Industry Statistics

Returns Aswath Damodaran’s industry averages: betas, the cost of capital, margins and valuation multiples for each of his roughly 95 industries and the market as a whole, per region. They are the inputs of a bottom-up valuation: a company’s beta is better estimated from the unlevered beta of its industry, relevered at its own debt-to-equity ratio, than from a regression on its own noisy returns, and its multiples and margins read best next to those of its industry.

Damodaran computes the averages from the financial statements and prices of all listed companies (about 6,000 in the United States and 48,000 globally) at the start of each year, and publishes them every January. The figures are therefore a snapshot at the start of the current year and do not change during it.

The datasets are:

• betas: the average levered Beta (2-year and 5-year weekly regressions), D/E Ratio, Effective Tax rate, Unlevered beta, Cash/Firm value, the Unlevered beta corrected for cash, HiLo Risk and the standard deviations of equity and operating income.
• total_betas: the market betas next to the Total Unlevered and Levered Beta, the beta divided by the correlation with the market, for an investor who is not diversified.
• cost_of_capital: Beta, Cost of Equity, E/(D+E), Cost of Debt, Tax Rate, After-tax Cost of Debt, D/(D+E) and Cost of Capital, from the treasury rate and implied equity risk premium of the start of the year.
• margins: gross, net, operating (unadjusted, lease adjusted, lease and R&D adjusted, before and after tax) and EBITDA margins, and expense ratios.
• price_to_earnings: the Current, Trailing and Forward PE, aggregate multiples, the expected growth of the next five years and the PEG Ratio.
• price_to_book: PBV, ROE, EV/ Invested Capital and ROIC.
• price_to_sales: Price/Sales, Net Margin, EV/Sales and the pre-tax operating margin.
• enterprise_value_multiples: EV/EBITDAR&D, EV/EBITDA, EV/EBIT and EV/EBIT (1-t), for firms with a positive EBITDA and for all firms.

The regions are the United States, Europe, Japan, Australia, New Zealand and Canada, Emerging Markets, China, India and Global. Rates, margins and returns are decimals (0.08 is 8%), betas and multiples plain numbers.

Also known as: Damodaran industry data, industry betas, unlevered beta by industry, bottom-up beta, industry cost of capital, industry WACC, industry margins, industry multiples, sector EV/EBITDA, industry PE.

Industry Statistics in Python or via the MCP

Install the Finance Toolkit with:

pip install financetoolkit -U

Then call get_industry_statistics as shown below.

from financetoolkit import Discovery

discovery = Discovery(api_key="FINANCIAL_MODELING_PREP_KEY")

cost_of_capital = discovery.get_industry_statistics(
    dataset="cost_of_capital", region="Europe"
)

cost_of_capital.loc[
    ["Semiconductor", "Software (System & Application)", "Utility (General)", "Total Market"],
    ["Beta", "Cost of Equity", "After-tax Cost of Debt", "D/(D+E)", "Cost of Capital"],
].round(4)

Or, after setting up the Finance Toolkit MCP, ask:

Which returns:

Parameters

get_industry_statistics accepts the following parameters.

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