Ford Motor Co Beneish M-Score Historical Data
The historical data trend for Ford Motor Co'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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Ford Motor Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.70 |
-2.79 |
-3.12 |
-2.23 |
-2.37 |
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Ford Motor Co 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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-2.23 |
-2.34 |
-2.30 |
-2.36 |
-2.37 |
Competitive Comparison
For the Auto Manufacturers subindustry, Ford Motor Co'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.
Ford Motor Co Beneish M-Score Distribution
For the Vehicles & Parts industry and Consumer Cyclical sector, Ford Motor Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Ford Motor Co's Beneish M-Score falls into.
Ford Motor Co 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 Ford Motor Co 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 * 1.0219 | + | 0.528 * 1.184 | + | 0.404 * 1.0572 | + | 0.892 * 1.1147 | + | 0.115 * 1.0283 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8817 | + | 4.679 * -0.032311 | - | 0.327 * 1.015 |
| = | -2.37 |
* 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 $62,026 Mil.
Revenue was 45962 + 43801 + 44954 + 41474 = $176,191 Mil.
Gross Profit was 2530 + 3800 + 5211 + 4619 = $16,160 Mil.
Total Current Assets was $121,481 Mil.
Total Assets was $273,310 Mil.
Property, Plant and Equipment(Net PPE) was $62,205 Mil.
Depreciation, Depletion and Amortization(DDA) was $6,523 Mil.
Selling, General, & Admin. Expense(SGA) was $10,702 Mil.
Total Current Liabilities was $101,531 Mil.
Long-Term Debt & Capital Lease Obligation was $100,957 Mil.
Net Income was -526 + 1199 + 1917 + 1757 = $4,347 Mil.
Non Operating Income was -1685 + 174 + -239 + 10 = $-1,740 Mil.
Cash Flow from Operations was 2492 + 4591 + 5035 + 2800 = $14,918 Mil.
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Total Receivables was $54,449 Mil.
Revenue was 43999 + 39392 + 40190 + 34476 = $158,057 Mil.
Gross Profit was 4103 + 3351 + 5627 + 4083 = $17,164 Mil.
Total Current Assets was $116,476 Mil.
Total Assets was $255,884 Mil.
Property, Plant and Equipment(Net PPE) was $60,037 Mil.
Depreciation, Depletion and Amortization(DDA) was $6,493 Mil.
Selling, General, & Admin. Expense(SGA) was $10,888 Mil.
Total Current Liabilities was $96,866 Mil.
Long-Term Debt & Capital Lease Obligation was $89,906 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) |
| = | (62026 / 176191) | / | (54449 / 158057) |
| = | 0.352038 | / | 0.34449 |
| | = | 1.0219 |
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) |
| = | (17164 / 158057) | / | (16160 / 176191) |
| = | 0.108594 | / | 0.091719 |
| | = | 1.184 |
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 - (121481 + 62205) / 273310) | / | (1 - (116476 + 60037) / 255884) |
| = | 0.327921 | / | 0.310184 |
| | = | 1.0572 |
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 |
| = | 176191 | / | 158057 |
| | = | 1.1147 |
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)) |
| = | (6493 / (6493 + 60037)) | / | (6523 / (6523 + 62205)) |
| = | 0.097595 | / | 0.09491 |
| | = | 1.0283 |
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) |
| = | (10702 / 176191) | / | (10888 / 158057) |
| = | 0.060741 | / | 0.068887 |
| | = | 0.8817 |
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) |
| = | ((100957 + 101531) / 273310) | / | ((89906 + 96866) / 255884) |
| = | 0.740873 | / | 0.729909 |
| | = | 1.015 |
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 |
| = | (4347 - -1740 | - | 14918) | / | 273310 |
| | = | -0.032311 |
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.
Ford Motor Co has a M-score of -2.37 suggests that the company is unlikely to be a manipulator.
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