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 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.40 |
-2.63 |
-2.23 |
-2.21 |
-2.87 |
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Aptiv Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.21 |
-2.25 |
-2.33 |
-2.58 |
-2.87 |
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 * 0.952 | + | 0.528 * 0.9111 | + | 0.404 * 1.0048 | + | 0.892 * 0.9831 | + | 0.115 * 0.9316 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0377 | + | 4.679 * -0.043695 | - | 0.327 * 1.2158 |
| = | -2.87 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was $3,622.00 Mil.
Revenue was 4907 + 4854 + 5051 + 4901 = $19,713.00 Mil.
Gross Profit was 962 + 903 + 968 + 878 = $3,711.00 Mil.
Total Current Assets was $7,826.00 Mil.
Total Assets was $23,458.00 Mil.
Property, Plant and Equipment(Net PPE) was $4,193.00 Mil.
Depreciation, Depletion and Amortization(DDA) was $964.00 Mil.
Selling, General, & Admin. Expense(SGA) was $1,465.00 Mil.
Total Current Liabilities was $5,131.00 Mil.
Long-Term Debt & Capital Lease Obligation was $8,255.00 Mil.
Net Income was 268 + 363 + 938 + 218 = $1,787.00 Mil.
Non Operating Income was -113 + -42 + 565 + -44 = $366.00 Mil.
Cash Flow from Operations was 1060 + 499 + 643 + 244 = $2,446.00 Mil.
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Total Receivables was $3,870.00 Mil.
Revenue was 4919 + 5114 + 5200 + 4818 = $20,051.00 Mil.
Gross Profit was 922 + 893 + 864 + 760 = $3,439.00 Mil.
Total Current Assets was $8,247.00 Mil.
Total Assets was $24,427.00 Mil.
Property, Plant and Equipment(Net PPE) was $4,325.00 Mil.
Depreciation, Depletion and Amortization(DDA) was $912.00 Mil.
Selling, General, & Admin. Expense(SGA) was $1,436.00 Mil.
Total Current Liabilities was $4,808.00 Mil.
Long-Term Debt & Capital Lease Obligation was $6,657.00 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) |
| = | (3622 / 19713) | / | (3870 / 20051) |
| = | 0.183737 | / | 0.193008 |
| | = | 0.952 |
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) |
| = | (3439 / 20051) | / | (3711 / 19713) |
| = | 0.171513 | / | 0.188251 |
| | = | 0.9111 |
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 - (7826 + 4193) / 23458) | / | (1 - (8247 + 4325) / 24427) |
| = | 0.487637 | / | 0.485324 |
| | = | 1.0048 |
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 |
| = | 19713 | / | 20051 |
| | = | 0.9831 |
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)) |
| = | (912 / (912 + 4325)) | / | (964 / (964 + 4193)) |
| = | 0.174146 | / | 0.18693 |
| | = | 0.9316 |
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) |
| = | (1465 / 19713) | / | (1436 / 20051) |
| = | 0.074316 | / | 0.071617 |
| | = | 1.0377 |
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) |
| = | ((8255 + 5131) / 23458) | / | ((6657 + 4808) / 24427) |
| = | 0.570637 | / | 0.469358 |
| | = | 1.2158 |
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 |
| = | (1787 - 366 | - | 2446) | / | 23458 |
| | = | -0.043695 |
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 -2.87 suggests that the company is unlikely to be a manipulator.
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