Economic Value Added (EVA)
Economic Value Added (EVA) is a measure of a company’s financial performance that represents the value created in excess of the required return of the company’s capital providers. It captures whether a company is generating returns above its true cost of capital, which distinguishes it from purely accounting-based measures such as Net Income.
The formula is as follows:
\[\text{NOPAT} = \text{EBIT} \cdot (1 - \text{Corporate Tax Rate})\] \[\text{Invested Capital} = \text{Total Equity} + \text{Total Debt}\] \[\text{EVA} = \text{NOPAT} - (\text{Weighted Average Cost of Capital} \cdot \text{Invested Capital})\]EVA is mostly used to compare value creation across business units or companies and over time, and as a basis for management compensation. It is equivalent to (Return on Invested Capital - WACC) * Invested Capital, so a company with a high return on capital but a small capital base can create less EVA than a larger, less profitable one.
Also known as: EVA, economic profit.
Economic Value Added (EVA) in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_economic_value_added as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(
["V", "MA", "HD"],
api_key="FINANCIAL_MODELING_PREP_KEY",
start_date="2022-01-01",
end_date="2025-12-31",
)
toolkit.models.get_economic_value_added().xs("Economic Value Added", level=1)
Or, after setting up the Finance Toolkit MCP, ask:
How much economic value did Visa, Mastercard and Home Depot add from 2022 to 2025?
Which returns:
| 2022 | 2023 | 2024 | 2025 | |
|---|---|---|---|---|
| HD | 1.51584e+10 | 1.23683e+10 | 1.21347e+10 | nan |
| MA | 9.17363e+09 | 1.03441e+10 | 1.21321e+10 | 1.32974e+10 |
| V | 1.14101e+10 | 1.30222e+10 | 1.54505e+10 | 1.53159e+10 |
Parameters
get_economic_value_added accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
rounding | int | The number of decimals to round the results to. Defaults to None. | 2 |
growth | bool | Whether to calculate the growth of the values. Defaults to False. | True |
lag | int | list[int] | The lag to use for the growth calculation. Defaults to 1. | 4 |
standardize | bool | Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False. | True |
trailing | int | None | The trailing period to use for the calculation. Defaults to None. | 4 |
market_risk_premium | float | None | The annual equity risk premium the Cost of Equity uses. Defaults to None, which takes the equity risk premium of each company’s country (Damodaran’s Total Equity Risk Premium, see get_market_risk_premium) and, where that is not available, the benchmark’s average return above the risk-free rate over the data. | None, which takes the equity risk premium of each company's country (Damodaran's Total Equity Risk Premium, see get_market_risk_premium) and, where that is not available, the benchmark's average return above the risk-free rate over the data |
show_columns | list[str] | None | List of columns to show in the results. If None, all columns will be shown. Defaults to None. | ["Invested Capital", "Economic Value Added"] |