Graham Number
Calculate the Graham Number, a conservative estimate of a stock’s fair value based on its earnings and book value, as devised by Benjamin Graham.
The Graham Number is intended as an upper bound on the price a defensive investor should pay for a stock. It is most meaningful for stable, profitable companies with positive book value - for companies with negative earnings or negative book value the result is not meaningful (the square root of a negative number is undefined and will show up as NaN).
The formula is as follows:
\[\text{Graham Number} = \sqrt{22.5 x \;\text{Earnings per Share}\; x \;\text{Book Value per Share}}\]The constant 22.5 is Graham’s limit of a price-to-earnings ratio of 15 times a price-to-book ratio of 1.5, so the Graham Number is the price at which the product of the two ratios reaches that limit. For companies whose value lies mostly in intangibles, or that buy back many shares, book value is small and the Graham Number sits far below the market price.
Also known as: Graham fair value.
Graham Number in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_graham_number as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(
["BAC", "C", "WFC"],
api_key="FINANCIAL_MODELING_PREP_KEY",
start_date="2021-01-01",
end_date="2025-12-31",
)
toolkit.models.get_graham_number()
Or, after setting up the Finance Toolkit MCP, ask:
What was the Graham number of Bank of America, Citigroup and Wells Fargo from 2021 to 2025?
Which returns:
| 2021 | 2022 | 2023 | 2024 | 2025 | |
|---|---|---|---|---|---|
| BAC | 47.9904 | 46.3468 | 47.4941 | 50.4045 | 56.4118 |
| C | 142.751 | 120.826 | 93.472 | 117.004 | 127.785 |
| WFC | 68.3912 | 55.5576 | 69.7188 | 74.7554 | 85.6834 |
Parameters
get_graham_number accepts the following parameters.
| Parameter | Type | Description | Example |
|---|---|---|---|
diluted | bool | Whether to use diluted shares in the calculation. Defaults to True. | False |
trailing | int | None | The trailing period to use for the calculation. Defaults to None, which uses 4 (the trailing twelve months of earnings) with quarterly data and a single period with yearly data. | 4 |
rounding | int | None | The number of decimals to round the results to. Defaults to None, which uses the rounding of the Toolkit (4 unless set otherwise). | 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 |