TES Co Beneish M-Score Historical Data
The historical data trend for TES 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.
TES Co Beneish M-Score Chart
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TES Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-1.81 |
-2.40 |
-2.03 |
-0.82 |
0.38 |
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TES Co Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.50 |
-2.83 |
-2.82 |
0.38 |
-1.95 |
Competitive Comparison of TES Co's Beneish M-Score
For the Semiconductors subindustry, TES 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.
TES Co's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, TES Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where TES Co's Beneish M-Score falls into.
TES 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 TES 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 * 1.8993 | + | 0.528 * 1.7785 | + | 0.404 * 0.7227 | + | 0.892 * 0.5237 | + | 0.115 * 0.9958 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.7026 | + | 4.679 * -0.017892 | - | 0.327 * 0.8954 |
| = | -1.95 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ₩20,020 Mil.
Revenue was 42169.448 + 26003.081 + 27705.446 + 56950.003 = ₩152,828 Mil.
Gross Profit was 7797.887 + -5491.129 + 190.748 + 14773.391 = ₩17,271 Mil.
Total Current Assets was ₩185,930 Mil.
Total Assets was ₩318,844 Mil.
Property, Plant and Equipment(Net PPE) was ₩66,288 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩5,444 Mil.
Selling, General, & Admin. Expense(SGA) was ₩13,398 Mil.
Total Current Liabilities was ₩20,088 Mil.
Long-Term Debt & Capital Lease Obligation was ₩59 Mil.
Net Income was 6899.754 + -7886.418 + -4061.145 + 13175.472 = ₩8,128 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -4978.205 + -9285.867 + -3414.734 + 31511.257 = ₩13,832 Mil.
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Total Receivables was ₩20,126 Mil.
Revenue was 36279.543 + 75357.614 + 91847.917 + 88317.168 = ₩291,802 Mil.
Gross Profit was 3334.391 + 14325.412 + 22741.603 + 18248.465 = ₩58,650 Mil.
Total Current Assets was ₩177,568 Mil.
Total Assets was ₩324,361 Mil.
Property, Plant and Equipment(Net PPE) was ₩53,006 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩4,334 Mil.
Selling, General, & Admin. Expense(SGA) was ₩15,024 Mil.
Total Current Liabilities was ₩22,731 Mil.
Long-Term Debt & Capital Lease Obligation was ₩158 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) |
| = | (20019.767 / 152827.978) | / | (20125.832 / 291802.242) |
| = | 0.130995 | / | 0.068971 |
| | = | 1.8993 |
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) |
| = | (58649.871 / 291802.242) | / | (17270.897 / 152827.978) |
| = | 0.200992 | / | 0.113009 |
| | = | 1.7785 |
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 - (185929.714 + 66287.832) / 318844.023) | / | (1 - (177568.28 + 53006.131) / 324361.297) |
| = | 0.208963 | / | 0.289143 |
| | = | 0.7227 |
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 |
| = | 152827.978 | / | 291802.242 |
| | = | 0.5237 |
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)) |
| = | (4333.756 / (4333.756 + 53006.131)) | / | (5444.386 / (5444.386 + 66287.832)) |
| = | 0.07558 | / | 0.075899 |
| | = | 0.9958 |
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) |
| = | (13397.907 / 152827.978) | / | (15024.499 / 291802.242) |
| = | 0.087667 | / | 0.051489 |
| | = | 1.7026 |
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) |
| = | ((58.576 + 20088.053) / 318844.023) | / | ((157.818 + 22730.865) / 324361.297) |
| = | 0.063186 | / | 0.070565 |
| | = | 0.8954 |
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 |
| = | (8127.663 - 0 | - | 13832.451) | / | 318844.023 |
| | = | -0.017892 |
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.
TES Co has a M-score of -1.95 suggests that the company is unlikely to be a manipulator.
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