Calculate Tobin’s Q Ratio, a valuation metric developed by economist James Tobin that compares the market value of a company to the cost of replacing its assets.

The formula is as follows:

\[\text{Market Value of Equity} = \text{Share Price} \cdot \text{Total Shares Outstanding}\] \[\text{Tobin's} Q \text{Ratio} = (\text{Market Value of Equity} + \text{Total Liabilities}) / \text{Total Assets}\]

Tobin’s Q Ratio can be interpreted as follows:

  • A Q ratio greater than 1 indicates that the market values the company above the cost of replacing its assets, which can reflect growth expectations, unrecognized intangible value, or overvaluation.
  • A Q ratio less than 1 indicates that the market values the company below the cost of replacing its assets, which can reflect undervaluation or declining growth prospects.

Also known as: Tobin’s Q, Q ratio.

No programming experience? With the Finance Toolkit MCP server, AI assistants such as Claude and ChatGPT can calculate the Tobin’s Q Ratio for you. Just ask in plain English.

Calculate the Tobin’s Q Ratio in Python

The Tobin’s Q Ratio is available in the Models module of the open-source Finance Toolkit. Install it with:

pip install financetoolkit -U

Then call get_tobins_q_ratio as shown below.

from financetoolkit import Toolkit

toolkit = Toolkit(["AAPL", "MSFT"], api_key="FINANCIAL_MODELING_PREP_KEY")

toolkit.models.get_tobins_q_ratio().loc["AAPL"]

Which returns:

  2021 2022
Market Value of Equity 2.94327e+12 2.09689e+12
Total Liabilities 2.87912e+11 3.02083e+11
Total Assets 3.51002e+11 3.52755e+11
Tobin’s Q Ratio 9.2056 6.8007

Parameters

get_tobins_q_ratio 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.
Internal Growth Rate (IGR) Graham Number Free Cash Flow to Firm (FCFF) Free Cash Flow to Equity (FCFE) Two-Stage Dividend Discount Model Residual Income Market Value Added (MVA) Ohlson O-Score Zmijewski Score Springate Score Grover Score Fulmer H-Score

The Models module page introduces the module, and the sidebar lists all of its functions.

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