Grover Score
Calculates the Grover Score, a financial metric used to predict the likelihood of a company going bankrupt. It was developed by re-estimating the coefficients of a reduced-form Altman Z-Score and adding a Return on Assets term, using a sample that paired each of Altman’s original bankrupt firms with a matched non-bankrupt firm from the same industry and year.
The formula is as follows:
\[\text{Working Capital to Total Assets} = \text{Working Capital} / \text{Total Assets}\] \[\text{EBIT to Total Assets} = \text{EBIT} / \text{Total Assets}\] \[\text{Return on Assets} = \text{Net Income} / \text{Total Assets}\] \[\text{Grover Score} = 1.65 \cdot \text{Working Capital to Total Assets} + 3.404 \cdot \text{EBIT to Total Assets} - 0.016 \cdot \text{Return on Assets} + 0.057\]The Grover Score can be interpreted as follows:
- A Grover Score of -0.02 or lower indicates a high likelihood of bankruptcy.
- A Grover Score of 0.01 or higher indicates a low likelihood of bankruptcy (per some secondary sources), leaving a gray area in between the two thresholds.
Also known as: Grover Score, G-Score, bankruptcy prediction, financial distress score.
Grover Score in Python or via the MCP
Install the Finance Toolkit with:
pip install financetoolkit -U
Then call get_grover_score as shown below.
from financetoolkit import Toolkit
toolkit = Toolkit(
["F", "GM", "STLA"],
api_key="FINANCIAL_MODELING_PREP_KEY",
start_date="2021-01-01",
end_date="2025-12-31",
)
toolkit.models.get_grover_score().xs("Grover Score", level=1)
Or, after setting up the Finance Toolkit MCP, ask:
What was the Grover score of Ford, General Motors and Stellantis from 2021 to 2025?
Which returns:
| 2021 | 2022 | 2023 | 2024 | 2025 | |
|---|---|---|---|---|---|
| F | 0.2398 | 0.2688 | 0.2442 | 0.2194 | 0.1363 |
| GM | 0.2379 | 0.2474 | 0.2157 | 0.2846 | 0.1825 |
| STLA | 0.477 | 0.5941 | 0.5796 | 0.2001 | -0.3018 |
Parameters
get_grover_score 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, which is 4 on quarterly data (a trailing twelve months), as the score was estimated on yearly statements. | 4 |
show_columns | list[str] | None | List of columns to show in the results. If None, all columns will be shown. Defaults to None. | ["Return on Assets", "Grover Score"] |