Beta benchmark · 20 sectors
Beta by Industry: Average Stock Beta by Sector (2024)
Beta measures a stock's sensitivity to broad market moves and is the central variable in both CAPM and WACC calculations. It ranges from 0.35 (utilities) to 1.60 (biotech), and varies significantly within sectors based on leverage and business model. This table shows Damodaran-calibrated levered and unlevered beta benchmarks across 20 industries for 2024 -- use them to sanity-check your CAPM cost of equity or re-lever a sector beta to match a target capital structure before building a DCF model.
Levered beta reflects a company's actual capital structure -- it includes the amplifying effect of debt on equity volatility. Unlevered beta (asset beta) strips out financial leverage to reveal the pure operating risk of the business. Use unlevered beta to compare risk across sectors with different capital structures, or re-lever it for a target capital structure in your WACC model. Related benchmarks: WACC by industry.
2024 data · 20 sectors
Beta Benchmarks by Sector
| Sector | Levered Beta | Unlevered Beta | D/E Ratio | Key Driver |
|---|---|---|---|---|
| Technology (Software/SaaS)MSFT, CRM, ADBE | 1.20 | 1.10 | 0.08x | Asset-light SaaS has low financial leverage so levered is close to unlevered; hardware adds cyclical sensitivity |
| SemiconductorsNVDA, AMD, MCHP | 1.45 | 1.30 | 0.12x | Capital-intensive fabs and inventory cycles amplify market swings; fabless designers sit at the lower end |
| Healthcare (Large Pharma)JNJ, PFE, ABBV | 0.75 | 0.70 | 0.08x | Patent-protected cash flows and inelastic demand dampen market correlation |
| BiotechMRNA, BMRN, RARE | 1.60 | 1.55 | 0.04x | Clinical trial binary events drive elevated beta; minimal debt as pre-revenue firms lack capacity |
| Financials (Banks)JPM, BAC, WFC | 0.95 | 0.40 | 1.50x | Unlevered beta is low; high leverage from deposits amplifies equity sensitivity -- WACC is ill-defined for banks |
| InsurancePGR, CB, TRV | 0.85 | 0.55 | 0.60x | Float-funded investment portfolios add market exposure; underwriting cycles create episodic volatility |
| Consumer Discretionary (Retail)HD, TGT, MCD | 1.05 | 0.85 | 0.25x | Cyclical spending sensitivity; brick-and-mortar operators carry more leverage than pure-play e-commerce |
| Consumer StaplesPG, KO, WMT | 0.55 | 0.48 | 0.15x | Defensive earnings and stable pricing power dampen market sensitivity |
| E-commerceAMZN, ETSY, CHWY | 1.30 | 1.10 | 0.18x | Growth expectations and discretionary demand combine; logistics capex adds operational leverage |
| Energy (Oil & Gas)XOM, CVX, DVN | 1.20 | 0.90 | 0.35x | Commodity price exposure adds systematic risk; leverage amplifies further in down-cycles |
| UtilitiesNEE, DUK, SO | 0.50 | 0.35 | 0.90x | Regulated monopoly pricing floors returns; high debt is offset by revenue certainty |
| MaterialsLIN, FCX, NEM | 1.10 | 0.85 | 0.30x | Commodity-linked revenues and capital intensity; mining and chemicals at the higher end |
| IndustrialsHON, CAT, GE | 1.00 | 0.80 | 0.25x | Broad cyclicality with moderate leverage; defense contractors and aerospace sub-sectors trade at a discount to beta |
| Communication ServicesGOOGL, META, VZ | 0.90 | 0.70 | 0.30x | Legacy telecom anchors the low end; ad-driven platforms drive the high end alongside digital media |
| Real Estate (REITs)PLD, EQIX, SPG | 0.80 | 0.45 | 0.80x | Interest rate sensitivity dominates; high leverage from mortgage financing amplifies equity moves |
| Medical DevicesMDT, SYK, ISRG | 1.00 | 0.92 | 0.10x | Recurring consumable revenue provides stability; pipeline risk adds upside volatility |
| Airlines/TravelDAL, UAL, MAR | 1.55 | 0.85 | 0.85x | High operating and financial leverage; demand is extremely cyclical and fuel-cost sensitive |
| Auto/EVTSLA, F, GM | 1.35 | 1.05 | 0.30x | Legacy OEMs carry manufacturing leverage; EV pure-plays add growth-stock premium to beta |
| Defense/AerospaceLMT, RTX, NOC | 0.85 | 0.72 | 0.18x | Government contract backlog provides revenue visibility; budget cycles add periodic risk |
| Restaurants/Food ServiceMCD, SBUX, YUM | 0.90 | 0.65 | 0.40x | Franchise models generate stable royalty streams; company-owned locations add capex and labor cyclicality |
How to Use Industry Beta in CAPM and WACC
Beta is the single input that translates market-level risk into a company-specific cost of equity. In the CAPM formula -- Cost of Equity = Risk-Free Rate + Beta x Equity Risk Premium -- beta scales the equity risk premium up or down based on how much the stock historically moves with the market. The CAPM calculator computes this automatically for any ticker, but the sector benchmarks above let you cross-check or substitute when single-stock beta is noisy.
