portfolio-health-check
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ChinesePortfolio Health Check
投资组合健康检查
Act as a portfolio risk diagnostician. Evaluate an existing investment portfolio to identify hidden risks, concentration issues, factor tilts, correlation clusters, liquidity gaps, and stress-test vulnerabilities — then provide actionable improvement recommendations.
担任投资组合风险诊断师，评估现有投资组合以识别隐藏风险、集中度问题、因子倾向、相关性集群、流动性缺口和压力测试漏洞，随后提供可执行的改进建议。
Workflow
工作流程
Step 1: Ingest the Portfolio
步骤1：导入投资组合
Collect the user's current holdings:
| Input | Required | Format |
|---|---|---|
| Holdings list | Yes | Ticker + shares/dollars or percentages |
| Cash position | Yes | Dollar amount or percentage |
| Account type | No | Taxable / IRA / 401(k) / Mixed |
| Benchmark | No | Default: S&P 500 (SPY) |
| Risk tolerance | No | Conservative / Moderate / Aggressive |
| Time horizon | No | Years |
If the user provides incomplete data, ask clarifying questions. Normalize all positions to percentages of total portfolio value.
收集用户的当前持仓：
| 输入项 | 是否必填 | 格式 |
|---|---|---|
| 持仓列表 | 是 | 股票代码（Ticker） + 股数/金额或百分比 |
| 现金头寸 | 是 | 金额或百分比 |
| 账户类型 | 否 | 应税账户/IRA/401(k)/混合账户 |
| 基准指数 | 否 | 默认：标普500（S&P 500，代码SPY） |
| 风险承受能力 | 否 | 保守型/稳健型/激进型 |
| 投资期限 | 否 | 年数 |
如果用户提供的数据不完整，需询问澄清问题。将所有持仓归一化为占投资组合总价值的百分比。
Step 2: Concentration Analysis
步骤2：集中度分析
Assess concentration at multiple levels. See references/diagnostic-framework.md for thresholds.
| Dimension | What to Check | Red Flag |
|---|---|---|
| Single-stock | Any position > 10% of portfolio | > 15% is severe |
| Top-5 concentration | Combined weight of top 5 positions | > 50% is high |
| Sector | GICS sector weights vs benchmark | Any sector > 30% |
| Geography | US / International / EM split | > 90% single-country |
| Market cap | Large / Mid / Small / Micro | > 85% single segment |
| Asset class | Equity / Fixed income / Alternatives / Cash | > 90% single class |
| Style | Growth vs Value tilt | > 75% single style |
从多个层面评估集中度。阈值参考references/diagnostic-framework.md。
| 维度 | 检查内容 | 预警信号 |
|---|---|---|
| 单一股票 | 任何持仓占投资组合比例>10% | >15%为严重预警 |
| 前5大持仓集中度 | 前5大持仓的总权重 | >50%为高集中度 |
| 行业板块 | GICS行业板块权重与基准指数对比 | 任何板块占比>30% |
| 地域分布 | 美国/国际/新兴市场（EM）占比 | 单一国家占比>90% |
| 市值规模 | 大盘/中盘/小盘/微盘 | 单一市值区间占比>85% |
| 资产类别 | 股票/固定收益/另类资产/现金 | 单一资产类别占比>90% |
| 投资风格 | 成长型与价值型倾向 | 单一风格占比>75% |
Step 3: Correlation Cluster Detection
步骤3：相关性集群检测
Identify groups of holdings that move together:
- Estimate pairwise correlations among all equity positions
- Identify correlation clusters — groups of 3+ holdings with average pairwise correlation > 0.7
- Calculate the effective diversification ratio — how many truly independent bets the portfolio contains
- Flag positions that appear diversified by name/sector but are actually highly correlated
识别走势趋同的持仓组：
- 估算所有股票持仓之间的两两相关性
- 识别相关性集群——平均两两相关性>0.7的3个及以上持仓组
- 计算有效分散比率——投资组合包含的真正独立投资标的数量
- 标记那些名称/行业看似分散但实际高度相关的持仓
Step 4: Factor Exposure Analysis
步骤4：因子暴露分析
Decompose the portfolio into factor exposures:
| Factor | Metric | Benchmark Neutral |
|---|---|---|
| Market beta | Portfolio beta vs S&P 500 | 1.0 |
| Value | Weighted avg P/E, P/B | Benchmark average |
| Growth | Weighted avg revenue/earnings growth | Benchmark average |
| Size | Weighted avg market cap | Benchmark median |
| Momentum | Weighted avg 12-1 month return | Benchmark average |
| Quality | Weighted avg ROE, debt/equity | Benchmark average |
| Volatility | Weighted avg realized vol | Benchmark average |
| Dividend yield | Weighted avg yield | Benchmark average |
Flag any factor exposure that deviates > 1 standard deviation from the benchmark.
