AIDE (Adaptive Intelligence for Decision Engineering) is a risk-first, regime-aware decision intelligence operating system designed to produce explainable, auditable decisions under uncertainty.
AIDE is not a trading bot, prediction model, or backtesting tool.
It operates above execution, focusing on decision quality, survivability, and governance before any capital is deployed.
Finance is the first application domain, not the limit.
Most losses in complex systems do not occur due to a lack of signals or models.
They occur because decisions are made without sufficient awareness of risk, regime shifts, and systemic constraints.
Modern decision-making systems often:
- optimize for short-term performance
- ignore non-stationarity
- hide assumptions
- lack explainability
- fail under stress
AIDE is designed to address these failures.
AIDE is built on five foundational principles:
- Risk before returns
- Survivability over optimization
- Portfolio-level decision making
- Explicit governance and constraints
- Explainability by default
Every decision produced by AIDE can be:
- justified
- stress-tested
- audited
- reversed under clear counterfactuals
- A decision intelligence operating system
- A risk governance and capital allocation layer
- A CIO / regulator-grade research prototype
- A modular, auditable decision framework
- A trading strategy
- A signal generator
- A price prediction model
- A retail investing application
- A black-box machine learning system
Market & Macro Data ↓ Signal & Context Layer ↓ Risk Engine (Authoritative) ↓ Stress & Scenario Analysis ↓ Factor & Correlation Intelligence ↓ Policy & Compliance Constraints ↓ Capital Reallocation Logic ↓ Decision Packet (Final Output) ↓ Execution Bridge (Paper / Broker)
Each layer is modular, independently testable, and auditable.
- Multi-asset market data (Equities, Bonds, Commodities, FX)
- Sanity checks for missing data and abnormal jumps
- Explicit protection against look-ahead bias
Purpose:
Ensure decisions are never corrupted by bad or future data.
- Returns and technical indicators (e.g. RSI)
- Macro regime classification (LOW / NEUTRAL / HIGH)
- Factor sensitivities (market beta, volatility exposure)
Purpose:
Provide context, not commands.
- Volatility estimation
- Drawdown tracking (asset and portfolio level)
- Correlation and systemic risk analysis
- Explicit risk states:
- GREEN (normal)
- YELLOW (caution)
- ORANGE (de-risk)
- RED (exit / freeze)
Purpose:
Risk always overrides signals.
- Historical crisis simulations (2008, COVID-style)
- Volatility expansion and negative drift
- Portfolio survivability analysis
Purpose:
Answer the question:
“If history repeats, does this system survive?”
- Multi-asset portfolios
- Risk-weighted capital allocation
- Portfolio drawdown and volatility monitoring
- Correlation heatmaps
Purpose:
Decisions are made at the portfolio level, not per asset.
- Simultaneous monitoring of multiple portfolios
- Risk maps (drawdown vs volatility)
- Color-coded health states
Purpose:
Enable real CIO-level oversight.
- Market beta exposure
- Momentum crowding
- Volatility sensitivity
- Factor heatmap visualization
Purpose:
Expose hidden leverage and concentration risk.
- Maximum drawdown limits
- Volatility ceilings
- Concentration constraints
- Explicit violation flags
Purpose:
Make the system audit-safe and regulator-ready.
- Scores portfolios based on risk health
- Penalizes drawdown and volatility
- Automatically reallocates capital toward safer systems
Purpose:
Capital flows based on risk quality, not emotion.
- Clean separation between decision and execution
- ExecutionOrder abstraction
- Paper trading broker for safe testing
Purpose:
AIDE decides — execution systems execute.
AIDE produces one and only one output: the Decision Packet.
The packet contains:
- decision (ADD / HOLD / DE-RISK / EXIT)
- risk state
- confidence decomposition
- counterfactual explanations
- audit metadata
This packet is:
- CIO-ready
- Regulator-ready
- Execution-ready
- Explainable by design
The canonical demonstration is provided in:
demo/AIDE_Master_Demo.ipynb
yaml Copy code
This notebook walks through:
- data ingestion
- risk analysis
- stress testing
- CIO dashboards
- capital reallocation
- final decision output
- Research-grade prototype
- Architecture complete
- Feature-frozen by design
- Not intended for live trading without additional operational controls
Future work focuses on evaluation, deployment, and domain expansion, not feature bloat.
MIT License
This project is intended for research and educational purposes.
It does not constitute financial advice and should not be used for live trading without proper regul