AB Akola Group Beneish M-Score Historical Data
The historical data trend for AB Akola Group'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.
AB Akola Group Beneish M-Score Chart
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AB Akola Group Annual Data
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Jun15 |
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Jun20 |
Jun21 |
Jun22 |
Jun23 |
Jun24 |
| Beneish M-Score |
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-3.08 |
-2.66 |
-1.33 |
-2.15 |
-3.11 |
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AB Akola Group Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
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Mar22 |
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Sep24 |
Dec24 |
| Beneish M-Score |
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-3.56 |
-3.48 |
-3.11 |
-3.00 |
-2.48 |
Competitive Comparison of AB Akola Group's Beneish M-Score
For the Conglomerates subindustry, AB Akola Group'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.
AB Akola Group's Beneish M-Score Distribution in the Conglomerates Industry
For the Conglomerates industry and Industrials sector, AB Akola Group's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AB Akola Group's Beneish M-Score falls into.
AB Akola Group 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 AB Akola Group 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 * 1.1851 | + | 0.528 * 0.6155 | + | 0.404 * 1.295 | + | 0.892 * 0.9467 | + | 0.115 * 1.3307 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.821 | + | 4.679 * -0.023477 | - | 0.327 * 1.0013 |
| = | -2.48 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was €256 Mil.
Revenue was 406.361 + 384.091 + 381.799 + 365.973 = €1,538 Mil.
Gross Profit was 42.736 + 44.095 + 47.396 + 27.017 = €161 Mil.
Total Current Assets was €662 Mil.
Total Assets was €987 Mil.
Property, Plant and Equipment(Net PPE) was €277 Mil.
Depreciation, Depletion and Amortization(DDA) was €25 Mil.
Selling, General, & Admin. Expense(SGA) was €34 Mil.
Total Current Liabilities was €510 Mil.
Long-Term Debt & Capital Lease Obligation was €132 Mil.
Net Income was 8.762 + 11.307 + 13.874 + -3.786 = €30 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0 Mil.
Cash Flow from Operations was 11.941 + -42.323 + 13.707 + 69.994 = €53 Mil.
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Total Receivables was €228 Mil.
Revenue was 338.396 + 420.726 + 499.258 + 366.433 = €1,625 Mil.
Gross Profit was 30.702 + 51.147 + 17.211 + 5.77 = €105 Mil.
Total Current Assets was €650 Mil.
Total Assets was €908 Mil.
Property, Plant and Equipment(Net PPE) was €224 Mil.
Depreciation, Depletion and Amortization(DDA) was €28 Mil.
Selling, General, & Admin. Expense(SGA) was €44 Mil.
Total Current Liabilities was €482 Mil.
Long-Term Debt & Capital Lease Obligation was €109 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) |
| = | (255.912 / 1538.224) | / | (228.104 / 1624.813) |
| = | 0.166368 | / | 0.140388 |
| | = | 1.1851 |
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) |
| = | (104.83 / 1624.813) | / | (161.244 / 1538.224) |
| = | 0.064518 | / | 0.104825 |
| | = | 0.6155 |
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 - (661.802 + 276.569) / 986.588) | / | (1 - (650.122 + 224.091) / 908.498) |
| = | 0.048872 | / | 0.037738 |
| | = | 1.295 |
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 |
| = | 1538.224 | / | 1624.813 |
| | = | 0.9467 |
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)) |
| = | (28.097 / (28.097 + 224.091)) | / | (25.272 / (25.272 + 276.569)) |
| = | 0.111413 | / | 0.083726 |
| | = | 1.3307 |
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) |
| = | (34.428 / 1538.224) | / | (44.296 / 1624.813) |
| = | 0.022382 | / | 0.027262 |
| | = | 0.821 |
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) |
| = | ((132.303 + 510.253) / 986.588) | / | ((108.778 + 482.156) / 908.498) |
| = | 0.651291 | / | 0.650452 |
| | = | 1.0013 |
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 |
| = | (30.157 - 0 | - | 53.319) | / | 986.588 |
| | = | -0.023477 |
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.
AB Akola Group has a M-score of -2.48 suggests that the company is unlikely to be a manipulator.
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