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equities

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Original

English
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Translation

Chinese

Equities

股票证券

Purpose

用途

Analyze equity securities including individual stocks, equity indices, and equity portfolios. This skill covers factor models, valuation ratios, index construction methodologies, style analysis, earnings mechanics, and sector classification frameworks essential for equity market analysis.
分析股票证券，包括个股、股票指数及股票投资组合。本技能涵盖因子模型、估值比率、指数构建方法、风格分析、收益机制以及股票市场分析必备的行业分类框架。

Layer

层级

2 — Asset Classes
2 — 资产类别

Direction

适用方向

both
双向

When to Use

使用场景

  • User asks about stocks, equity securities, or equity portfolio analysis
  • User asks about equity factor models (CAPM, Fama-French, momentum, quality, low vol)
  • User asks about index weighting methodologies (cap-weighted, equal-weighted, fundamental)
  • User asks about valuation ratios (P/E, P/B, EV/EBITDA, dividend yield)
  • User asks about earnings mechanics (EPS, diluted EPS, forward P/E, PEG ratio)
  • User asks about sector or industry classification (GICS)
  • User asks about style analysis (value vs growth, large vs small cap)
  • User asks about return decomposition (price return vs total return)
  • 用户询问股票、股票证券或股票投资组合分析相关问题
  • 用户询问股票因子模型（CAPM、Fama-French、动量、质量、低波动）
  • 用户询问指数加权方法（市值加权、等权加权、基本面加权）
  • 用户询问估值比率（P/E、P/B、EV/EBITDA、股息率）
  • 用户询问收益机制（EPS、稀释EPS、预期P/E、PEG ratio）
  • 用户询问行业分类（GICS）
  • 用户询问风格分析（价值 vs 成长、大盘 vs 小盘）
  • 用户询问收益分解（价格收益 vs 总收益）

Core Concepts

核心概念

Market Cap Weighting vs Equal Weighting vs Fundamental Weighting

市值加权 vs 等权加权 vs 基本面加权

Cap-weighted indices weight each stock by its market capitalization, meaning larger companies dominate the index. Equal-weighted indices assign the same weight to every constituent, giving more influence to smaller names and requiring periodic rebalancing. Fundamental weighting uses metrics like revenue, earnings, or book value to determine weights, attempting to break the link between price and portfolio weight.
市值加权指数根据个股的市值来分配权重，意味着大型公司在指数中占主导地位。等权加权指数为每个成分股分配相同权重，赋予小市值公司更大影响力，且需要定期再平衡。基本面加权则采用营收、收益或账面价值等指标来确定权重，试图打破价格与投资组合权重之间的关联。

Factor Models

因子模型

Factor models explain equity returns through systematic exposures. The single-factor CAPM uses market beta. Multi-factor models add Size (SMB — Small Minus Big), Value (HML — High Minus Low book-to-market), Momentum (UMD — Up Minus Down), Quality (profitable minus unprofitable), and Low Volatility. Factor exposures are estimated via time-series regression of excess returns on factor returns.
CAPM: E(R_i) = R_f + beta_i × (E(R_m) - R_f)
Fama-French 3-Factor: R_i - R_f = alpha + beta_m×(R_m - R_f) + beta_s×SMB + beta_v×HML + epsilon
因子模型通过系统性风险敞口来解释股票收益。单因子CAPM模型使用市场贝塔。多因子模型则加入了规模因子（SMB — 小盘股减大盘股）、价值因子（HML — 高市净率减低市净率）、动量因子（UMD — 上涨股减下跌股）、质量因子（盈利股减非盈利股）以及低波动因子。因子敞口通过超额收益对因子收益的时间序列回归来估算。
CAPM: E(R_i) = R_f + beta_i × (E(R_m) - R_f)
Fama-French 3-Factor: R_i - R_f = alpha + beta_m×(R_m - R_f) + beta_s×SMB + beta_v×HML + epsilon

Style Box Classification

风格箱分类

The Morningstar style box maps funds and portfolios along two dimensions: Value/Blend/Growth (horizontal) and Large/Mid/Small cap (vertical), producing a 3x3 grid. Style is determined by valuation ratios (P/E, P/B) and growth metrics (earnings growth, sales growth). Style analysis regresses fund returns against style benchmark indices to determine effective exposures.
晨星风格箱从两个维度对基金和投资组合进行划分：价值/平衡/成长（横向）和大盘/中盘/小盘（纵向），形成一个3×3的网格。风格由估值比率（P/E、P/B）和增长指标（收益增长、营收增长）决定。风格分析通过将基金收益与风格基准指数进行回归，来确定实际的风险敞口。

