Zigup Beneish M-Score Historical Data
The historical data trend for Zigup'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.
Zigup Beneish M-Score Chart
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Zigup Annual Data
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Apr15 |
Apr16 |
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Apr18 |
Apr19 |
Apr20 |
Apr21 |
Apr22 |
Apr23 |
Apr24 |
| Beneish M-Score |
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3.52 |
-2.64 |
-2.57 |
-2.25 |
-2.36 |
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Zigup Semi-Annual Data
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Oct14 |
Apr15 |
Oct15 |
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Apr18 |
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Apr19 |
Oct19 |
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Apr23 |
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Apr24 |
| Beneish M-Score |
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-2.57 |
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-2.25 |
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-2.36 |
Competitive Comparison of Zigup's Beneish M-Score
For the Rental & Leasing Services subindustry, Zigup'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.
Zigup's Beneish M-Score Distribution in the Business Services Industry
For the Business Services industry and Industrials sector, Zigup's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Zigup's Beneish M-Score falls into.
Zigup 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 Zigup 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 * 0.7754 | + | 0.528 * 1.2381 | + | 0.404 * 0.8874 | + | 0.892 * 1.2305 | + | 0.115 * 0.8869 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8721 | + | 4.679 * 0.006632 | - | 0.327 * 1.0075 |
| = | -2.36 |
* 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 (Apr24) TTM: | Last Year (Apr23) TTM: |
Total Receivables was £421 Mil.
Revenue was £1,833 Mil.
Gross Profit was £433 Mil.
Total Current Assets was £508 Mil.
Total Assets was £2,225 Mil.
Property, Plant and Equipment(Net PPE) was £1,483 Mil.
Depreciation, Depletion and Amortization(DDA) was £251 Mil.
Selling, General, & Admin. Expense(SGA) was £229 Mil.
Total Current Liabilities was £449 Mil.
Long-Term Debt & Capital Lease Obligation was £673 Mil.
Net Income was £125 Mil.
Gross Profit was £0 Mil.
Cash Flow from Operations was £110 Mil.
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Total Receivables was £441 Mil.
Revenue was £1,490 Mil.
Gross Profit was £436 Mil.
Total Current Assets was £525 Mil.
Total Assets was £2,107 Mil.
Property, Plant and Equipment(Net PPE) was £1,333 Mil.
Depreciation, Depletion and Amortization(DDA) was £196 Mil.
Selling, General, & Admin. Expense(SGA) was £214 Mil.
Total Current Liabilities was £409 Mil.
Long-Term Debt & Capital Lease Obligation was £644 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) |
| = | (421.032 / 1833.127) | / | (441.277 / 1489.746) |
| = | 0.22968 | / | 0.29621 |
| | = | 0.7754 |
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) |
| = | (435.573 / 1489.746) | / | (432.891 / 1833.127) |
| = | 0.292381 | / | 0.236149 |
| | = | 1.2381 |
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 - (508.47 + 1483.344) / 2225.166) | / | (1 - (524.887 + 1332.923) / 2106.779) |
| = | 0.104869 | / | 0.118175 |
| | = | 0.8874 |
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 |
| = | 1833.127 | / | 1489.746 |
| | = | 1.2305 |
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)) |
| = | (196.474 / (196.474 + 1332.923)) | / | (251.254 / (251.254 + 1483.344)) |
| = | 0.128465 | / | 0.144849 |
| | = | 0.8869 |
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) |
| = | (229.27 / 1833.127) | / | (213.658 / 1489.746) |
| = | 0.12507 | / | 0.143419 |
| | = | 0.8721 |
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) |
| = | ((672.546 + 448.78) / 2225.166) | / | ((644.484 + 409.281) / 2106.779) |
| = | 0.503929 | / | 0.500178 |
| | = | 1.0075 |
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 |
| = | (125.018 - 0 | - | 110.26) | / | 2225.166 |
| | = | 0.006632 |
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.
Zigup has a M-score of -2.36 suggests that the company is unlikely to be a manipulator.
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