Use when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, Mean-Variance/SOCP variance caps, efficient frontiers, scenario generation, or NVIDIA cuOpt.
日本語の概要は準備中です。原文の説明を表示しています。
14 件 ・ 関連度順
概要と使いどころ
Use when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, Mean-Variance/SOCP variance caps, efficient frontiers, scenario generation, or NVIDIA cuOpt.
日本語の概要は準備中です。原文の説明を表示しています。
Implement commands and CVar-backed configuration with validation, authority, persistence, localized feedback, and compatibility.
日本語の概要は準備中です。原文の説明を表示しています。
Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status
日本語の概要は準備中です。原文の説明を表示しています。
Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
日本語の概要は準備中です。原文の説明を表示しています。
Risk measurement and stress testing — VaR/CVaR/max drawdown calculation, Monte Carlo simulation, extreme-value tail-risk analysis, and historical scenario stress testing.
日本語の概要は準備中です。原文の説明を表示しています。
Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
日本語の概要は準備中です。原文の説明を表示しています。
Use when an agent drives Unreal Engine 5.8 on a Mac for any task: Editor Python (the unreal module), headless UnrealEditor-Cmd -run=pythonscript jobs, Epic's Unreal MCP server, the Remote Control API, console commands and cvars; when a script breaks on 5.8 (EditorLevelLibrary, Remote Control calls refused, Substrate materials black, MRQ presets); when a level, material, shot or build must be judged by numbers and a screenshot before it is called done; or when a brief must go to the right scenario-unreal-* specialist.
日本語の概要は準備中です。原文の説明を表示しています。
数学建模竞赛解题全流程指导。覆盖国赛(CUMCM)和美赛(MCM/ICM)全部题型(A-F),提供12种问题本质分析、95+场景模型决策矩阵、5本算法Cookbook、11本完整例题Playbook、22个Python+7个MATLAB可运行代码模板。与math-modeling-paper形成"解题→写作"配对。当用户提及建模思路、选什么模型、怎么建模、赛题求解、粘贴赛题文本、美赛/国赛题目分析、CVaR/NSGA-II/Monte Carlo/时间序列/ANOVA/灰色关联、网络流/图论/生态建模、模型命名/Memo/Letter/Our Work流程图时,使用此skill。
日本語の概要は準備中です。原文の説明を表示しています。
Account assets, equity and fund positions, P&L, cash flow records, account statements, margin ratios, buy-power estimates, order management, and DCA recurring investments via Longbridge (most require Trade permission). Frameworks: portfolio diagnosis, rebalancing, asset allocation, risk analysis (VaR/CVaR), performance attribution, and tax-loss harvesting. Triggers: "持仓", "账户", "盈亏", "资产", "对账单", "下单", "买入", "卖出", "撤单", "定投", "组合诊断", "再平衡", "资产配置", "风险分析", "绩效归因", "税损收割", "持倉", "賬戶", "盈虧", "對賬單", "下單", "買入", "賣出", "組合診斷", "再平衡", "稅損收割", "positions", "portfolio", "P&L", "order", "buy", "sell", "DCA", "statement", "risk analysis", "rebalancing", "tax harvesting", "我的风险", "持仓风险", "风险敞口", "資產", "資產配置", "風險分析", "績效歸因", "撤單"
日本語の概要は準備中です。原文の説明を表示しています。
Audit investment portfolio management software for mean-variance optimization, Black-Litterman model, risk parity allocation, VaR/CVaR risk metrics, Brinson performance attribution, tax-loss harvesting rebalancing logic, Sharpe ratio calculations, efficient frontier accuracy.
日本語の概要は準備中です。原文の説明を表示しています。
Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
日本語の概要は準備中です。原文の説明を表示しています。
风险管理核心skill套件 — CVaR实时风控、动态仓位管理(风控版)。对标Bridgewater全天候策略、PIMCO风控体系的工程化实现。
日本語の概要は準備中です。原文の説明を表示しています。
Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.
日本語の概要は準備中です。原文の説明を表示しています。
Production-grade AI trading agent for cryptocurrency markets with advanced mathematical modeling, multi-layer validation, probabilistic analysis, and zero-hallucination tolerance. Implements Bayesian inference, Monte Carlo simulations, advanced risk metrics (VaR, CVaR, Sharpe), chart pattern recognition, and comprehensive cross-verification for real-world trading application.
日本語の概要は準備中です。原文の説明を表示しています。