mPlus Beneish M-Score Historical Data
The historical data trend for mPlus'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.
mPlus Beneish M-Score Chart
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mPlus Annual Data
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Trend |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.22 |
-1.67 |
5.54 |
-2.34 |
-2.91 |
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mPlus Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.44 |
-2.91 |
-2.36 |
-2.14 |
-1.45 |
Competitive Comparison of mPlus's Beneish M-Score
For the Electrical Equipment & Parts subindustry, mPlus'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.
mPlus's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, mPlus's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where mPlus's Beneish M-Score falls into.
mPlus 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 mPlus 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 * 1.1405 | + | 0.528 * 0.857 | + | 0.404 * 1.6486 | + | 0.892 * 0.829 | + | 0.115 * 1.2316 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1007 | + | 4.679 * 0.17774 | - | 0.327 * 0.9151 |
| = | -1.45 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was ₩38,126 Mil.
Revenue was 26621.108 + 18842.751 + 21571.117 + 144292.679 = ₩211,328 Mil.
Gross Profit was 7621.368 + 3044.853 + 6523.792 + 12900.574 = ₩30,091 Mil.
Total Current Assets was ₩267,504 Mil.
Total Assets was ₩336,808 Mil.
Property, Plant and Equipment(Net PPE) was ₩53,093 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,758 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,140 Mil.
Total Current Liabilities was ₩236,965 Mil.
Long-Term Debt & Capital Lease Obligation was ₩20,256 Mil.
Net Income was 2352.918 + 160.03 + 3697.493 + 4143.288 = ₩10,354 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 13136.647 + -36270.824 + -5438.272 + -20938.078 = ₩-49,511 Mil.
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Total Receivables was ₩40,328 Mil.
Revenue was 33562.441 + 149486.94 + 12709.548 + 59169.032 = ₩254,928 Mil.
Gross Profit was 7264.748 + 16238.756 + 3882.77 + 3722.301 = ₩31,109 Mil.
Total Current Assets was ₩368,466 Mil.
Total Assets was ₩424,182 Mil.
Property, Plant and Equipment(Net PPE) was ₩43,333 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩3,840 Mil.
Selling, General, & Admin. Expense(SGA) was ₩3,442 Mil.
Total Current Liabilities was ₩347,234 Mil.
Long-Term Debt & Capital Lease Obligation was ₩6,787 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) |
| = | (38125.853 / 211327.655) | / | (40327.517 / 254927.961) |
| = | 0.180411 | / | 0.158192 |
| | = | 1.1405 |
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) |
| = | (31108.575 / 254927.961) | / | (30090.587 / 211327.655) |
| = | 0.122029 | / | 0.142388 |
| | = | 0.857 |
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 - (267504.31 + 53092.951) / 336807.532) | / | (1 - (368465.929 + 43332.931) / 424182.024) |
| = | 0.048129 | / | 0.029193 |
| | = | 1.6486 |
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 |
| = | 211327.655 | / | 254927.961 |
| | = | 0.829 |
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)) |
| = | (3840.167 / (3840.167 + 43332.931)) | / | (3757.686 / (3757.686 + 53092.951)) |
| = | 0.081406 | / | 0.066098 |
| | = | 1.2316 |
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) |
| = | (3140.38 / 211327.655) | / | (3441.542 / 254927.961) |
| = | 0.01486 | / | 0.0135 |
| | = | 1.1007 |
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) |
| = | ((20255.568 + 236964.93) / 336807.532) | / | ((6786.956 + 347233.542) / 424182.024) |
| = | 0.763702 | / | 0.834596 |
| | = | 0.9151 |
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 |
| = | (10353.729 - 0 | - | -49510.527) | / | 336807.532 |
| | = | 0.17774 |
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.
mPlus has a M-score of -1.45 signals that the company is likely to be a manipulator.
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