Analyze equity securities, factor models, and equity portfolio construction. Use when the user asks about stocks, equity valuation ratios, index construction methods, or style analysis. Also trigger when users mention 'P/E ratio', 'growth vs value', 'market cap weighting', 'sector allocation', 'GICS

Equities This skill is a decision procedure: which valuation metric to use for which company, which index methodology fits which mandate, and the order of operations for analyzing a stock. It assumes the user can look up definitions; the value here is choosing the right tool. Core Concepts Choosing the Valuation Metric Match the metric to the sector and capital structure — using the wrong one is the most common equity analysis error. Situation Use Avoid Why Financials (banks, insurers) P/B, P/TBV, ROE vs P/B EV/EBITDA Debt is raw material, not financing — EV and EBITDA are meaningless; book value is marked closer to fair value Capital intensive (industrials, telecom, energy) EV/EBITDA, EV/EBIT P/E alone Neutralizes depreciation policy and leverage differences across peers Mature dividend payers (utilities, staples) Dividend yield + payout sustainability, P/E PEG Growth is low and stable; income and coverage matter most High growth, low/no earnings EV/Sales, PEG (if earnings exist), unit economics P/E, P/B Earnings are depressed by reinvestment; book value is mostly intangibles Cyclicals (autos, semis, materials) Mid cycle or normalized P/E, P/B at trough Spot P/E P/E is lowest at the cycle peak and highest at the trough — spot P/E inverts the buy/sell signal Negative earnings, positive cash flow EV/EBITDA, P/FCF P/E, earnings yield Ratio is undefined or misleading with negative denominator REITs and listed real estate P/FFO, P/AFFO, NAV P/E GAAP depreciation distorts earnings for property — handled in detail by the real assets skill Cross border / different leverage EV based multiples Equity multiples Enterprise value normalizes for capital structure Cross checks that apply everywhere: Use forward (next 12 month) estimates for the numerator decision when the business is changing; trailing figures when estimate quality is poor. Compare against the company's own history and a true peer set, not the whole market. Translate any multiple into its implied assumptions (growth, margin, required return) before declaring cheap/expensive — a low multiple usually encodes a real problem. Choosing the Index Methodology Mandate Methodology Trade off to flag Cheap, tax efficient market exposure Cap weighted (S&P 500, total market) Momentum chasing by construction; concentration in mega caps — a single sector can exceed 30% Reduce concentration / small cap tilt Equal weighted Higher turnover and rebalancing cost; structural size and contrarian tilt Break the price weight link Fundamental weighted (revenue, earnings, book) Effectively a value tilt with extra steps; compare cost vs an explicit value fund Explicit factor exposure Factor/style index (value, momentum, quality, low vol) Verify the factor definition and rebalance rules; factor timing rarely works Avoid Price weighted (DJIA style) Weight proportional to share price is economically arbitrary — legacy only Selection rules: default to cap weighted for core beta; add equal or fundamental weighted only when the user explicitly wants the embedded tilt and accepts the turnover; treat any "smart beta" product as a factor portfolio and evaluate its factor loadings, not its marketing name. Security Analysis Sequence 1. Classify the business — sector (GICS or equivalent), cyclical vs defensive, capital intensity, leverage. This determines the valuation toolkit (table above). 2. Quality screen — revenue trend, margin trend, ROIC vs cost of capital, balance sheet risk (net debt/EBITDA, interest coverage), share count trajectory (dilution vs buybacks). 3. Earnings basis — pick trailing vs forward EPS, check for one offs, use diluted share count. For cyclicals, normalize to mid cycle. 4. Value with the matched metric — primary multiple from the table, one cross check multiple, and where dividends are central a dividend based check (Gordon growth: P = D1 / (r g), valid only when g < r). 5. Factor and style context — regress (or eyeball) exposures to market beta, size, value, momentum, quality. Distinguish stock specific thesis from a factor bet you could buy more cheaply via an index. 6. Portfolio fit — marginal effect on sector concentration and factor tilts; total return (price + dividends) is the comparison basis, never price return alone. Key Formulas Formula Expression Use Case EV/EBITDA (Market Cap + Debt Cash) / EBITDA Capital structure neutral valuation Earnings Yield EPS / Price Compare equity vs bond yields PEG (P/E) / Earnings Growth Rate (in %) Growth adjusted valuation Gordon Growth P = D1 / (r g) Dividend based intrinsic value CAPM E(R) = R f + beta × (E(R m) R f) Required return input for valuation Total Return Price Return + Dividend Return Performance comparison basis Worked Examples Metric Selection and Valuation Given: An industrial company with market cap $500M, total debt $100M, cash $50M, EBITDA $75M, EPS $7.50, price $150. Decide and calculate: 1. Capital intensive industrial → primary metric is EV/EBITDA (table above), with P/E as cross check. 2. EV = $500M + $100M $50M = $550M. EV/EBITDA = $550M / $75M = 7.33x . 3. Cross check: P/E = $150 / $7.50 = 20.0x; earnings yield = 7.50 / 150 = 5.0% . 4. Interpretation: 7.33x EV/EBITDA is modest for an industrial if margins are stable — compare against the peer set and the company's own 5 10 year range. The 20x P/E looks richer than the EV multiple because the company carries little net debt; the EV multiple is the better cross peer comparison. Common Pitfalls Applying EV/EBITDA to banks or P/E to REITs — metric/sector mismatch is the dominant error this skill exists to prevent Buying cyclicals on low trailing P/E at the cycle peak (the "value trap" inversion) Treating a fundamental weighted or smart beta index as alpha rather than a packaged factor tilt Confusing price return with total return — dividends compound to a large share of long run equity returns Survivorship bias in backtested factor or screen results Cross References historical risk (wealth management plugin): volatility and drawdown measurement for equity return series statistics fundamentals (core plugin): beta estimation via CAPM regression performance metrics (wealth management plugin): Sharpe ratio and related risk adjusted return measures fund vehicles (wealth management plugin): equity fund selection (ETFs, mutual funds, SMAs) currencies and fx (wealth management plugin): international equity currency effects asset allocation (wealth management plugin): equity allocation within multi asset portfolios real assets (wealth management plugin): REIT valuation (P/FFO, NAV) is owned by that skill qualitative valuation (wealth management plugin) and quantitative valuation (wealth management plugin): deeper single company valuation workflows financial statements (wealth management plugin): EBITDA, free cash flow, ROIC, and margin analysis underpinning fundamental stock selection equity compensation (wealth management plugin): employer stock acquired through RSUs, options, and ESPPs carries equity risk plus tax and insider trading constraints factor investing (wealth management plugin): the factor loading evaluation of smart beta and style products prescribed above lives in that skill Running the Script The demo prints valuation metrics (including the worked example's EV/EBITDA and earnings yield), a factor regression on synthetic data, and sector concentration analysis. Run help for a list of the classes and functions. For programmatic use, import the module rather than running it — the demo only executes under python equities.py .