Step 1: Start with the unlevered sector beta, then re-lever it. If a company has meaningfully different leverage from the sector average, the levered benchmark will be misleading. Use the unlevered beta as a clean baseline for business risk, then apply the Hamada equation: Levered Beta = Unlevered Beta x (1 + (1 - Tax Rate) x D/E). For a software company with 20% D/E at a 25% tax rate, that would be 1.10 x (1 + 0.75 x 0.20) = 1.27. Plug that into CAPM to get a capital-structure-adjusted cost of equity.
Step 2: Use beta as a sanity check, not a precise input. Single-stock beta estimates are notoriously noisy -- they depend heavily on the lookback period, return frequency, and market proxy chosen. If your independently estimated beta for a software company comes out at 0.50, that should trigger a review: the sector median is 1.20. A dramatic departure from the sector usually means the company is genuinely different (very defensive software with near-zero revenue cyclicality) or the estimate is stale. The WACC calculator pulls beta from live data; supplement with the sector benchmark when the live figure looks like an outlier.
Step 3: Adjust for forward-looking risk, not just historical co-movement. Beta is backward-looking. A company on the verge of a major business model transition (entering a new market, spinning off a division, completing a leveraged buyout) will have a historical beta that does not reflect its future risk profile. In those cases, build up from the unlevered sector beta and apply qualitative adjustments: add 0.10-0.20 for significant execution risk, subtract if the transition moves the company into a lower-risk segment. Document the rationale alongside your WACC assumptions in the DCF model.
What Drives Each Sector's Beta
Utilities (0.50 levered beta)
Rate regulation gives utilities predictable, government-backed cash flows that are nearly uncorrelated with economic cycles. The high D/E ratio amplifies the levered beta above the unlevered (0.35), but both remain well below 1.0 -- the market benchmark. Utilities are the classic defensive holding for investors seeking low correlation.
Biotech (1.60 levered beta)
Binary FDA outcomes, pre-revenue business models, and near-zero debt capacity combine to produce the highest betas in the benchmark. Minimal financial leverage means unlevered beta (1.55) is nearly as high as levered -- the risk is almost entirely operational. A failed Phase III trial can erase 80% of equity value in a single trading session.
Financials/Banks (0.95 levered, 0.40 unlevered)
The largest divergence in the table: 1.50x D/E from deposits and wholesale funding transforms a low-operating-risk business (0.40 unlevered beta) into near-market-level equity sensitivity. WACC is technically ill-defined for banks -- analysts use cost of equity (8%-10%) as the primary hurdle instead of a debt-blended discount rate.
Semiconductors (1.45 levered beta)
Inventory cycles in chips are sharp and synchronised with the economic cycle -- a customer destocking event can cut revenue by 30%-40% in a single quarter. Fabless designers (NVDA, AMD) sit at the higher end; analog and embedded chip makers with diverse end markets (MCHP) compress toward 1.20-1.30.
Consumer Staples (0.55 levered beta)
Inelastic demand, pricing power, and decades-long brand moats give staples companies earnings that barely move with the economic cycle. Beta stays low even during recessions because consumers keep buying toothpaste and breakfast cereal. These names are the market's shock absorbers -- their defensive attributes command premium valuations.
Airlines/Travel (1.55 levered, 0.85 unlevered)
High operating leverage (fixed costs, aircraft leases, labor contracts) combines with high financial leverage to produce some of the most volatile equities in the index. Fuel cost sensitivity adds a commodity-price dimension on top of demand cyclicality. The unlevered beta of 0.85 shows the underlying business is near-market risk; the capital structure amplifies that to 1.55.
Common questions
Beta by industry -- answered directly.
What is beta in investing?
Beta is a measure of a stock's sensitivity to broad market movements. A beta of 1.0 means the stock tends to move in line with the market. Beta is calculated by regressing the stock's historical returns against the market's returns and is the central input in both CAPM cost-of-equity calculations and WACC models.
What does a beta above 1 mean for a stock?
A beta above 1.0 means the stock historically moves more than the market in percentage terms. A beta of 1.50 implies that when the S&P 500 rises 10%, the stock tends to rise roughly 15% — and falls 15% when the market drops 10%. Higher beta means higher systematic risk and higher expected return over the long run, but larger drawdowns in bear markets.
