T K Beneish M-Score Historical Data
The historical data trend for T K'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.
T K Beneish M-Score Chart
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T K Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.07 |
-3.29 |
-1.67 |
-2.61 |
-2.27 |
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T K 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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-2.57 |
-2.44 |
-2.41 |
-2.27 |
-2.58 |
Competitive Comparison of T K's Beneish M-Score
For the Metal Fabrication subindustry, T K'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.
T K's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, T K's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where T K's Beneish M-Score falls into.
T K 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 T K 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 * 0.7752 | + | 0.528 * 1.1584 | + | 0.404 * 1.1887 | + | 0.892 * 1.0595 | + | 0.115 * 1.051 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9102 | + | 4.679 * -0.037507 | - | 0.327 * 0.84 |
| = | -2.58 |
* 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 ₩63,864 Mil.
Revenue was 73365.321 + 71340.333 + 74590.255 + 82223.61 = ₩301,520 Mil.
Gross Profit was 19959.831 + 15809.022 + 19900.408 + 26143.174 = ₩81,812 Mil.
Total Current Assets was ₩311,867 Mil.
Total Assets was ₩645,188 Mil.
Property, Plant and Equipment(Net PPE) was ₩181,331 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩9,307 Mil.
Selling, General, & Admin. Expense(SGA) was ₩18,021 Mil.
Total Current Liabilities was ₩40,906 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,614 Mil.
Net Income was 16191.872 + 7161.49 + 11490.105 + 17036.942 = ₩51,880 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 30487.902 + 9110.224 + 18769.41 + 17711.67 = ₩76,079 Mil.
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Total Receivables was ₩77,759 Mil.
Revenue was 83913.27 + 76253.649 + 67935.292 + 56489.032 = ₩284,591 Mil.
Gross Profit was 27658.43 + 23031.17 + 20505.909 + 18258.613 = ₩89,454 Mil.
Total Current Assets was ₩317,109 Mil.
Total Assets was ₩604,181 Mil.
Property, Plant and Equipment(Net PPE) was ₩167,338 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩9,051 Mil.
Selling, General, & Admin. Expense(SGA) was ₩18,688 Mil.
Total Current Liabilities was ₩45,856 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,545 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) |
| = | (63864.403 / 301519.519) | / | (77759.231 / 284591.243) |
| = | 0.211809 | / | 0.273231 |
| | = | 0.7752 |
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) |
| = | (89454.122 / 284591.243) | / | (81812.435 / 301519.519) |
| = | 0.314325 | / | 0.271334 |
| | = | 1.1584 |
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 - (311867.175 + 181331.071) / 645187.971) | / | (1 - (317108.744 + 167338.364) / 604180.572) |
| = | 0.235574 | / | 0.198175 |
| | = | 1.1887 |
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 |
| = | 301519.519 | / | 284591.243 |
| | = | 1.0595 |
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)) |
| = | (9051.153 / (9051.153 + 167338.364)) | / | (9307.095 / (9307.095 + 181331.071)) |
| = | 0.051313 | / | 0.048821 |
| | = | 1.051 |
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) |
| = | (18020.739 / 301519.519) | / | (18688.068 / 284591.243) |
| = | 0.059766 | / | 0.065666 |
| | = | 0.9102 |
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) |
| = | ((1613.683 + 40906.495) / 645187.971) | / | ((1545.315 + 45856.329) / 604180.572) |
| = | 0.065904 | / | 0.078456 |
| | = | 0.84 |
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 |
| = | (51880.409 - 0 | - | 76079.206) | / | 645187.971 |
| | = | -0.037507 |
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.
T K has a M-score of -2.58 suggests that the company is unlikely to be a manipulator.
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