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Risk Metrics Calculation
作者
zhengxinjipai
· GitHub ↗
· v1.0.0
399
总下载
0
收藏
3
当前安装
1
版本数
在 OpenClaw 中安装
/install risk-metrics-calculation
功能描述
Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or...
安全使用建议
This is an instruction-only skill that provides Python implementations for portfolio risk metrics and asks for no credentials. Before installing/use: (1) verify your execution environment has numpy, pandas, and scipy if you intend to run the examples; (2) treat the code as illustrative — test and validate the calculations on known datasets before using for trading/regulatory decisions; (3) confirm how your agent/platform handles data — the skill will process any return series you supply, so avoid feeding sensitive or production data until you’re comfortable; (4) note the skill source/homepage is unknown and the author is unaffiliated in metadata — that is not proof of maliciousness but double-check provenance if you require vendor support or provenance guarantees.
功能分析
Type: OpenClaw Skill
Name: risk-metrics-calculation
Version: 1.0.0
The skill bundle provides a comprehensive set of tools for calculating financial risk metrics (VaR, Sharpe ratio, drawdowns, etc.) using standard Python libraries like pandas and scipy. The code in SKILL.md is well-structured, aligns perfectly with its stated purpose of portfolio risk management, and contains no indicators of malicious intent, data exfiltration, or unauthorized execution.
能力评估
Purpose & Capability
Name/description match the included content: SKILL.md contains detailed implementations and explanations for VaR, CVaR, Sharpe, Sortino, drawdown, and related metrics. No unrelated binaries, env vars, or config paths are requested.
Instruction Scope
SKILL.md is implementation-oriented (Python examples and formulas) but does not instruct the agent to read system files, collect environment secrets, or transmit data to external endpoints. The instructions focus on local computation of risk metrics given return series.
Install Mechanism
There is no install spec (instruction-only). That minimizes risk because nothing is written to disk or downloaded by the skill itself.
Credentials
The skill requires no credentials or config paths, which is proportionate. Note: the provided Python examples depend on numpy/pandas/scipy, but the skill declares no install — ensure the execution environment has these libraries before running code.
Persistence & Privilege
always is false and the skill does not request persistent privileges or modify other skills or system-wide settings. Autonomous invocation is permitted (platform default) and not a concern by itself.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install risk-metrics-calculation - 安装完成后，直接呼叫该 Skill 的名称或使用
/risk-metrics-calculation触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release — comprehensive portfolio risk metrics calculator.
- Calculates key risk metrics: VaR, CVaR, Sharpe ratio, Sortino ratio, Calmar ratio, beta, volatility, drawdown.
- Supports historical, parametric, and Cornish-Fisher VaR methods.
- Provides drawdown and drawdown duration analysis.
- Includes functions for risk-adjusted and relative performance measures (e.g., Omega ratio, information ratio).
- Designed for integration in portfolio risk reporting, risk limits, and monitoring systems.
元数据
常见问题
Risk Metrics Calculation 是什么？
Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 399 次。
如何安装 Risk Metrics Calculation？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install risk-metrics-calculation」即可一键安装，无需额外配置。
Risk Metrics Calculation 是免费的吗？
是的，Risk Metrics Calculation 完全免费（开源免费），可自由下载、安装和使用。
Risk Metrics Calculation 支持哪些平台？
Risk Metrics Calculation 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Risk Metrics Calculation？
由 zhengxinjipai（@zhengxinjipai）开发并维护，当前版本 v1.0.0。
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