f-code Beneish M-Score Historical Data
The historical data trend for f-code'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.
f-code Beneish M-Score Chart
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f-code Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
- |
-1.45 |
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f-code Quarterly Data
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Dec19 |
Dec20 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
| Beneish M-Score |
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-1.71 |
-1.45 |
-1.45 |
-1.10 |
-0.86 |
Competitive Comparison of f-code's Beneish M-Score
For the Advertising Agencies subindustry, f-code'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.
f-code's Beneish M-Score Distribution in the Media - Diversified Industry
For the Media - Diversified industry and Communication Services sector, f-code's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where f-code's Beneish M-Score falls into.
f-code 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 f-code 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 * 0.8947 | + | 0.528 * 1.0277 | + | 0.404 * 1.4249 | + | 0.892 * 2.5416 | + | 0.115 * 2.2741 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7622 | + | 4.679 * -0.011989 | - | 0.327 * 0.9172 |
| = | -0.86 |
* 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 (Jun24) TTM: | Last Year (Jun23) TTM: |
Total Receivables was 円667 Mil.
Revenue was 1002.313 + 1035.356 + 901.608 + 716.163 = 円3,655 Mil.
Gross Profit was 566.796 + 634.831 + 501.645 + 423.864 = 円2,127 Mil.
Total Current Assets was 円8,143 Mil.
Total Assets was 円17,973 Mil.
Property, Plant and Equipment(Net PPE) was 円250 Mil.
Depreciation, Depletion and Amortization(DDA) was 円76 Mil.
Selling, General, & Admin. Expense(SGA) was 円1,136 Mil.
Total Current Liabilities was 円4,017 Mil.
Long-Term Debt & Capital Lease Obligation was 円6,035 Mil.
Net Income was 176.76 + 196.166 + 198.965 + 145.807 = 円718 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 194.274 + 157.525 + 242.592 + 338.791 = 円933 Mil.
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Total Receivables was 円293 Mil.
Revenue was 478.922 + 385.338 + 269.854 + 304.108 = 円1,438 Mil.
Gross Profit was 311.361 + 233.647 + 152.008 + 163.103 = 円860 Mil.
Total Current Assets was 円4,471 Mil.
Total Assets was 円7,187 Mil.
Property, Plant and Equipment(Net PPE) was 円28 Mil.
Depreciation, Depletion and Amortization(DDA) was 円32 Mil.
Selling, General, & Admin. Expense(SGA) was 円586 Mil.
Total Current Liabilities was 円1,271 Mil.
Long-Term Debt & Capital Lease Obligation was 円3,112 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) |
| = | (666.615 / 3655.44) | / | (293.13 / 1438.222) |
| = | 0.182362 | / | 0.203814 |
| | = | 0.8947 |
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) |
| = | (860.119 / 1438.222) | / | (2127.136 / 3655.44) |
| = | 0.598043 | / | 0.58191 |
| | = | 1.0277 |
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 - (8143.339 + 250.43) / 17972.734) | / | (1 - (4470.643 + 28.248) / 7187.245) |
| = | 0.532972 | / | 0.374045 |
| | = | 1.4249 |
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 |
| = | 3655.44 | / | 1438.222 |
| | = | 2.5416 |
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)) |
| = | (32 / (32 + 28.248)) | / | (76.315 / (76.315 + 250.43)) |
| = | 0.531138 | / | 0.233561 |
| | = | 2.2741 |
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) |
| = | (1136.019 / 3655.44) | / | (586.414 / 1438.222) |
| = | 0.310775 | / | 0.407735 |
| | = | 0.7622 |
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) |
| = | ((6034.855 + 4017.304) / 17972.734) | / | ((3111.613 + 1270.874) / 7187.245) |
| = | 0.5593 | / | 0.609759 |
| | = | 0.9172 |
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 |
| = | (717.698 - 0 | - | 933.182) | / | 17972.734 |
| | = | -0.011989 |
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.
f-code has a M-score of -0.86 signals that the company is likely to be a manipulator.
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