Aptiv Beneish M-Score Historical Data
The historical data trend for Aptiv'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.
Aptiv Beneish M-Score Chart
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Aptiv Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.67 |
-2.40 |
-2.63 |
-2.23 |
-2.21 |
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Aptiv 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 |
-2.25 |
-2.30 |
-2.10 |
-2.21 |
Competitive Comparison of Aptiv's Beneish M-Score
For the Auto Parts subindustry, Aptiv'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.
Aptiv's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, Aptiv's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Aptiv's Beneish M-Score falls into.
Aptiv 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 Aptiv 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 * 0.9175 | + | 0.528 * 0.8814 | + | 0.404 * 1.046 | + | 0.892 * 1.1158 | + | 0.115 * 0.9272 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1021 | + | 4.679 * 0.05417 | - | 0.327 * 0.879 |
| = | -2.23 |
* 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 €3,549 Mil.
Revenue was 4510.723 + 4791.818 + 4799.6 + 4500.012 = €18,602 Mil.
Gross Profit was 845.474 + 836.741 + 797.472 + 709.84 = €3,190 Mil.
Total Current Assets was €7,562 Mil.
Total Assets was €22,400 Mil.
Property, Plant and Equipment(Net PPE) was €3,966 Mil.
Depreciation, Depletion and Amortization(DDA) was €846 Mil.
Selling, General, & Admin. Expense(SGA) was €1,332 Mil.
Total Current Liabilities was €4,409 Mil.
Long-Term Debt & Capital Lease Obligation was €6,104 Mil.
Net Income was 829.885 + 1526.373 + 223.366 + 151.308 = €2,731 Mil.
Non Operating Income was -126.546 + -29.984 + -50.765 + -31.756 = €-239 Mil.
Cash Flow from Operations was 572.208 + 699.002 + 493.805 + -8.406 = €1,757 Mil.
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Total Receivables was €3,466 Mil.
Revenue was 4380.16 + 4660.14 + 3837.922 + 3793.624 = €16,672 Mil.
Gross Profit was 767.472 + 800.93 + 416.24 + 534.812 = €2,519 Mil.
Total Current Assets was €7,348 Mil.
Total Assets was €20,658 Mil.
Property, Plant and Equipment(Net PPE) was €3,725 Mil.
Depreciation, Depletion and Amortization(DDA) was €725 Mil.
Selling, General, & Admin. Expense(SGA) was €1,083 Mil.
Total Current Liabilities was €4,593 Mil.
Long-Term Debt & Capital Lease Obligation was €6,439 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) |
| = | (3548.79 / 18602.153) | / | (3466.368 / 16671.846) |
| = | 0.190773 | / | 0.207917 |
| | = | 0.9175 |
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) |
| = | (2519.454 / 16671.846) | / | (3189.527 / 18602.153) |
| = | 0.15112 | / | 0.17146 |
| | = | 0.8814 |
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 - (7562.499 + 3966.025) / 22399.559) | / | (1 - (7348.096 + 3725.024) / 20658.496) |
| = | 0.485324 | / | 0.463992 |
| | = | 1.046 |
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 |
| = | 18602.153 | / | 16671.846 |
| | = | 1.1158 |
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)) |
| = | (725.378 / (725.378 + 3725.024)) | / | (845.84 / (845.84 + 3966.025)) |
| = | 0.162992 | / | 0.175782 |
| | = | 0.9272 |
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) |
| = | (1331.944 / 18602.153) | / | (1083.13 / 16671.846) |
| = | 0.071602 | / | 0.064968 |
| | = | 1.1021 |
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) |
| = | ((6104.469 + 4408.936) / 22399.559) | / | ((6439.024 + 4592.56) / 20658.496) |
| = | 0.469358 | / | 0.533997 |
| | = | 0.879 |
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 |
| = | (2730.932 - -239.051 | - | 1756.609) | / | 22399.559 |
| | = | 0.05417 |
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.
Aptiv has a M-score of -2.23 suggests that the company is unlikely to be a manipulator.
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