Angi Beneish M-Score Historical Data
The historical data trend for Angi'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.
Angi Beneish M-Score Chart
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Angi Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.04 |
-3.09 |
-1.71 |
-3.02 |
-3.21 |
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Angi Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-3.40 |
-3.21 |
-3.21 |
-2.92 |
-2.99 |
Competitive Comparison of Angi's Beneish M-Score
For the Internet Content & Information subindustry, Angi'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.
Angi's Beneish M-Score Distribution in the Interactive Media Industry
For the Interactive Media industry and Communication Services sector, Angi's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Angi's Beneish M-Score falls into.
Angi 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 Angi 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 * 0.7645 | + | 0.528 * 1.0147 | + | 0.404 * 1.0286 | + | 0.892 * 0.8871 | + | 0.115 * 0.9404 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9139 | + | 4.679 * -0.0507 | - | 0.327 * 0.9506 |
| = | -2.99 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $52 Mil.
Revenue was 296.719 + 315.134 + 305.39 + 300.433 = $1,218 Mil.
Gross Profit was 281.969 + 300.982 + 292.893 + 283.194 = $1,159 Mil.
Total Current Assets was $500 Mil.
Total Assets was $1,856 Mil.
Property, Plant and Equipment(Net PPE) was $86 Mil.
Depreciation, Depletion and Amortization(DDA) was $90 Mil.
Selling, General, & Admin. Expense(SGA) was $945 Mil.
Total Current Liabilities was $244 Mil.
Long-Term Debt & Capital Lease Obligation was $497 Mil.
Net Income was 35.161 + 3.76 + -1.631 + -5.56 = $32 Mil.
Non Operating Income was 0.885 + -0.516 + -0.225 + 0.838 = $1 Mil.
Cash Flow from Operations was 30.916 + 62.692 + 22.296 + 8.943 = $125 Mil.
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Total Receivables was $77 Mil.
Revenue was 351.231 + 351.587 + 355.497 + 314.378 = $1,373 Mil.
Gross Profit was 337.568 + 336.879 + 338.56 + 312.808 = $1,326 Mil.
Total Current Assets was $516 Mil.
Total Assets was $1,906 Mil.
Property, Plant and Equipment(Net PPE) was $121 Mil.
Depreciation, Depletion and Amortization(DDA) was $112 Mil.
Selling, General, & Admin. Expense(SGA) was $1,166 Mil.
Total Current Liabilities was $304 Mil.
Long-Term Debt & Capital Lease Obligation was $496 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) |
| = | (52.402 / 1217.676) | / | (77.269 / 1372.693) |
| = | 0.043034 | / | 0.05629 |
| | = | 0.7645 |
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) |
| = | (1325.815 / 1372.693) | / | (1159.038 / 1217.676) |
| = | 0.96585 | / | 0.951844 |
| | = | 1.0147 |
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 - (499.52 + 85.599) / 1856.007) | / | (1 - (515.796 + 121.244) / 1905.759) |
| = | 0.684743 | / | 0.665729 |
| | = | 1.0286 |
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 |
| = | 1217.676 | / | 1372.693 |
| | = | 0.8871 |
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)) |
| = | (112.417 / (112.417 + 121.244)) | / | (89.658 / (89.658 + 85.599)) |
| = | 0.481112 | / | 0.51158 |
| | = | 0.9404 |
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) |
| = | (945 / 1217.676) | / | (1165.691 / 1372.693) |
| = | 0.776069 | / | 0.8492 |
| | = | 0.9139 |
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) |
| = | ((496.639 + 243.602) / 1856.007) | / | ((495.853 + 303.717) / 1905.759) |
| = | 0.398835 | / | 0.419555 |
| | = | 0.9506 |
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 |
| = | (31.73 - 0.982 | - | 124.847) | / | 1856.007 |
| | = | -0.0507 |
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.
Angi has a M-score of -2.99 suggests that the company is unlikely to be a manipulator.
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