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Data/Sector indices/EV/EBITDA by sector
Data through 31 August 2026Next update 10 Oct 2026This page monthly · API daily

EV/EBITDA multiples by sector

The current and historical enterprise value (EV) to EBITDA for the eleven Sectors, calculated separately for the United States, global markets and global markets excluding the United States.

EV/EBITDA compares the same sector across markets well, and compares sectors with each other badly. It is measured before depreciation, so capital-heavy sectors look cheaper than they are. To rank sectors against one another, use P/E ratios by sector or price to book instead.

Most expensive sector, U.S.
25.4
Information Technology
Least expensive sector, U.S.
9.3
Energy
Median U.S. premium over global ex-U.S.
+41%
across 11 sectors
Sectors trading above their global ex-U.S. equivalent
11/11
sectors

EV/EBITDA (TTM) by sector and market

Month-end Aug 2026, with the change on the same month a year earlier.
United StatesGlobalGlobal ex-U.S.
sector Aug 2026 Chg Aug 2026 Chg Aug 2026 Chg
Information Technology 25.39 -1.79 21.29 -0.72 14.00 +1.05
Real Estate 22.62 +2.10 21.19 +1.28 19.37 +0.26
Financials 19.59 -1.28 17.28 -1.96 15.72 -2.05
Consumer Discretionary 18.98 +0.39 14.64 +0.51 9.93 +0.19
Industrials 18.73 +0.90 15.88 +0.57 13.68 +0.37
Health Care 17.59 +2.41 15.70 +1.20 12.50 -0.72
Consumer Staples 16.04 -0.04 12.69 -0.58 9.59 -1.02
Communication Services 14.14 +0.40 12.53 -0.06 8.75 -1.42
Materials 12.96 -0.49 10.22 +0.15 9.30 +0.33
Utilities 12.67 -1.01 11.39 -0.20 10.22 +0.58
Energy 9.27 +0.40 6.97 +0.53 5.26 +0.40
The three markets. United States is the U.S. sector index. Global is the worldwide sector index and includes the United States. Global ex-U.S. is the same index with U.S. companies removed. Both global columns cover developed and emerging markets.

Aggregate enterprise value divided by aggregate trailing twelve-month EBITDA, normalised. Financials covers only Transaction & Payment Processing Services and Financial Exchanges & Data — EBITDA is not a meaningful measure for banks, so they are excluded. That row is not comparable with the other ten. For banks, price to book is the measure that works — and unlike this one, it is calculated on the whole Financials sector.

The U.S. premium

EV/EBITDA (TTM) by sector, United States against global excluding the United States, with the premium labelled.
Every one of the 11 sectors trades higher in the United States, by a median of 41%. Country-level comparisons are usually explained away by sector composition — a market heavy in banks trades below one heavy in software. Holding the sector constant shows how much of the gap that actually explains.

Ranked, United States

EV/EBITDA (TTM) ranked by sector for the United States, Aug 2026.

EBITDA is measured before depreciation, so capital intensive sectors look cheaper than they really are.

Historical EV/EBITDA (TTM), United States

Year-end values for the 10 years to 2025, most recent first.
MonthInformation TechnologyReal EstateFinancialsConsumer DiscretionaryIndustrialsHealth CareConsumer StaplesCommunication ServicesMaterialsUtilitiesEnergy
Aug 2026 25.3922.6219.5918.9818.7317.5916.0414.1412.9612.679.27
2025 Dec 27.4920.6418.7019.9018.4216.6416.2815.2812.8013.068.56
2024 Dec 27.5519.6821.7419.0615.4820.0516.8113.6813.5313.047.19
2023 Dec 24.4020.1529.5517.0315.3417.6315.1412.4112.5212.425.73
2022 Dec 15.9616.6120.0614.4415.0616.2416.428.579.1413.755.37
2021 Dec 23.4524.4825.4021.8817.6218.1817.5312.9611.9114.238.97
2020 Dec 23.2821.3029.9526.0920.8918.2216.9214.1418.1813.63226.40
2019 Dec 16.8819.3326.9515.0713.4516.7417.1711.7610.3912.618.91
2018 Dec 11.5117.9219.6313.1111.9014.3313.0810.0310.6311.157.39
2017 Dec 13.57n/an/a14.1913.0714.8713.2311.4614.2911.9612.32
2016 Dec 12.04n/an/a11.6611.3511.7713.1010.5713.7811.9935.09

Long monthly histories for the global and global ex-U.S. sector series are available to subscribers.

U.S. premium by sector

Consumer Discretionary+91%
Information Technology+81%
Energy+76%
Consumer Staples+67%
Communication Services+62%
Health Care+41%

Aug 2026, United States

Highest — Information Technology25.4
Lowest — Energy9.3
Ratio2.7×
Sectors covered11

Where sector multiples stand, August 2026

In the United States, Information Technology is the most expensive sector on this measure at 25.4 times EBITDA, and Energy the least at 9.3 — a spread of 2.7 to one.

The more striking pattern is across markets rather than across sectors. Every one of the 11 sectors trades at a premium in the United States compared with the same sector outside it, by a median of 41%. The widest gap is Consumer Discretionary at +91%; the narrowest is Real Estate at +17%.