Which stock market sectors have the highest beta?
Biotech (1.60), airlines/travel (1.55), and semiconductors (1.45) carry the highest levered betas. Biotech is driven by binary FDA trial outcomes. Airlines combine high operating and financial leverage with extreme demand cyclicality. Semiconductors are exposed to sharp inventory cycles that can cut revenue 30-40% in a single quarter.
How is beta used in portfolio construction?
Portfolio managers use beta to control overall market sensitivity. A portfolio with a weighted-average beta above 1.0 amplifies market moves (higher risk, higher return potential); below 1.0 dampens them (defensive positioning). Beta also feeds directly into CAPM: Cost of Equity = Risk-Free Rate + Beta x Equity Risk Premium, which drives the discount rate in DCF models.
What is a beta of 0?
A beta of 0 means the stock has no statistical correlation with market movements — it moves independently of the broad index. Cash and Treasury bills have betas near zero. In practice, very few equities have true zero beta; some gold miners and certain healthcare companies approach it during specific market regimes.
What is a good beta for a stock?
A beta of 1.0 means the stock moves in line with the market. Betas below 1.0 (defensive sectors like utilities at 0.50, consumer staples at 0.55) indicate lower systematic risk and are considered good for income-oriented or risk-averse investors. Betas above 1.0 (biotech at 1.60, semiconductors at 1.45) indicate higher volatility relative to the market. There is no universally good beta — it depends on the investor's goal. For valuation purposes, a good beta is an accurate one that reflects the company's actual sensitivity to market cycles, not a default assumption.
What does a beta below 1 mean?
A beta below 1 means the stock historically moves less than the market in percentage terms. A beta of 0.60 implies that when the S&P 500 falls 10%, the stock tends to fall roughly 6%. Sectors with sub-1 betas — utilities (0.50), consumer staples (0.55), healthcare pharma (0.75) — exhibit this characteristic because their revenues are largely insensitive to the economic cycle. Investors value these defensive properties in bear markets, which is why low-beta stocks tend to outperform during downturns and underperform in strong bull markets.
Which sectors have the highest beta?
Biotech (1.60), airlines/travel (1.55), and semiconductors (1.45) carry the highest levered betas in the benchmark. Biotech is driven by binary FDA trial outcomes and near-zero debt capacity. Airlines combine high operating leverage (fixed costs, leases) with high financial leverage and extreme demand cyclicality. Semiconductors are exposed to sharp inventory cycles where customer destocking can cut revenue 30-40% in a single quarter. Auto/EV (1.35) and e-commerce (1.30) round out the high-beta cluster.
How is beta calculated?
Beta is calculated by regressing a stock's historical returns against the market's returns (typically using the S&P 500 as the market proxy) over a set lookback period — commonly 2-5 years using monthly or weekly returns. The slope of the regression line is the beta estimate. Formally: Beta = Covariance(stock returns, market returns) / Variance(market returns). Single-stock betas are notoriously noisy because they depend heavily on the lookback period, return frequency, and market proxy chosen. Industry-median betas from sources like Damodaran provide a more stable benchmark.
What is the average S&P 500 beta?
By construction, the market-cap-weighted average beta of all S&P 500 constituents is 1.0 — because the index itself is the benchmark. Equal-weighted, the average beta of S&P 500 constituents is typically slightly above 1.0 because smaller-cap index members tend to have modestly higher betas than the mega-cap companies that dominate the market-cap-weighted calculation. In practice, most analysts treat 1.0 as the market average and benchmark individual stocks and sectors against it.
Why does beta differ by sector?
Beta differs by sector because sectors have fundamentally different revenue sensitivities to the economic cycle (operating risk) and different amounts of financial leverage (financial risk). Utilities have regulated revenues that barely move with GDP, and their high debt amplifies equity moves modestly — resulting in low beta. Biotech has binary clinical outcomes completely independent of the cycle but enormous event risk. Semiconductors are tightly coupled to corporate IT spending cycles. Financial leverage then scales these underlying business risks up or down: the Hamada equation shows levered beta = unlevered beta x (1 + (1 - tax rate) x D/E).
Is a high beta always a bad sign?
No. High beta reflects higher systematic risk, but it is also associated with higher expected returns over the long run — the core insight of CAPM. For growth investors and long-horizon investors, high-beta sectors like biotech and semiconductors have delivered strong returns over full market cycles despite their volatility. High beta becomes a problem when an investor has a short time horizon, needs capital preservation, or cannot tolerate drawdowns — contexts where volatility directly impairs outcomes. For valuation purposes, high beta increases the cost of equity in a WACC calculation, which reduces the DCF intrinsic value of a company's cash flows.
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