JTEKT Beneish M-Score Historical Data
The historical data trend for JTEKT'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.
JTEKT Beneish M-Score Chart
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JTEKT Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.39 |
-2.83 |
-2.56 |
-2.57 |
-2.56 |
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JTEKT 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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-2.49 |
-2.56 |
-2.52 |
-2.66 |
-2.66 |
Competitive Comparison of JTEKT's Beneish M-Score
For the Auto Parts subindustry, JTEKT'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.
JTEKT's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, JTEKT's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where JTEKT's Beneish M-Score falls into.
JTEKT 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 JTEKT 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 * 0.9591 | + | 0.528 * 0.9335 | + | 0.404 * 1.0875 | + | 0.892 * 1.1433 | + | 0.115 * 1.0283 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9543 | + | 4.679 * -0.060753 | - | 0.327 * 0.9842 |
| = | -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 円336,733 Mil.
Revenue was 489595 + 476550 + 445681 + 453237 = 円1,865,063 Mil.
Gross Profit was 80591 + 62263 + 64724 + 80552 = 円288,130 Mil.
Total Current Assets was 円776,929 Mil.
Total Assets was 円1,529,939 Mil.
Property, Plant and Equipment(Net PPE) was 円469,833 Mil.
Depreciation, Depletion and Amortization(DDA) was 円70,186 Mil.
Selling, General, & Admin. Expense(SGA) was 円203,012 Mil.
Total Current Liabilities was 円455,642 Mil.
Long-Term Debt & Capital Lease Obligation was 円195,094 Mil.
Net Income was 13296 + 8130 + 14984 + 15944 = 円52,354 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 40643 + 47517 + 41644 + 15499 = 円145,303 Mil.
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Total Receivables was 円307,112 Mil.
Revenue was 420332 + 432890 + 371686 + 406445 = 円1,631,353 Mil.
Gross Profit was 62456 + 62943 + 49193 + 60672 = 円235,264 Mil.
Total Current Assets was 円697,364 Mil.
Total Assets was 円1,387,979 Mil.
Property, Plant and Equipment(Net PPE) was 円454,390 Mil.
Depreciation, Depletion and Amortization(DDA) was 円70,097 Mil.
Selling, General, & Admin. Expense(SGA) was 円186,081 Mil.
Total Current Liabilities was 円427,054 Mil.
Long-Term Debt & Capital Lease Obligation was 円172,779 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) |
| = | (336733 / 1865063) | / | (307112 / 1631353) |
| = | 0.180548 | / | 0.188256 |
| | = | 0.9591 |
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) |
| = | (235264 / 1631353) | / | (288130 / 1865063) |
| = | 0.144214 | / | 0.154488 |
| | = | 0.9335 |
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 - (776929 + 469833) / 1529939) | / | (1 - (697364 + 454390) / 1387979) |
| = | 0.18509 | / | 0.170193 |
| | = | 1.0875 |
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 |
| = | 1865063 | / | 1631353 |
| | = | 1.1433 |
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)) |
| = | (70097 / (70097 + 454390)) | / | (70186 / (70186 + 469833)) |
| = | 0.133649 | / | 0.12997 |
| | = | 1.0283 |
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) |
| = | (203012 / 1865063) | / | (186081 / 1631353) |
| = | 0.10885 | / | 0.114065 |
| | = | 0.9543 |
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) |
| = | ((195094 + 455642) / 1529939) | / | ((172779 + 427054) / 1387979) |
| = | 0.425335 | / | 0.432163 |
| | = | 0.9842 |
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 |
| = | (52354 - 0 | - | 145303) | / | 1529939 |
| | = | -0.060753 |
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.
JTEKT has a M-score of -2.66 suggests that the company is unlikely to be a manipulator.
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