That finding cuts against the usual explanation for expensive-looking U.S. equities. Country comparisons are routinely dismissed on the grounds that the U.S. index simply holds more software and less banking. Holding the sector constant removes that objection, and a substantial premium remains.

Why EV/EBITDA is the right measure for crossing borders

Most valuation multiples travel badly between countries. A P/E ratio sits below tax and interest, so it absorbs every difference in corporate tax rates, in how much debt a market's companies carry, and in local accounting for financing costs. Two identical businesses in two countries can show materially different P/E ratios for reasons that have nothing to do with the businesses.

EV/EBITDA sits above all of that. Enterprise value counts debt as well as equity, and EBITDA is measured before interest and tax. What is left is closer to a comparison of the operating businesses themselves, which is what makes a sector comparison across markets defensible on this measure and awkward on most others.

What EBITDA leaves out

The metric flatters capital-hungry businesses. EBITDA is measured before depreciation, so a utility that must continually replace turbines and a software company that must replace almost nothing can print the same EV/EBITDA and be nothing alike as investments. Read Utilities, Energy, Real Estate and Materials with that in mind: their multiples look low partly because the measure ignores what it costs them to stay in business.

A note on Financials

The Financials multiple here is not a whole-sector figure, and it should not be read as one. EBITDA is close to meaningless for a bank, where interest income is the revenue rather than a financing item sitting below the line.

Siblis therefore calculates the Financials EV/EBITDA using only companies classified as Transaction & Payment Processing Services and Financial Exchanges & Data. This multiple makes sense only for these types of financial companies. Banks, insurers and capital markets firms are excluded. The figure is a fair reading of payments and exchange businesses; it is not a reading of the banking system, and it is not comparable with the other ten sectors on a like-for-like basis.

Choosing a measure

No single ratio answers every question about a sector. Each of these pages covers the same eleven sectors — what changes is the question the measure is good at, and how far the coverage reaches.

MeasureThe question it answers Why that one
EV/EBITDA this page How does one sector compare across markets? Sits above tax and debt, so it survives crossing borders. The only measure here that makes an international sector comparison sound.
P/E and earnings How fast are a sector’s earnings growing? Trailing and forward multiples with the earnings behind them, so the multiple and its denominator can be read together.
CAPE Is a sector expensive against its own history? Averages a decade of real earnings, which smooths the cycle out of the denominator.
Price to book What is the market paying for the assets? Works where earnings-based measures break down — asset-heavy sectors, and banks in particular. U.S. sectors only.
Dividend yield Which sectors pay, and how much? Income rather than valuation, but it moves inversely with price and is read alongside the multiples. U.S. sectors only.

Where this data is used

Some examples. Siblis valuation data appears in peer-reviewed journals, central bank publications and the financial press.

Es-CAPE Velocity: Value-Driven Sector Rotation Corey HoffsteinNewfound Research · 2019
Industry Variance Risk Premium, Cross-Industry Correlation, and Expected Returns Yabei Zhu, Xingguo Luo & Qi XuThe Journal of Futures Markets, 43(1) · 2023
Intangibles: The Impaired Accounting Challenge John H. Nugen, Alex Pomelnikov & Kerry WebbJournal of Business & Economic Policy, 4(1) · 2017

International sector data, in full

This page shows the U.S. sector history and a current reading for the global and global ex-U.S. universes. The subscription is the complete set.

Global and ex-U.S. sector historyThe full monthly series for both international universes, not just the latest reading.
Eleven sectors, three universesEvery sector calculated separately for the U.S., global and global ex-U.S. markets.
Every ratio, not just this oneP/E trailing and forward, CAPE, dividend yield and price-to-book alongside EV/EBITDA.
Excel and APIA workbook that opens, and a JSON endpoint that drops into Python, Sheets or Power Query.
XLSX Download the sample dashboardEvery market, ratio and month the database covers, marked cell by cell. · 1.0 MB
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How this is calculated

Aggregate enterprise value of a sector's constituent companies divided by their aggregate EBITDA over the previous twelve months — not an average of the constituents' individual multiples.

  • Enterprise value — Market capitalisation plus net debt, aggregated across the sector.
  • EBITDA — Earnings before interest, tax, depreciation and amortisation, trailing twelve months, normalised: major purely accounting gains and losses are removed.
  • Financials — Transaction & Payment Processing Services and Financial Exchanges & Data only. See the note above.
  • Revisions — Figures are point-in-time. If a company later restates its results, the historic reading is left exactly as first published: the series reflects what was known at the time, not what is known now.

Full methodology (PDF) →

Cite this page

Siblis Research. (2026). EV/EBITDA multiples by sector [Data set]. Retrieved 31 August 2026, from siblisresearch.com/data/ev-ebitda-multiple/

@misc{siblis_ev_ebitda_multiple,
  title={EV/EBITDA multiples by sector}, author={{Siblis Research}},
  year={2026}, url={https://siblisresearch.com/data/ev-ebitda-multiple/},
  urldate={2026-08-31}}

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