KDDI Beneish M-Score Historical Data
The historical data trend for KDDI'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.
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KDDI Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.56 |
-2.76 |
-2.95 |
-2.77 |
-2.50 |
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KDDI 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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-2.75 |
-2.50 |
-2.55 |
-2.57 |
-2.60 |
Competitive Comparison
For the Telecom Services subindustry, KDDI'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.
KDDI Beneish M-Score Distribution
For the Telecommunication Services industry and Communication Services sector, KDDI's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where KDDI's Beneish M-Score falls into.
KDDI 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 KDDI 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 * 1.0529 | + | 0.528 * 1.0095 | + | 0.404 * 1.0847 | + | 0.892 * 0.9557 | + | 0.115 * 1.0833 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9562 | + | 4.679 * -0.045353 | - | 0.327 * 1.0875 |
| = | -2.66 |
* 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 $18,363 Mil.
Revenue was 10324.688 + 9783.165 + 9426.952 + 11138.868 = $40,674 Mil.
Gross Profit was 4363.074 + 4239.65 + 4213.37 + 4340.748 = $17,157 Mil.
Total Current Assets was $27,638 Mil.
Total Assets was $93,457 Mil.
Property, Plant and Equipment(Net PPE) was $21,945 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,864 Mil.
Selling, General, & Admin. Expense(SGA) was $9,910 Mil.
Total Current Liabilities was $36,166 Mil.
Long-Term Debt & Capital Lease Obligation was $13,625 Mil.
Net Income was 1228.616 + 1296.987 + 1251.736 + 1076.525 = $4,854 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 2486.236 + 3523.629 + 1313.727 + 1768.827 = $9,092 Mil.
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Total Receivables was $18,250 Mil.
Revenue was 10688.649 + 9695.124 + 10090.003 + 12083.938 = $42,558 Mil.
Gross Profit was 4502.909 + 4158.711 + 4688.953 + 4771.238 = $18,122 Mil.
Total Current Assets was $26,962 Mil.
Total Assets was $86,078 Mil.
Property, Plant and Equipment(Net PPE) was $21,861 Mil.
Depreciation, Depletion and Amortization(DDA) was $5,348 Mil.
Selling, General, & Admin. Expense(SGA) was $10,844 Mil.
Total Current Liabilities was $33,817 Mil.
Long-Term Debt & Capital Lease Obligation was $8,351 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) |
| = | (18363.498 / 40673.673) | / | (18249.54 / 42557.714) |
| = | 0.451484 | / | 0.428819 |
| | = | 1.0529 |
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) |
| = | (18121.811 / 42557.714) | / | (17156.842 / 40673.673) |
| = | 0.425817 | / | 0.421817 |
| | = | 1.0095 |
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 - (27637.62 + 21945.097) / 93456.673) | / | (1 - (26961.586 + 21861.456) / 86077.554) |
| = | 0.469458 | / | 0.432802 |
| | = | 1.0847 |
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 |
| = | 40673.673 | / | 42557.714 |
| | = | 0.9557 |
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)) |
| = | (5347.994 / (5347.994 + 21861.456)) | / | (4864.295 / (4864.295 + 21945.097)) |
| = | 0.196549 | / | 0.18144 |
| | = | 1.0833 |
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) |
| = | (9910.362 / 40673.673) | / | (10843.977 / 42557.714) |
| = | 0.243655 | / | 0.254806 |
| | = | 0.9562 |
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) |
| = | ((13624.75 + 36165.618) / 93456.673) | / | ((8350.574 + 33816.816) / 86077.554) |
| = | 0.532764 | / | 0.489877 |
| | = | 1.0875 |
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 |
| = | (4853.864 - 0 | - | 9092.419) | / | 93456.673 |
| | = | -0.045353 |
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.
KDDI has a M-score of -2.66 suggests that the company is unlikely to be a manipulator.
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