Market Value Added (MVA)
Market Value Added (MVA) is a measure of a company’s financial performance that represents the difference between the current market value of a company (both its equity and its debt) and the total capital that has historically been invested in it. It is the market-priced counterpart to Economic Value Added (EVA): where EVA measures a single period’s excess return over the cost of capital, MVA reflects the market’s cumulative, forward-looking verdict on all of a company’s expected future EVA.
The formula is as follows:
\[\text{Market Value of Equity} = \text{Share Price} \cdot \text{Total Shares Outstanding}\] \[\text{Invested Capital} = \text{Total Equity} + \text{Total Debt}\] \[\text{MVA} = (\text{Market Value of Equity} + \text{Market Value of Debt}) - \text{Invested Capital}\]Also known as: MVA, market value added.
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Calculate the Market Value Added (MVA) in Python
The Market Value Added (MVA) is available in the Models module of the open-source Finance Toolkit. Install it with:
pip install financetoolkit -U
Then call get_market_value_added as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(["AAPL", "MSFT"], api_key="FINANCIAL_MODELING_PREP_KEY")
toolkit.models.get_market_value_added().loc["AAPL"]
Which returns:
| 2021 | 2022 | 2023 | 2024 | 2025 | |
|---|---|---|---|---|---|
| Market Value of Equity | 2.92522e+12 | 2.08399e+12 | 3.00786e+12 | 3.83091e+12 | 4.06822e+12 |
| Market Value of Debt | 1.36522e+11 | 1.3248e+11 | 1.2393e+11 | 1.19059e+11 | 1.12377e+11 |
| Invested Capital | 1.93614e+11 | 1.91382e+11 | 1.84614e+11 | 1.81042e+11 | 1.8106e+11 |
| Market Value Added | 2.86813e+12 | 2.02509e+12 | 2.94718e+12 | 3.76893e+12 | 3.99954e+12 |
Parameters
get_market_value_added accepts the following parameters:
- diluted (bool, optional): Whether to use diluted shares in the calculation. Defaults to True.
- rounding (int, optional): The number of decimals to round the results to. Defaults to None.
- growth (bool, optional): Whether to calculate the growth of the values. Defaults to False.
- lag (int | list[int], optional): The lag to use for the growth calculation. Defaults to 1.
- standardize (bool, optional): Whether to standardize (Z-Score) the result. When combined with growth=True, standardizes the growth values instead of the raw values. Defaults to False.
- trailing (int | None, optional): The trailing period to use for the calculation. Defaults to None.
- show_columns (list[str] | None, optional): List of columns to show in the results. If None, all columns will be shown. Defaults to None.
Related Models
The Models module page introduces the module, and the sidebar lists all of its functions.