Valuation Ratios

估值比率

  • P/E Ratio = Price / Earnings Per Share
  • P/B Ratio = Price / Book Value Per Share
  • EV/EBITDA = Enterprise Value / EBITDA
  • Dividend Yield = Annual Dividends Per Share / Price
  • Earnings Yield = EPS / Price (inverse of P/E)
  • P/E Ratio = 股价 / 每股收益
  • P/B Ratio = 股价 / 每股账面价值
  • EV/EBITDA = 企业价值 / 息税折旧摊销前利润
  • 股息率 = 年度每股股息 / 股价
  • 收益率 = EPS / 股价（P/E的倒数）

Earnings Mechanics

收益机制

  • EPS (Earnings Per Share) = Net Income / Shares Outstanding
  • Diluted EPS accounts for stock options, convertibles, and other dilutive securities
  • Forward P/E uses analyst consensus estimated future earnings
  • PEG Ratio = P/E / Earnings Growth Rate (a growth-adjusted valuation measure)
  • EPS（每股收益）= 净利润 / 已发行股份数
  • 稀释EPS考虑了股票期权、可转换债券及其他稀释性证券的影响
  • 预期P/E使用分析师一致预期的未来收益
  • PEG Ratio = P/E / 收益增长率（经增长调整后的估值指标）

Sector and Industry Classification (GICS)

行业分类框架（GICS）

The Global Industry Classification Standard organizes equities into 11 sectors, 25 industry groups, 74 industries, and 163 sub-industries. Sector analysis helps identify concentration risk in portfolios and provides a framework for relative valuation comparisons.
全球行业分类标准将股票分为11个行业板块、25个行业组、74个行业及163个子行业。行业分析有助于识别投资组合中的集中度风险，并为相对估值比较提供框架。

Index Construction

指数构建

  • Price-weighted (DJIA): weight proportional to share price, biased toward high-priced stocks
  • Cap-weighted (S&P 500): weight proportional to market cap, reflects aggregate market value
  • Equal-weighted: same weight to each constituent, requires periodic rebalancing
  • 价格加权（DJIA）：权重与股价成正比，偏向高价股
  • 市值加权（S&P 500）：权重与市值成正比，反映市场总价值
  • 等权加权：每个成分股权重相同，需要定期再平衡

Return Decomposition

收益分解

Total Return = Price Return + Dividend Return. Price return captures capital gains only. Total return includes reinvested dividends and is the appropriate measure for performance comparison.
总收益 = 价格收益 + 股息收益。价格收益仅反映资本利得。总收益包括再投资股息，是业绩比较的合适指标。

Key Formulas

核心公式

FormulaExpressionUse Case
CAPM Expected ReturnE(R_i) = R_f + beta_i × (E(R_m) - R_f)Single-factor expected return
Fama-French 3-FactorR_i - R_f = alpha + beta_m×(R_m-R_f) + beta_s×SMB + beta_v×HML + epsilonMulti-factor return attribution
P/E RatioPrice / EPSRelative valuation
Earnings YieldEPS / PriceInverse of P/E, comparable to bond yields
PEG Ratio(P/E) / Earnings Growth RateGrowth-adjusted valuation
EV/EBITDA(Market Cap + Debt - Cash) / EBITDACapital-structure-neutral valuation
Dividend YieldAnnual Dividends / PriceIncome return measure
Total ReturnPrice Return + Dividend ReturnComplete performance measure
公式表达式使用场景
CAPM预期收益E(R_i) = R_f + beta_i × (E(R_m) - R_f)单因子预期收益计算
Fama-French三因子模型R_i - R_f = alpha + beta_m×(R_m-R_f) + beta_s×SMB + beta_v×HML + epsilon多因子收益归因
P/E比率股价 / EPS相对估值
收益率EPS / 股价P/E的倒数，可与债券收益率对比
PEG比率(P/E) / 收益增长率经增长调整后的估值
EV/EBITDA(Market Cap + Debt - Cash) / EBITDA不受资本结构影响的估值
股息率Annual Dividends / Price收益回报指标
总收益Price Return + Dividend Return完整业绩指标