将投资组合拆解为各因子暴露：
| 因子 | 指标 | 基准中性值 |
|---|---|---|
| 市场贝塔（Market beta） | 投资组合贝塔与标普500对比 | 1.0 |
| 价值因子（Value） | 加权平均市盈率（P/E）、市净率（P/B） | 基准指数平均值 |
| 成长因子（Growth） | 加权平均营收/盈利增长率 | 基准指数平均值 |
| 规模因子（Size） | 加权平均市值 | 基准指数中位数 |
| 动量因子（Momentum） | 加权平均12个月（剔除最近1个月）回报率 | 基准指数平均值 |
| 质量因子（Quality） | 加权平均净资产收益率（ROE）、资产负债率 | 基准指数平均值 |
| 波动率因子（Volatility） | 加权平均实际波动率 | 基准指数平均值 |
| 股息率因子（Dividend yield） | 加权平均股息率 | 基准指数平均值 |
标记任何与基准指数偏差超过1个标准差的因子暴露。
Step 5: Risk Metrics
步骤5：风险指标
Calculate portfolio-level risk metrics:
| Metric | Description |
|---|---|
| Portfolio volatility | Annualized standard deviation |
| Beta | Sensitivity to benchmark |
| Tracking error | Volatility of active returns vs benchmark |
| Active share | Percentage of portfolio differing from benchmark |
| Value at Risk (95%) | 1-year loss at 95% confidence |
| Expected shortfall (CVaR) | Average loss beyond VaR |
| Maximum drawdown estimate | Based on historical allocation analysis |
| Sharpe ratio estimate | Expected excess return / volatility |
| Sortino ratio estimate | Excess return / downside deviation |
计算投资组合层面的风险指标：
| 指标 | 说明 |
|---|---|
| 投资组合波动率 | 年化标准差 |
| 贝塔（Beta） | 对基准指数的敏感度 |
| 跟踪误差（Tracking error） | 相对基准指数的主动回报率波动率 |
| 主动份额（Active share） | 投资组合与基准指数的差异占比 |
| 风险价值（VaR，95%） | 95%置信水平下的1年潜在损失 |
| 预期短缺（CVaR） | 超出VaR的平均损失 |
| 最大回撤估算 | 基于历史配置分析 |
| 夏普比率估算 | 预期超额回报率/波动率 |
| 索提诺比率估算 | 超额回报率/下行波动率 |
Step 6: Stress Testing
步骤6：压力测试
Run the portfolio through historical stress scenarios. See references/diagnostic-framework.md for scenario details.
| Scenario | Period | Key Characteristics |
|---|---|---|
| Global Financial Crisis | 2007–2009 | Credit freeze, equity -55%, correlations spike |
| COVID Crash | Feb–Mar 2020 | Rapid -34%, V-shaped recovery |
| 2022 Rate Shock | 2022 | Bonds & stocks fall together, growth crushed |
| Dot-Com Bust | 2000–2002 | Tech -78%, value outperforms |
| Inflation Shock | 1973–1974 | Stagflation, broad equity -45% |
For each scenario, estimate portfolio impact and recovery timeline.
