Kyocera Beneish M-Score Historical Data
The historical data trend for Kyocera'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.
Kyocera Beneish M-Score Chart
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Kyocera Annual Data
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Trend |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
Mar24 |
| Beneish M-Score |
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-2.65 |
-2.62 |
-2.45 |
-2.55 |
-2.65 |
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Kyocera 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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-2.55 |
-2.68 |
-2.65 |
-2.67 |
-2.65 |
Competitive Comparison of Kyocera's Beneish M-Score
For the Conglomerates subindustry, Kyocera'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.
Kyocera's Beneish M-Score Distribution in the Conglomerates Industry
For the Conglomerates industry and Industrials sector, Kyocera's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Kyocera's Beneish M-Score falls into.
Kyocera 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 Kyocera 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 * 0.9917 | + | 0.528 * 1.0098 | + | 0.404 * 1.0007 | + | 0.892 * 0.9262 | + | 0.115 * 1.0385 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0655 | + | 4.679 * -0.038547 | - | 0.327 * 1.0926 |
| = | -2.77 |
* 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 $2,618 Mil.
Revenue was 3414.456 + 3523.939 + 3421.624 + 3391.528 = $13,752 Mil.
Gross Profit was 887.64 + 975.868 + 975.116 + 958.226 = $3,797 Mil.
Total Current Assets was $9,607 Mil.
Total Assets was $29,805 Mil.
Property, Plant and Equipment(Net PPE) was $4,997 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,077 Mil.
Selling, General, & Admin. Expense(SGA) was $3,157 Mil.
Total Current Liabilities was $3,138 Mil.
Long-Term Debt & Capital Lease Obligation was $1,805 Mil.
Net Income was 71.473 + 235.301 + 129.156 + 264.52 = $700 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 569.108 + 503.801 + 232.744 + 543.711 = $1,849 Mil.
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Total Receivables was $2,850 Mil.
Revenue was 3731.999 + 3812.221 + 3630.67 + 3672.343 = $14,847 Mil.
Gross Profit was 933.847 + 1106.387 + 1033.735 + 1065.497 = $4,139 Mil.
Total Current Assets was $10,155 Mil.
Total Assets was $30,628 Mil.
Property, Plant and Equipment(Net PPE) was $4,864 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,097 Mil.
Selling, General, & Admin. Expense(SGA) was $3,199 Mil.
Total Current Liabilities was $3,449 Mil.
Long-Term Debt & Capital Lease Obligation was $1,200 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) |
| = | (2617.913 / 13751.547) | / | (2850.215 / 14847.233) |
| = | 0.190372 | / | 0.191969 |
| | = | 0.9917 |
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) |
| = | (4139.466 / 14847.233) | / | (3796.85 / 13751.547) |
| = | 0.278804 | / | 0.276103 |
| | = | 1.0098 |
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 - (9607.312 + 4996.923) / 29805.218) | / | (1 - (10154.634 + 4863.662) / 30628.433) |
| = | 0.510011 | / | 0.509662 |
| | = | 1.0007 |
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 |
| = | 13751.547 | / | 14847.233 |
| | = | 0.9262 |
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)) |
| = | (1097.219 / (1097.219 + 4863.662)) | / | (1076.501 / (1076.501 + 4996.923)) |
| = | 0.18407 | / | 0.177248 |
| | = | 1.0385 |
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) |
| = | (3156.839 / 13751.547) | / | (3198.868 / 14847.233) |
| = | 0.229562 | / | 0.215452 |
| | = | 1.0655 |
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) |
| = | ((1804.976 + 3138.389) / 29805.218) | / | ((1199.946 + 3449.492) / 30628.433) |
| = | 0.165856 | / | 0.151801 |
| | = | 1.0926 |
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 |
| = | (700.45 - 0 | - | 1849.364) | / | 29805.218 |
| | = | -0.038547 |
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.
Kyocera has a M-score of -2.77 suggests that the company is unlikely to be a manipulator.
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