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.
KDDI Beneish M-Score Chart
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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 of KDDI's Beneish M-Score
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's Beneish M-Score Distribution in the Telecommunication Services Industry
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 * 1.048 | + | 0.528 * 1.0106 | + | 0.404 * 1.0847 | + | 0.892 * 1.0247 | + | 0.115 * 1.079 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9575 | + | 4.679 * -0.04545 | - | 0.327 * 1.0875 |
| = | -2.60 |
* 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 円2,644,004 Mil.
Revenue was 1486564 + 1446392 + 1332576 + 1488869 = 円5,754,401 Mil.
Gross Profit was 628202 + 626811 + 595594 + 580203 = 円2,430,810 Mil.
Total Current Assets was 円3,979,306 Mil.
Total Assets was 円13,456,032 Mil.
Property, Plant and Equipment(Net PPE) was 円3,159,688 Mil.
Depreciation, Depletion and Amortization(DDA) was 円688,209 Mil.
Selling, General, & Admin. Expense(SGA) was 円1,400,937 Mil.
Total Current Liabilities was 円5,207,180 Mil.
Long-Term Debt & Capital Lease Obligation was 円1,961,712 Mil.
Net Income was 176898 + 191753 + 176943 + 143893 = 円689,487 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 357972 + 520951 + 185706 + 236429 = 円1,301,058 Mil.
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Total Receivables was 円2,462,133 Mil.
Revenue was 1442057 + 1389159 + 1351676 + 1432882 = 円5,615,774 Mil.
Gross Profit was 607509 + 595878 + 628141 + 565761 = 円2,397,289 Mil.
Total Current Assets was 円3,637,517 Mil.
Total Assets was 円11,613,136 Mil.
Property, Plant and Equipment(Net PPE) was 円2,949,434 Mil.
Depreciation, Depletion and Amortization(DDA) was 円705,323 Mil.
Selling, General, & Admin. Expense(SGA) was 円1,427,819 Mil.
Total Current Liabilities was 円4,562,389 Mil.
Long-Term Debt & Capital Lease Obligation was 円1,126,616 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) |
| = | (2644004 / 5754401) | / | (2462133 / 5615774) |
| = | 0.459475 | / | 0.438432 |
| | = | 1.048 |
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) |
| = | (2397289 / 5615774) | / | (2430810 / 5754401) |
| = | 0.426885 | / | 0.422426 |
| | = | 1.0106 |
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 - (3979306 + 3159688) / 13456032) | / | (1 - (3637517 + 2949434) / 11613136) |
| = | 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 |
| = | 5754401 | / | 5615774 |
| | = | 1.0247 |
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)) |
| = | (705323 / (705323 + 2949434)) | / | (688209 / (688209 + 3159688)) |
| = | 0.192988 | / | 0.178853 |
| | = | 1.079 |
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) |
| = | (1400937 / 5754401) | / | (1427819 / 5615774) |
| = | 0.243455 | / | 0.254252 |
| | = | 0.9575 |
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) |
| = | ((1961712 + 5207180) / 13456032) | / | ((1126616 + 4562389) / 11613136) |
| = | 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 |
| = | (689487 - 0 | - | 1301058) | / | 13456032 |
| | = | -0.04545 |
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 -2.60 suggests that the company is unlikely to be a manipulator.
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