Worked Examples

示例计算

Example 1: CAPM Expected Return

示例1：CAPM预期收益计算

Given: beta = 1.2, R_f = 4%, E(R_m) = 10% Calculate: Expected return using CAPM Solution: Equity risk premium = E(R_m) - R_f = 10% - 4% = 6% E(R_i) = R_f + beta × ERP = 4% + 1.2 × 6% = 4% + 7.2% = 11.2%
The stock's expected return is 11.2%, reflecting a 7.2% risk premium for bearing 1.2x market risk.
给定： beta = 1.2，R_f = 4%，E(R_m) = 10% 计算： 使用CAPM计算预期收益 解答： 股票风险溢价 = E(R_m) - R_f = 10% - 4% = 6% E(R_i) = R_f + beta × ERP = 4% + 1.2 × 6% = 4% + 7.2% = 11.2%
该股票的预期收益为11.2%，反映了承担1.2倍市场风险所获得的7.2%风险溢价。

Example 2: Style Analysis via Regression

示例2：基于回归的风格分析

Given: A fund's monthly excess returns regressed on Russell 1000 Value and Russell 1000 Growth index excess returns over 36 months. Calculate: Style tilt of the fund Solution: Regression: R_fund - R_f = alpha + beta_V×(R_Value - R_f) + beta_G×(R_Growth - R_f) + epsilon Suppose results: beta_V = 0.70, beta_G = 0.25, alpha = 0.05%/month Interpretation: The fund has a 74% value tilt (0.70 / (0.70 + 0.25)) and 26% growth tilt. The positive alpha of 0.05%/month (roughly 0.6%/year) suggests modest skill beyond style exposures. Total beta of 0.95 indicates slight cash drag.
给定： 将某基金36个月的月度超额收益与罗素1000价值指数和罗素1000成长指数的超额收益进行回归。 计算： 基金的风格倾向 解答： 回归公式：R_fund - R_f = alpha + beta_V×(R_Value - R_f) + beta_G×(R_Growth - R_f) + epsilon 假设结果：beta_V = 0.70，beta_G = 0.25，alpha = 0.05%/月 解读：该基金的价值倾向为74%（0.70 / (0.70 + 0.25)），成长倾向为26%。每月0.05%的正alpha（约每年0.6%）表明除风格敞口外，基金具备小幅超额收益能力。总beta为0.95，表明存在轻微现金拖累。

Common Pitfalls

常见误区

  • Using trailing P/E when forward P/E is more relevant for valuation — trailing earnings reflect the past, not the future
  • Ignoring sector concentration in cap-weighted indices — a single sector can dominate 30%+ of the index
  • Survivorship bias in backtested factor strategies — failed companies drop out, inflating historical returns
  • Confusing price return with total return — dividends contribute significantly to long-term equity returns
  • 当预期P/E更适合估值时使用历史P/E —— 历史收益反映过去，而非未来
  • 忽略市值加权指数中的行业集中度 —— 单个行业可能占据指数30%以上的权重
  • 回测因子策略时存在幸存者偏差 —— 倒闭公司被剔除，导致历史收益被高估
  • 混淆价格收益与总收益 —— 股息对长期股票收益贡献显著

Cross-References

交叉引用

  • historical-risk (wealth-management plugin, Layer 1a): beta, volatility, and Sharpe ratio fundamentals
  • fund-vehicles (wealth-management plugin, Layer 2): equity fund selection (ETFs, mutual funds, SMAs)
  • currencies-and-fx (wealth-management plugin, Layer 2): international equity currency effects
  • portfolio-construction (wealth-management plugin, Layer 3): equity allocation within multi-asset portfolios
  • historical-risk（wealth-management plugin, Layer 1a）：beta、波动率及Sharpe ratio基础
  • fund-vehicles（wealth-management plugin, Layer 2）：股票基金选择（ETFs、mutual funds、SMAs）
  • currencies-and-fx（wealth-management plugin, Layer 2）：国际股票汇率影响
  • portfolio-construction（wealth-management plugin, Layer 3）：多资产投资组合中的股票配置

Reference Implementation

参考实现

See 
scripts/equities.py
for computational helpers.
详见
scripts/equities.py
获取计算工具。