Neuromeka Co Beneish M-Score Historical Data
The historical data trend for Neuromeka Co'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.
Neuromeka Co Beneish M-Score Chart
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Neuromeka Co Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
1.36 |
5.28 |
-2.07 |
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Neuromeka Co Quarterly Data
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Dec17 |
Dec18 |
Dec19 |
Dec20 |
Jun21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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5.28 |
7.17 |
7.48 |
6.65 |
-2.07 |
Competitive Comparison of Neuromeka Co's Beneish M-Score
For the Specialty Industrial Machinery subindustry, Neuromeka Co'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.
Neuromeka Co's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Neuromeka Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Neuromeka Co's Beneish M-Score falls into.
Neuromeka Co 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 Neuromeka Co 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 * 0.6787 | + | 0.528 * 0.5426 | + | 0.404 * 1.0482 | + | 0.892 * 1.8387 | + | 0.115 * 0.8131 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9405 | + | 4.679 * 0.054266 | - | 0.327 * 1.1832 |
| = | -2.07 |
* 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 ₩9,400 Mil.
Revenue was 8054.344 + 6231.66 + 7344.346 + 3639.055 = ₩25,269 Mil.
Gross Profit was 772.025 + 914.301 + 1663.608 + 789.362 = ₩4,139 Mil.
Total Current Assets was ₩42,380 Mil.
Total Assets was ₩95,230 Mil.
Property, Plant and Equipment(Net PPE) was ₩25,871 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩2,322 Mil.
Selling, General, & Admin. Expense(SGA) was ₩14,622 Mil.
Total Current Liabilities was ₩58,241 Mil.
Long-Term Debt & Capital Lease Obligation was ₩26,083 Mil.
Net Income was -4029.902 + -6785.248 + -227.501 + -5719.964 = ₩-16,763 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -1897.055 + -8865.481 + -4951.792 + -6215.988 = ₩-21,930 Mil.
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Total Receivables was ₩7,532 Mil.
Revenue was 6614.663 + 3089.037 + 3071.311 + 967.96 = ₩13,743 Mil.
Gross Profit was 282.067 + 331.539 + 185.702 + 422.212 = ₩1,222 Mil.
Total Current Assets was ₩55,824 Mil.
Total Assets was ₩95,721 Mil.
Property, Plant and Equipment(Net PPE) was ₩14,027 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩1,007 Mil.
Selling, General, & Admin. Expense(SGA) was ₩8,456 Mil.
Total Current Liabilities was ₩50,801 Mil.
Long-Term Debt & Capital Lease Obligation was ₩20,837 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) |
| = | (9400.234 / 25269.405) | / | (7532.154 / 13742.971) |
| = | 0.372001 | / | 0.548073 |
| | = | 0.6787 |
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) |
| = | (1221.52 / 13742.971) | / | (4139.296 / 25269.405) |
| = | 0.088883 | / | 0.163807 |
| | = | 0.5426 |
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 - (42380.015 + 25871.146) / 95229.547) | / | (1 - (55823.536 + 14026.632) / 95720.977) |
| = | 0.283298 | / | 0.270273 |
| | = | 1.0482 |
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 |
| = | 25269.405 | / | 13742.971 |
| | = | 1.8387 |
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)) |
| = | (1006.55 / (1006.55 + 14026.632)) | / | (2321.562 / (2321.562 + 25871.146)) |
| = | 0.066955 | / | 0.082346 |
| | = | 0.8131 |
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) |
| = | (14621.631 / 25269.405) | / | (8455.524 / 13742.971) |
| = | 0.57863 | / | 0.615262 |
| | = | 0.9405 |
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) |
| = | ((26082.505 + 58241.461) / 95229.547) | / | ((20836.913 + 50800.674) / 95720.977) |
| = | 0.885481 | / | 0.7484 |
| | = | 1.1832 |
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 |
| = | (-16762.615 - 0 | - | -21930.316) | / | 95229.547 |
| | = | 0.054266 |
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.
Neuromeka Co has a M-score of -2.07 suggests that the company is unlikely to be a manipulator.
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