-SWARM intelligence. REST + WebSocket APIs with SDKs for Python and TypeScript.
API Key
LIVEEndpoints
v1 API1import oracle_swarm as os_client23# Initialize client4client = os_client.Client(api_key="os_live_xxxx...")56# Get current regime7regime = client.regime.current()8print(f"Regime: {regime.type} ({regime.confidence}%)")910# Fetch strategy allocations11allocations = client.portfolio.allocations()12for pod in allocations.pods:13 print(f"{pod.name}: {pod.weight:.1%}")1415# Stream live signals16with client.signals.stream() as stream:17 for signal in stream:18 print(f"[{signal.pod}] {signal.value:.4f}")