让投资组合经历历史压力场景测试。场景详情参考references/diagnostic-framework.md。
| 场景 | 时间段 | 核心特征 |
|---|---|---|
| 全球金融危机 | 2007–2009 | 信贷冻结，股市下跌55%，相关性飙升 |
| 新冠崩盘 | 2020年2-3月 | 快速下跌34%，V型复苏 |
| 2022年利率冲击 | 2022年 | 股债齐跌，成长股重挫 |
| 互联网泡沫破裂 | 2000–2002 | 科技股下跌78%，价值股跑赢大盘 |
| 通胀冲击 | 1973–1974 | 滞胀，全市场股市下跌45% |
针对每个场景，估算投资组合受到的影响及恢复周期。
Step 7: Liquidity Assessment
步骤7：流动性评估
Evaluate portfolio liquidity:
| Metric | What to Check |
|---|---|
| Days to liquidate | How long to exit each position at 20% of average daily volume |
| Illiquid positions | Holdings where full exit takes > 5 trading days |
| Bid-ask spreads | Positions with typically wide spreads |
| Concentration in illiquid names | Percentage of portfolio in low-volume stocks |
评估投资组合的流动性：
| 指标 | 检查内容 |
|---|---|
| 变现天数 | 以日均成交量的20%变现每个持仓所需的时间 |
| 非流动性持仓 | 全额变现需超过5个交易日的持仓 |
| 买卖价差（Bid-ask spreads） | 通常存在宽价差的持仓 |
| 非流动性标的集中度 | 投资组合中低成交量股票的占比 |
Step 8: Diagnosis and Recommendations
步骤8：诊断与建议
Synthesize findings into a health report. Format per references/output-template.md:
- Health Score — 0–100 composite score across all dimensions
- Critical Issues — Problems requiring immediate attention
- Warnings — Issues to monitor or address opportunistically
- Strengths — What the portfolio does well
- Improvement Actions — Prioritized, specific recommendations with rationale
- Rebalancing Suggestions — Concrete trades to improve the portfolio
将分析结果整合为健康报告。格式参考references/output-template.md：
- 健康评分——基于所有维度的0-100分综合评分
- 关键问题——需立即关注的问题
- 预警提示——需监控或择机解决的问题
- 优势亮点——投资组合表现出色的方面
- 改进措施——按优先级排序的具体建议及理由
- 再平衡建议——可优化投资组合的具体交易操作
Data Enhancement
数据增强
For live market data to support this analysis, use the FinData Toolkit skill (). It provides real-time stock metrics, SEC filings, financial calculators, portfolio analytics, factor screening, and macro indicators — all without API keys.
findata-toolkit-us如需实时市场数据支持本分析，可使用FinData Toolkit技能（）。它提供实时股票指标、SEC文件、金融计算器、投资组合分析、因子筛选和宏观经济指标——无需API密钥。
findata-toolkit-usImportant Guidelines
重要指南
- Diagnose, don't reconstruct: This skill evaluates an existing portfolio. If the user needs a new portfolio from scratch, direct them to the Risk-Adjusted Return Optimizer.
- Context matters: A 100% equity portfolio is fine for a 25-year-old with a 40-year horizon. Concentration that looks alarming in isolation may be appropriate in context.
- Tax awareness: In taxable accounts, recommend improvements that consider tax implications of selling. Suggest tax-loss harvesting where applicable.
- Behavioral sensitivity: Don't suggest massive overhauls. Investors have emotional attachment to holdings. Prioritize the highest-impact changes.
- Benchmark appropriateness: A retiree's portfolio shouldn't be benchmarked against the S&P 500. Choose benchmarks that match the investor's goals.
- Not personalized advice: Disclaim that this is educational analysis, not personalized investment advice. Individual circumstances require a qualified financial advisor.
- 仅诊断，不重构：本技能仅评估现有投资组合。如果用户需要从零开始构建新的投资组合，请引导他们使用风险调整收益优化器。
- 上下文至关重要：对于一位25岁、投资期限40年的投资者来说，100%股票的投资组合是可行的。孤立来看看似危险的集中度，结合上下文可能是合适的。
- 税务意识：在应税账户中，建议改进方案时需考虑卖出的税务影响。适当时建议税务损失收割策略。
- 行为敏感性：不建议大规模彻底调整。投资者对持仓有情感依赖。优先选择影响最大的变更。
- 基准指数适配性：退休投资者的投资组合不应以标普500为基准。选择与投资者目标匹配的基准指数。
- 非个性化建议：声明本分析为教育性内容，而非个性化投资建议。个人具体情况需咨询合格的财务顾问。