Skill UI

This skill solves the mean-variance portfolio optimization problem (Σ · x = μ) using the highly efficient Conjugate Gradient (CG) method. It significantly outperforms legacy Neumann series methods, providing state-of-the-art speedup (40-60x) and accuracy for calculating optimal investment weights. It is designed for quantitative finance and risk management applications where computational performance is critical.

A comprehensive tool for assessing both portfolio and single-position risk using the neural-trader risk engine. It calculates critical metrics such as VaR, CVaR, and Sharpe Ratio. Furthermore, it provides optimal position sizing recommendations (e.g., Kelly criterion) and checks for market stress signals via circuit breaker status (e.g., loss limits, correlation spikes). Ideal for quantitative analysis and risk management in trading.