Group 1 Automotive Beneish M-Score Historical Data
The historical data trend for Group 1 Automotive's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
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Group 1 Automotive Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.61 |
-3.03 |
-2.93 |
-2.15 |
-1.96 |
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Group 1 Automotive Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.15 |
-2.25 |
-2.12 |
-2.07 |
-1.96 |
Competitive Comparison
For the Auto & Truck Dealerships subindustry, Group 1 Automotive's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Group 1 Automotive Beneish M-Score Distribution
For the Vehicles & Parts industry and Consumer Cyclical sector, Group 1 Automotive's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Group 1 Automotive's Beneish M-Score falls into.
Group 1 Automotive Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Group 1 Automotive for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 1.1542 | + | 0.528 * 1.0817 | + | 0.404 * 0.9238 | + | 0.892 * 1.1018 | + | 0.115 * 1.0063 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9806 | + | 4.679 * 0.0571 | - | 0.327 * 0.9886 |
| = | -1.96 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $608 Mil.
Revenue was 4480 + 4705.1 + 4558.6 + 4130 = $17,874 Mil.
Gross Profit was 730.6 + 786.2 + 775.5 + 727.9 = $3,020 Mil.
Total Current Assets was $2,791 Mil.
Total Assets was $7,774 Mil.
Property, Plant and Equipment(Net PPE) was $2,465 Mil.
Depreciation, Depletion and Amortization(DDA) was $92 Mil.
Selling, General, & Admin. Expense(SGA) was $1,927 Mil.
Total Current Liabilities was $2,506 Mil.
Long-Term Debt & Capital Lease Obligation was $2,199 Mil.
Net Income was 108.7 + 163.9 + 170.5 + 158.1 = $601 Mil.
Non Operating Income was -25.2 + -4.8 + -1.8 + -1.1 = $-33 Mil.
Cash Flow from Operations was -202.3 + 153.5 + 95.6 + 143.4 = $190 Mil.
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Total Receivables was $478 Mil.
Revenue was 4068.9 + 4163.4 + 4145.3 + 3844.4 = $16,222 Mil.
Gross Profit was 719.4 + 752.6 + 768.4 + 724.7 = $2,965 Mil.
Total Current Assets was $1,985 Mil.
Total Assets was $6,718 Mil.
Property, Plant and Equipment(Net PPE) was $2,377 Mil.
Depreciation, Depletion and Amortization(DDA) was $89 Mil.
Selling, General, & Admin. Expense(SGA) was $1,783 Mil.
Total Current Liabilities was $1,921 Mil.
Long-Term Debt & Capital Lease Obligation was $2,191 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (607.5 / 17873.7) | / | (477.7 / 16222) |
| = | 0.033988 | / | 0.029448 |
| | = | 1.1542 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (2965.1 / 16222) | / | (3020.2 / 17873.7) |
| = | 0.182783 | / | 0.168975 |
| | = | 1.0817 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (2791.3 + 2465.2) / 7774.1) | / | (1 - (1985.3 + 2377.3) / 6717.5) |
| = | 0.323845 | / | 0.350562 |
| | = | 0.9238 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 17873.7 | / | 16222 |
| | = | 1.1018 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (89.3 / (89.3 + 2377.3)) | / | (92 / (92 + 2465.2)) |
| = | 0.036204 | / | 0.035977 |
| | = | 1.0063 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (1926.8 / 17873.7) | / | (1783.3 / 16222) |
| = | 0.107801 | / | 0.109931 |
| | = | 0.9806 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((2198.8 + 2505.7) / 7774.1) | / | ((2190.6 + 1921.4) / 6717.5) |
| = | 0.60515 | / | 0.612132 |
| | = | 0.9886 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (601.2 - -32.9 | - | 190.2) | / | 7774.1 |
| | = | 0.0571 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Group 1 Automotive has a M-score of -1.96 suggests that the company is unlikely to be a manipulator.
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