Denso Beneish M-Score Historical Data
The historical data trend for Denso'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.
Denso Beneish M-Score Chart
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Denso Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.72 |
-3.05 |
-2.44 |
-2.47 |
-2.55 |
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Denso 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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-2.56 |
-2.55 |
-2.54 |
-2.57 |
-2.74 |
Competitive Comparison of Denso's Beneish M-Score
For the Auto Parts subindustry, Denso'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.
Denso's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, Denso's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Denso's Beneish M-Score falls into.
Denso 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 Denso 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 * 0.9668 | + | 0.528 * 0.9087 | + | 0.404 * 1.2023 | + | 0.892 * 1.0829 | + | 0.115 * 1.0042 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2237 | + | 4.679 * -0.082539 | - | 0.327 * 0.9441 |
| = | -2.81 |
* 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 $8,424 Mil.
Revenue was 12789.081 + 12179.228 + 12117.169 + 13209.496 = $50,295 Mil.
Gross Profit was 2073.676 + 1853.644 + 1612.833 + 2093.468 = $7,634 Mil.
Total Current Assets was $23,846 Mil.
Total Assets was $57,782 Mil.
Property, Plant and Equipment(Net PPE) was $14,133 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,626 Mil.
Selling, General, & Admin. Expense(SGA) was $4,854 Mil.
Total Current Liabilities was $14,246 Mil.
Long-Term Debt & Capital Lease Obligation was $3,705 Mil.
Net Income was 46.527 + 564.53 + 604.564 + 874.07 = $2,090 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 1772.2 + 1373.702 + 2108.065 + 1604.969 = $6,859 Mil.
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Total Receivables was $8,046 Mil.
Revenue was 11974.728 + 11202.239 + 10562.772 + 12704.478 = $46,444 Mil.
Gross Profit was 1761.541 + 1535.535 + 1296.234 + 1812.116 = $6,405 Mil.
Total Current Assets was $22,897 Mil.
Total Assets was $52,505 Mil.
Property, Plant and Equipment(Net PPE) was $14,641 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,734 Mil.
Selling, General, & Admin. Expense(SGA) was $3,663 Mil.
Total Current Liabilities was $12,933 Mil.
Long-Term Debt & Capital Lease Obligation was $4,343 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) |
| = | (8424.263 / 50294.974) | / | (8046.019 / 46444.217) |
| = | 0.167497 | / | 0.17324 |
| | = | 0.9668 |
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) |
| = | (6405.426 / 46444.217) | / | (7633.621 / 50294.974) |
| = | 0.137917 | / | 0.151777 |
| | = | 0.9087 |
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 - (23845.758 + 14132.677) / 57782.041) | / | (1 - (22896.65 + 14641.114) / 52505.344) |
| = | 0.342729 | / | 0.285068 |
| | = | 1.2023 |
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 |
| = | 50294.974 | / | 46444.217 |
| | = | 1.0829 |
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)) |
| = | (2734.319 / (2734.319 + 14641.114)) | / | (2626.17 / (2626.17 + 14132.677)) |
| = | 0.157367 | / | 0.156704 |
| | = | 1.0042 |
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) |
| = | (4854.182 / 50294.974) | / | (3663.149 / 46444.217) |
| = | 0.096514 | / | 0.078872 |
| | = | 1.2237 |
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) |
| = | ((3704.782 + 14245.504) / 57782.041) | / | ((4343.26 + 12932.903) / 52505.344) |
| = | 0.310655 | / | 0.329036 |
| | = | 0.9441 |
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 |
| = | (2089.691 - 0 | - | 6858.936) | / | 57782.041 |
| | = | -0.082539 |
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.
Denso has a M-score of -2.81 suggests that the company is unlikely to be a manipulator.
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