KT Beneish M-Score Historical Data
The historical data trend for KT'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 Beneish M-Score Chart
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KT Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.77 |
-3.17 |
-2.90 |
-2.54 |
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KT Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
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Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
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Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.54 |
-2.65 |
-2.75 |
-2.56 |
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Competitive Comparison of KT's Beneish M-Score
For the Telecom Services subindustry, KT'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's Beneish M-Score Distribution in the Telecommunication Services Industry
For the Telecommunication Services industry and Communication Services sector, KT's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where KT's Beneish M-Score falls into.
KT 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 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 * 1.4508 | + | 0.528 * 0.961 | + | 0.404 * 0.9785 | + | 0.892 * 0.9544 | + | 0.115 * 0.9512 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0268 | + | 4.679 * -0.083433 | - | 0.327 * 1.0477 |
| = | -2.55 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was R$29,410 Mil.
Revenue was 24790.691 + 24497.721 + 25698.405 + 26648.67 = R$101,635 Mil.
Gross Profit was 15626.451 + 16293.86 + 16122.624 + 16083.253 = R$64,126 Mil.
Total Current Assets was R$57,450 Mil.
Total Assets was R$162,773 Mil.
Property, Plant and Equipment(Net PPE) was R$58,995 Mil.
Depreciation, Depletion and Amortization(DDA) was R$14,562 Mil.
Selling, General, & Admin. Expense(SGA) was R$28,678 Mil.
Total Current Liabilities was R$49,891 Mil.
Long-Term Debt & Capital Lease Obligation was R$29,393 Mil.
Net Income was 978.27 + 1476.156 + 1182.944 + 972.937 = R$4,610 Mil.
Non Operating Income was 106.693 + -48.894 + -79.552 + -202.105 = R$-224 Mil.
Cash Flow from Operations was 6610.123 + 6807.344 + 3422.395 + 1574.938 = R$18,415 Mil.
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Total Receivables was R$21,240 Mil.
Revenue was 24322.909 + 24942.624 + 25589.204 + 31637.908 = R$106,493 Mil.
Gross Profit was 15009.191 + 15497.587 + 16364.968 + 17699.404 = R$64,571 Mil.
Total Current Assets was R$48,976 Mil.
Total Assets was R$152,653 Mil.
Property, Plant and Equipment(Net PPE) was R$59,276 Mil.
Depreciation, Depletion and Amortization(DDA) was R$13,751 Mil.
Selling, General, & Admin. Expense(SGA) was R$29,263 Mil.
Total Current Liabilities was R$39,743 Mil.
Long-Term Debt & Capital Lease Obligation was R$31,223 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) |
| = | (29409.865 / 101635.487) | / | (21239.842 / 106492.645) |
| = | 0.289366 | / | 0.199449 |
| | = | 1.4508 |
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) |
| = | (64571.15 / 106492.645) | / | (64126.188 / 101635.487) |
| = | 0.606344 | / | 0.630943 |
| | = | 0.961 |
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 - (57450.054 + 58994.519) / 162773.335) | / | (1 - (48975.668 + 59275.572) / 152652.822) |
| = | 0.284621 | / | 0.290866 |
| | = | 0.9785 |
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 |
| = | 101635.487 | / | 106492.645 |
| | = | 0.9544 |
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)) |
| = | (13750.844 / (13750.844 + 59275.572)) | / | (14561.574 / (14561.574 + 58994.519)) |
| = | 0.1883 | / | 0.197966 |
| | = | 0.9512 |
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) |
| = | (28678.094 / 101635.487) | / | (29263.39 / 106492.645) |
| = | 0.282166 | / | 0.274793 |
| | = | 1.0268 |
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) |
| = | ((29392.856 + 49890.758) / 162773.335) | / | ((31222.541 + 39743.223) / 152652.822) |
| = | 0.48708 | / | 0.464883 |
| | = | 1.0477 |
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 |
| = | (4610.307 - -223.858 | - | 18414.8) | / | 162773.335 |
| | = | -0.083433 |
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 has a M-score of -2.55 suggests that the company is unlikely to be a manipulator.
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