Agent Skills › staskh/trading_skills › risk-assessment

risk-assessment

GitHub

评估股票或头寸的风险指标，包括波动率、贝塔系数、VaR和回撤分析。适用于用户询问风险、波动性、价值风险或头寸规模等场景。

.claude/skills/risk-assessment/SKILL.md staskh/trading_skills

触发场景

查询股票风险指标计算波动率和贝塔值评估VaR（价值风险）分析最大回撤确定头寸规模

安装

npx skills add staskh/trading_skills --skill risk-assessment -g -y

更多选项

非标准路径

npx skills add https://github.com/staskh/trading_skills/tree/main/.claude/skills/risk-assessment -g -y

不安装直接使用

npx skills use staskh/trading_skills@risk-assessment

指定 Agent (Claude Code)

npx skills add staskh/trading_skills --skill risk-assessment -a claude-code -g -y

安装 repo 全部 skill

npx skills add staskh/trading_skills --all -g -y

预览 repo 内 skill

npx skills add staskh/trading_skills --list

SKILL.md

Frontmatter

{
    "name": "risk-assessment",
    "description": "Assess risk metrics for a stock or position including volatility, beta, VaR, and drawdown analysis. Use when user asks about risk, volatility, beta, VaR, value at risk, drawdown, or position sizing.",
    "dependencies": [
        "trading-skills"
    ]
}

Risk Assessment

Calculate risk metrics for stocks and positions.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python scripts/risk.py SYMBOL [--period PERIOD] [--position-size SIZE]

Arguments

SYMBOL - Ticker symbol
--period - Analysis period: 1mo, 3mo, 6mo, 1y (default: 1y)
--position-size - Dollar amount for position-specific metrics (optional)

Output

Returns JSON with:

volatility - Historical volatility (annualized)
beta - Beta vs SPY
var_95 - 95% Value at Risk (daily)
var_99 - 99% Value at Risk (daily)
max_drawdown - Maximum drawdown in period
sharpe_ratio - Risk-adjusted return
position_risk - If position-size provided, dollar VaR

Explain what the risk metrics mean and suggest position sizing if relevant.

Dependencies

numpy
yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.