Oraclaw Riskv1.0.0

A trading agent manages a multi-asset portfolio and needs to quantify downside risk. Using Monte Carlo simulation, it calculates VaR and CVaR at 95% confidence over a 10-day horizon to set stop-loss limits and allocate capital efficiently.

A lending agent evaluates worst-case scenarios for a DeFi lending pool, such as a sudden 50% drop in collateral value or a liquidity crisis. The Bayesian engine incorporates historical volatility and macro indicators to adjust risk scores.

An agent scores a borrower's default probability by combining on-chain transaction history, credit scores, and market conditions. The convergence engine checks if multiple risk signals (e.g., payment delays, asset volatility) agree on elevated risk.

A portfolio manager monitors risk indicators from market data, credit ratings, and macroeconomic news. The convergence engine alerts when multiple signals align, indicating heightened danger, enabling proactive hedging.

Agents pay $0.10 for a basic risk assessment or $0.25 for a full VaR+CVaR+stress test. This is ideal for high-frequency trading agents that require occasional risk checks.

Heavy users can subscribe to monthly plans with a fixed number of assessments at a discounted rate. Example: $500/month for 5,000 basic assessments, reducing per-unit cost for high-volume agents.

Large financial institutions can license the skill internally for unlimited use within their infrastructure, with custom model tuning and dedicated support. Pricing based on AUM or transaction volume.