NSK Beneish M-Score Historical Data
The historical data trend for NSK'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.
NSK Beneish M-Score Chart
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NSK Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.75 |
-2.81 |
-2.40 |
-2.42 |
-2.73 |
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NSK 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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-2.72 |
-2.73 |
-2.97 |
-2.86 |
-2.75 |
Competitive Comparison of NSK's Beneish M-Score
For the Auto Parts subindustry, NSK'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.
NSK's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, NSK's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where NSK's Beneish M-Score falls into.
NSK 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 NSK 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 * 0.9196 | + | 0.528 * 1.1028 | + | 0.404 * 0.9836 | + | 0.892 * 1.0902 | + | 0.115 * 0.9919 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0197 | + | 4.679 * -0.077356 | - | 0.327 * 1.0798 |
| = | -2.82 |
* 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 $1,501 Mil.
Revenue was 1398.569 + 1342.237 + 1331.703 + 2672.569 = $6,745 Mil.
Gross Profit was 308.102 + 278.176 + 275.145 + 451.744 = $1,313 Mil.
Total Current Assets was $4,488 Mil.
Total Assets was $8,759 Mil.
Property, Plant and Equipment(Net PPE) was $2,464 Mil.
Depreciation, Depletion and Amortization(DDA) was $391 Mil.
Selling, General, & Admin. Expense(SGA) was $1,171 Mil.
Total Current Liabilities was $2,409 Mil.
Long-Term Debt & Capital Lease Obligation was $0 Mil.
Net Income was 28.219 + 10.748 + -6.572 + 56.006 = $88 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 107.861 + 38.202 + 481.508 + 138.362 = $766 Mil.
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Total Receivables was $1,497 Mil.
Revenue was 1442.644 + 1415.193 + 1369.501 + 1959.783 = $6,187 Mil.
Gross Profit was 329.237 + 312.232 + 309.976 + 376.952 = $1,328 Mil.
Total Current Assets was $4,266 Mil.
Total Assets was $8,904 Mil.
Property, Plant and Equipment(Net PPE) was $2,770 Mil.
Depreciation, Depletion and Amortization(DDA) was $435 Mil.
Selling, General, & Admin. Expense(SGA) was $1,053 Mil.
Total Current Liabilities was $2,268 Mil.
Long-Term Debt & Capital Lease Obligation was $0 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) |
| = | (1501.137 / 6745.078) | / | (1497.352 / 6187.121) |
| = | 0.222553 | / | 0.242011 |
| | = | 0.9196 |
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) |
| = | (1328.397 / 6187.121) | / | (1313.167 / 6745.078) |
| = | 0.214704 | / | 0.194685 |
| | = | 1.1028 |
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 - (4487.514 + 2463.782) / 8758.646) | / | (1 - (4266.389 + 2769.918) / 8904.271) |
| = | 0.20635 | / | 0.209783 |
| | = | 0.9836 |
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 |
| = | 6745.078 | / | 6187.121 |
| | = | 1.0902 |
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)) |
| = | (435.368 / (435.368 + 2769.918)) | / | (390.902 / (390.902 + 2463.782)) |
| = | 0.135828 | / | 0.136934 |
| | = | 0.9919 |
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) |
| = | (1170.573 / 6745.078) | / | (1052.972 / 6187.121) |
| = | 0.173545 | / | 0.170188 |
| | = | 1.0197 |
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) |
| = | ((0 + 2408.552) / 8758.646) | / | ((0 + 2267.698) / 8904.271) |
| = | 0.274991 | / | 0.254675 |
| | = | 1.0798 |
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 |
| = | (88.401 - 0 | - | 765.933) | / | 8758.646 |
| | = | -0.077356 |
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.
NSK has a M-score of -2.82 suggests that the company is unlikely to be a manipulator.
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