KT&G Beneish M-Score Historical Data
The historical data trend for KT&G'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.
KT&G Beneish M-Score Chart
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KT&G Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.30 |
-2.41 |
-2.64 |
-2.13 |
-2.60 |
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KT&G 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 |
-2.60 |
-2.89 |
-2.84 |
-2.82 |
Competitive Comparison of KT&G's Beneish M-Score
For the Tobacco subindustry, KT&G'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.
KT&G's Beneish M-Score Distribution in the Tobacco Products Industry
For the Tobacco Products industry and Consumer Defensive sector, KT&G's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where KT&G's Beneish M-Score falls into.
KT&G 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 KT&G 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 * 0.7996 | + | 0.528 * 1.0021 | + | 0.404 * 0.8988 | + | 0.892 * 0.9941 | + | 0.115 * 1.1966 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9597 | + | 4.679 * -0.024239 | - | 0.327 * 1.095 |
| = | -2.82 |
* 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 ₩1,875,109 Mil.
Revenue was 1636347 + 1423774 + 1292261 + 1441433 = ₩5,793,815 Mil.
Gross Profit was 855428 + 714122 + 644208 + 621910 = ₩2,835,668 Mil.
Total Current Assets was ₩6,987,985 Mil.
Total Assets was ₩13,492,606 Mil.
Property, Plant and Equipment(Net PPE) was ₩2,487,204 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩246,348 Mil.
Selling, General, & Admin. Expense(SGA) was ₩835,722 Mil.
Total Current Liabilities was ₩3,129,534 Mil.
Long-Term Debt & Capital Lease Obligation was ₩759,849 Mil.
Net Income was 241243 + 312836 + 286346 + 117518 = ₩957,943 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 361435 + 206496 + 347187 + 369879 = ₩1,284,997 Mil.
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Total Receivables was ₩2,358,753 Mil.
Revenue was 1689510 + 1335995 + 1395670 + 1406742.862 = ₩5,827,918 Mil.
Gross Profit was 827117 + 650894 + 708294 + 672155.719 = ₩2,858,461 Mil.
Total Current Assets was ₩6,661,305 Mil.
Total Assets was ₩12,929,380 Mil.
Property, Plant and Equipment(Net PPE) was ₩1,984,986 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩239,922 Mil.
Selling, General, & Admin. Expense(SGA) was ₩875,913 Mil.
Total Current Liabilities was ₩2,990,425 Mil.
Long-Term Debt & Capital Lease Obligation was ₩413,267 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) |
| = | (1875109 / 5793815) | / | (2358753.089 / 5827917.862) |
| = | 0.32364 | / | 0.404733 |
| | = | 0.7996 |
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) |
| = | (2858460.719 / 5827917.862) | / | (2835668 / 5793815) |
| = | 0.490477 | / | 0.48943 |
| | = | 1.0021 |
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 - (6987985 + 2487204) / 13492606) | / | (1 - (6661304.837 + 1984985.511) / 12929379.976) |
| = | 0.29775 | / | 0.331268 |
| | = | 0.8988 |
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 |
| = | 5793815 | / | 5827917.862 |
| | = | 0.9941 |
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)) |
| = | (239922 / (239922 + 1984985.511)) | / | (246348 / (246348 + 2487204)) |
| = | 0.107835 | / | 0.09012 |
| | = | 1.1966 |
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) |
| = | (835722 / 5793815) | / | (875913.301 / 5827917.862) |
| = | 0.144244 | / | 0.150296 |
| | = | 0.9597 |
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) |
| = | ((759849 + 3129534) / 13492606) | / | ((413266.593 + 2990425.067) / 12929379.976) |
| = | 0.28826 | / | 0.263253 |
| | = | 1.095 |
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 |
| = | (957943 - 0 | - | 1284997) | / | 13492606 |
| | = | -0.024239 |
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.
KT&G has a M-score of -2.82 suggests that the company is unlikely to be a manipulator.
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