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Price-to-Earnings Multiples and Comparable Company Valuation

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Price-to-Earnings Ratio and Relative ValuationEquity Valuation Across Growth Phases+2 more→→Enterprise Value and Valuation MultiplesEquity Valuation Using Multiples
equity valuation multiples fundamentals

Core Idea

Earnings multiples (P/E, PEG, EV/EBITDA) provide simple relative valuation by comparing companies to peers. Theoretical P/E depends on growth, risk, and payout ratio: P/E = (payout ratio × (1 + g)) / (r - g). Multiples work best when comparing similar firms, but ignore differences in quality, growth prospects, and risk that drive fundamental value differences.

How It's Best Learned

Compare valuation multiples across a peer group and create a simple model linking multiples to fundamentals like growth and ROE.

Explainer

From your prerequisite work on P/E valuation and stock fundamentals, you understand that a stock's intrinsic value depends on the cash flows it is expected to generate and the discount rate that reflects its risk. The dividend discount model gives us P = D/(r - g), where D is the next dividend, r is the required return, and g is the perpetual growth rate. Dividing both sides by earnings E gives the theoretical P/E ratio: P/E = (D/E) / (r - g) = (payout ratio) / (r - g). This formula is the bridge between relative valuation (comparing P/E multiples across companies) and fundamental valuation (discounting cash flows at a risk-adjusted rate). A stock trading at a higher P/E than peers is either expected to grow faster, has lower risk, or is simply overvalued — the multiple alone cannot distinguish these.

Comparable company analysis (comps) is the practical application of this logic. The process begins by assembling a peer group of companies with similar business models, competitive positions, and capital structures. You then compute standardized multiples — P/E (market cap divided by net income), EV/EBITDA (enterprise value divided by earnings before interest, taxes, depreciation, and amortization), PEG (P/E divided by expected growth rate) — for each peer and construct a distribution. The subject company's implied value range is derived by applying the peer median or mean multiple to its own earnings. EV/EBITDA is often preferred over P/E because it is capital-structure-neutral: using enterprise value (equity plus net debt) and EBITDA (pre-financing earnings) removes the distortions from different leverage levels, making cross-company comparison cleaner.

The theoretical P/E formula reveals exactly what drives multiple differences across firms. Higher expected growth g raises P/E because future earnings streams are larger. Lower required return r (lower risk, perhaps lower beta) raises P/E because those streams are discounted at a lower rate. A higher payout ratio mechanically raises P/E, though this is partly offset by the growth foregone from paying out rather than reinvesting. The PEG ratio — P/E divided by expected growth — is an attempt to control for growth differences, putting high-growth and low-growth firms on the same footing. A PEG below 1 is traditionally interpreted as potentially undervalued (you are paying less than one unit of P/E for each percentage point of growth), though this is a heuristic rather than a rigorous result.

The critical limitation of multiples is that they summarize everything into one number, hiding the underlying drivers. Two firms with identical P/E ratios can have completely different growth prospects, risk profiles, and return-on-equity characteristics that will lead to very different fundamental values. Comps analysis is most reliable when the peer group is genuinely comparable — similar industry economics, growth stage, and risk — and weakest when applied across companies with structural differences. In practice, equity analysts use multiples as a sanity check alongside DCF valuation: if the DCF says a stock is worth $50 but every comparable trades at a multiple implying $25, the analyst needs to explain that gap or revisit the DCF assumptions. The two methods triangulate rather than substitute for each other.

Practice Questions 5 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Dividing Integers → Unit Rates → Proportions → Percent Concept → Converting Between Fractions, Decimals, and Percents → Operations with Rational Numbers → Two-Step Equations → Solving Multi-Step Equations → Equations with Variables on Both Sides → Literal Equations → Slope-Intercept Form → Point-Slope Form → Writing Linear Equations → Parallel and Perpendicular Line Slopes → Graphing Linear Equations → Piecewise Functions → One-Sided Limits → Continuity Definition → Limits and Continuity in Multiple Variables → Functions of Several Variables → Continuity in Multiple Variables → Partial Derivatives: Definition and Computation → Differentiability in Multiple Variables → Differentiability in Multivariable Functions → Total Differential and Linear Approximation → Chain Rule for Multivariable Functions → Implicit Differentiation → Related Rates → Optimization Problems → Critical Points of Multivariable Functions → Critical Points and Classification of Extrema → Second Partial Test for Local Extrema (Hessian) → The Hessian Matrix and Second Derivative Test → Unconstrained Optimization: Finding Extrema → Optimization in Multiple Variables → Lagrange Multipliers → Constrained Optimization and Lagrange Multipliers → Utility and Preferences → Marginal Utility and Diminishing Returns → Profit Maximization → Price-to-Earnings Ratio and Relative Valuation → Price-to-Earnings Multiples and Comparable Company Valuation

Longest path: 94 steps · 491 total prerequisite topics

Prerequisites (4)

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