Lear Beneish M-Score Historical Data
The historical data trend for Lear'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.
Lear Beneish M-Score Chart
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Lear Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.42 |
-2.36 |
-2.66 |
-2.55 |
-2.66 |
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Lear 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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-2.55 |
-2.40 |
-2.52 |
-2.63 |
-2.66 |
Competitive Comparison of Lear's Beneish M-Score
For the Auto Parts subindustry, Lear'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.
Lear's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, Lear's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Lear's Beneish M-Score falls into.
Lear 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 Lear 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 * 0.9494 | + | 0.528 * 0.9259 | + | 0.404 * 0.9763 | + | 0.892 * 1.1233 | + | 0.115 * 0.9959 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9291 | + | 4.679 * -0.042319 | - | 0.327 * 1.0124 |
| = | -2.66 |
* 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 $3,681 Mil.
Revenue was 5841.2 + 5781 + 5999.2 + 5845.5 = $23,467 Mil.
Gross Profit was 405.2 + 418.2 + 457 + 430 = $1,710 Mil.
Total Current Assets was $7,637 Mil.
Total Assets was $14,696 Mil.
Property, Plant and Equipment(Net PPE) was $2,977 Mil.
Depreciation, Depletion and Amortization(DDA) was $604 Mil.
Selling, General, & Admin. Expense(SGA) was $715 Mil.
Total Current Liabilities was $5,667 Mil.
Long-Term Debt & Capital Lease Obligation was $2,743 Mil.
Net Income was 127.3 + 132.9 + 168.7 + 143.6 = $573 Mil.
Non Operating Income was -15.9 + -5.8 + -19.5 + -13.7 = $-55 Mil.
Cash Flow from Operations was 569.7 + 403.8 + 311.4 + -35.6 = $1,249 Mil.
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Total Receivables was $3,452 Mil.
Revenue was 5370.9 + 5241.2 + 5071 + 5208.4 = $20,892 Mil.
Gross Profit was 371.6 + 376.9 + 339.9 + 321.5 = $1,410 Mil.
Total Current Assets was $6,994 Mil.
Total Assets was $13,763 Mil.
Property, Plant and Equipment(Net PPE) was $2,854 Mil.
Depreciation, Depletion and Amortization(DDA) was $577 Mil.
Selling, General, & Admin. Expense(SGA) was $685 Mil.
Total Current Liabilities was $5,188 Mil.
Long-Term Debt & Capital Lease Obligation was $2,591 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) |
| = | (3681.2 / 23466.9) | / | (3451.9 / 20891.5) |
| = | 0.156868 | / | 0.16523 |
| | = | 0.9494 |
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) |
| = | (1409.9 / 20891.5) | / | (1710.4 / 23466.9) |
| = | 0.067487 | / | 0.072886 |
| | = | 0.9259 |
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 - (7636.9 + 2977.4) / 14695.5) | / | (1 - (6994.1 + 2854) / 13763) |
| = | 0.277718 | / | 0.284451 |
| | = | 0.9763 |
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 |
| = | 23466.9 | / | 20891.5 |
| | = | 1.1233 |
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)) |
| = | (576.5 / (576.5 + 2854)) | / | (604.4 / (604.4 + 2977.4)) |
| = | 0.168051 | / | 0.168742 |
| | = | 0.9959 |
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) |
| = | (714.7 / 23466.9) | / | (684.8 / 20891.5) |
| = | 0.030456 | / | 0.032779 |
| | = | 0.9291 |
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) |
| = | ((2742.6 + 5667.2) / 14695.5) | / | ((2591.2 + 5188.3) / 13763) |
| = | 0.57227 | / | 0.565247 |
| | = | 1.0124 |
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 |
| = | (572.5 - -54.9 | - | 1249.3) | / | 14695.5 |
| | = | -0.042319 |
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.
Lear has a M-score of -2.66 suggests that the company is unlikely to be a manipulator.
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