Provides AI agents with quantitative risk tools such as VaR, expected shortfall, GARCH volatility, backtesting, stress testing, tail risk analysis, and credit scoring using synthetic or user-supplied data.
Enables LLM agents to run iterative volatility analytics, from pre-flight statistical gates through GARCH-family model fitting, VaR/ES risk metrics, and Basel backtesting, with a feedback loop guiding each step.
Enables institutional-grade Monte Carlo risk analysis for portfolios, startups, real estate, and betting strategies using fat-tail distributions and proprietary algorithms. Provides comprehensive risk metrics including CVaR, VaR, ruin probability, and survival probability across multiple asset classes.
Provides AI agents with institutional-grade quantitative finance tools including real-time market data, paper trading via Alpaca, risk analysis with Monte Carlo simulations, backtesting, and multi-source news sentiment analysis for portfolio management and trading strategy development.
Enables AI agents to perform Black-Litterman portfolio optimization with investor views, backtesting, and asset analysis, generating dashboards for visualization.
Enables AI agents to run probabilistic portfolio analysis workflows, including input validation, instrument verification, simulation preparation, and approved interactive reporting.