TSE Co Beneish M-Score Historical Data
The historical data trend for TSE 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.
TSE Co Beneish M-Score Chart
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TSE 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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-1.99 |
-3.05 |
-2.13 |
-2.38 |
-1.76 |
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TSE Co 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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-2.38 |
-2.79 |
-2.54 |
-2.27 |
-1.76 |
Competitive Comparison of TSE Co's Beneish M-Score
For the Semiconductor Equipment & Materials subindustry, TSE 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.
TSE Co's Beneish M-Score Distribution in the Semiconductors Industry
For the Semiconductors industry and Technology sector, TSE Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where TSE Co's Beneish M-Score falls into.
TSE 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 TSE 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 * 1.3081 | + | 0.528 * 2.1731 | + | 0.404 * 1.1107 | + | 0.892 * 0.7344 | + | 0.115 * 1.0103 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9525 | + | 4.679 * -0.005595 | - | 0.327 * 0.9197 |
| = | -1.76 |
* 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 ₩70,346 Mil.
Revenue was 70278.046 + 76939.713 + 57318.323 + 44611.608 = ₩249,148 Mil.
Gross Profit was 9654.147 + 15534.664 + 5497.846 + 2903.416 = ₩33,590 Mil.
Total Current Assets was ₩207,346 Mil.
Total Assets was ₩443,121 Mil.
Property, Plant and Equipment(Net PPE) was ₩184,409 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩26,311 Mil.
Selling, General, & Admin. Expense(SGA) was ₩15,884 Mil.
Total Current Liabilities was ₩65,333 Mil.
Long-Term Debt & Capital Lease Obligation was ₩10,000 Mil.
Net Income was 754.301 + 6198.352 + -3301.623 + -3530.12 = ₩121 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 3447.718 + 3496.754 + -3044.014 + -1300.48 = ₩2,600 Mil.
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Total Receivables was ₩73,228 Mil.
Revenue was 81592.852 + 89406.59 + 87320.895 + 80943.832 = ₩339,264 Mil.
Gross Profit was 13887.852 + 20994.111 + 32655.383 + 31859.457 = ₩99,397 Mil.
Total Current Assets was ₩228,247 Mil.
Total Assets was ₩435,836 Mil.
Property, Plant and Equipment(Net PPE) was ₩162,102 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩23,402 Mil.
Selling, General, & Admin. Expense(SGA) was ₩22,707 Mil.
Total Current Liabilities was ₩71,584 Mil.
Long-Term Debt & Capital Lease Obligation was ₩8,984 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) |
| = | (70345.639 / 249147.69) | / | (73227.698 / 339264.169) |
| = | 0.282345 | / | 0.215843 |
| | = | 1.3081 |
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) |
| = | (99396.803 / 339264.169) | / | (33590.073 / 249147.69) |
| = | 0.292978 | / | 0.13482 |
| | = | 2.1731 |
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 - (207346.004 + 184408.67) / 443121.341) | / | (1 - (228247.078 + 162102.075) / 435835.839) |
| = | 0.11592 | / | 0.104367 |
| | = | 1.1107 |
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 |
| = | 249147.69 | / | 339264.169 |
| | = | 0.7344 |
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)) |
| = | (23402.187 / (23402.187 + 162102.075)) | / | (26310.936 / (26310.936 + 184408.67)) |
| = | 0.126154 | / | 0.124862 |
| | = | 1.0103 |
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) |
| = | (15884.272 / 249147.69) | / | (22707.413 / 339264.169) |
| = | 0.063754 | / | 0.066931 |
| | = | 0.9525 |
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) |
| = | ((10000.276 + 65333.454) / 443121.341) | / | ((8984.213 + 71583.965) / 435835.839) |
| = | 0.170007 | / | 0.184859 |
| | = | 0.9197 |
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 |
| = | (120.91 - 0 | - | 2599.978) | / | 443121.341 |
| | = | -0.005595 |
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.
TSE Co has a M-score of -1.76 signals that the company is likely to be a manipulator.
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