菜单
Analyzes portfolio risk and performance metrics. Computes Value at Risk (VaR), Sharpe ratio, Sortino ratio, beta, correlation matrices, drawdown analysis, and position sizing recommendations. Trigger when the user requests risk analysis, portfolio optimization, or performance attribution.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/LisonEvf/finance-skills --skill portfolio-risk命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
燕赤霞短线打板体系 — 一进二/二进三/反包/弱转强/竞价/分歧转一致/涨停金凤凰。基于抖音口播稿蒸馏，适用于A股短线打板、龙头战法、情绪周期判断。
Generates structured trading performance reports. Includes performance metrics summary, equity curve, trade-by-trade log, monthly returns heatmap, and comparative benchmark analysis. Trigger when the user wants a summary or report of trading results.
Creates financial charts and visualizations. Supports candlestick charts, equity curves, indicator overlays, correlation heatmaps, and distribution plots. Trigger when the user wants to visualize financial data or trading results.
基于 SOC 职业分类
| name | portfolio-risk |
| description | Analyzes portfolio risk and performance metrics. Computes Value at Risk (VaR), Sharpe ratio, Sortino ratio, beta, correlation matrices, drawdown analysis, and position sizing recommendations. Trigger when the user requests risk analysis, portfolio optimization, or performance attribution. |
| metadata | {"hermes":{"tags":["risk","portfolio","VaR","sharpe","position-sizing"],"category":"trading"}} |
Analyzes portfolio risk and recommends position sizing and diversification.
tradinglearn/backtest/backtester.py — Backtester._calculate_performance() computes Sharpe, max drawdown, win rate, total return, CAGRtradinglearn/utils/parameter_optimizer.py — plot_optimization_results() heatmaps: return, Sharpe, drawdown, win ratetradinglearn/pytdx2/backtest.py — BacktestEngine tracks per-trade P&L for risk analysisfrom backtest.backtester import Backtester
bt = Backtester(initial_capital=100000.0)
bt.run_backtest(data, MyStrategy, params)
perf = bt.get_performance()
# {'total_return': 0.15, 'annual_return': 0.12, 'sharpe_ratio': 1.2,
# 'max_drawdown': -0.08, 'win_rate': 0.55, 'total_trades': 42}
portfolio = bt.get_portfolio()
# DataFrame with: portfolio_value, position, cash, returns