AppLovin Beneish M-Score Historical Data
The historical data trend for AppLovin'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.
AppLovin Beneish M-Score Chart
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AppLovin Annual Data
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Trend |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
-2.01 |
-2.37 |
-2.87 |
-2.58 |
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AppLovin Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.87 |
-2.60 |
-2.60 |
-2.73 |
-2.58 |
Competitive Comparison of AppLovin's Beneish M-Score
For the Software - Application subindustry, AppLovin'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.
AppLovin's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, AppLovin's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where AppLovin's Beneish M-Score falls into.
AppLovin 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 AppLovin 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 * 1.0764 | + | 0.528 * 0.9003 | + | 0.404 * 0.8708 | + | 0.892 * 1.4345 | + | 0.115 * 1.0054 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7297 | + | 4.679 * -0.08911 | - | 0.327 * 1.0787 |
| = | -2.52 |
* 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 €1,351 Mil.
Revenue was 1311.004 + 1079.61 + 1003.431 + 973.466 = €4,368 Mil.
Gross Profit was 1004.972 + 836.647 + 740.944 + 702.85 = €3,285 Mil.
Total Current Assets was €2,208 Mil.
Total Assets was €5,605 Mil.
Property, Plant and Equipment(Net PPE) was €190 Mil.
Depreciation, Depletion and Amortization(DDA) was €416 Mil.
Selling, General, & Admin. Expense(SGA) was €955 Mil.
Total Current Liabilities was €1,010 Mil.
Long-Term Debt & Capital Lease Obligation was €3,382 Mil.
Net Income was 572.24 + 391.412 + 287.961 + 217.288 = €1,469 Mil.
Non Operating Income was 1.283 + 7.161 + 8.312 + 2.363 = €19 Mil.
Cash Flow from Operations was 669.458 + 496.183 + 422.256 + 361.357 = €1,949 Mil.
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Total Receivables was €875 Mil.
Revenue was 874.14 + 809.808 + 692.402 + 668.188 = €3,045 Mil.
Gross Profit was 623.243 + 561.457 + 453.738 + 423.518 = €2,062 Mil.
Total Current Assets was €1,482 Mil.
Total Assets was €4,914 Mil.
Property, Plant and Equipment(Net PPE) was €203 Mil.
Depreciation, Depletion and Amortization(DDA) was €454 Mil.
Selling, General, & Admin. Expense(SGA) was €912 Mil.
Total Current Liabilities was €866 Mil.
Long-Term Debt & Capital Lease Obligation was €2,704 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) |
| = | (1350.605 / 4367.511) | / | (874.644 / 3044.538) |
| = | 0.309239 | / | 0.287283 |
| | = | 1.0764 |
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) |
| = | (2061.956 / 3044.538) | / | (3285.413 / 4367.511) |
| = | 0.677264 | / | 0.752239 |
| | = | 0.9003 |
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 - (2208.141 + 189.662) / 5605.142) | / | (1 - (1482.021 + 203.153) / 4914.374) |
| = | 0.572214 | / | 0.657093 |
| | = | 0.8708 |
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 |
| = | 4367.511 | / | 3044.538 |
| | = | 1.4345 |
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)) |
| = | (453.755 / (453.755 + 203.153)) | / | (416.344 / (416.344 + 189.662)) |
| = | 0.690744 | / | 0.68703 |
| | = | 1.0054 |
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) |
| = | (955.045 / 4367.511) | / | (912.306 / 3044.538) |
| = | 0.21867 | / | 0.299653 |
| | = | 0.7297 |
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) |
| = | ((3382.219 + 1009.886) / 5605.142) | / | ((2704.06 + 865.76) / 4914.374) |
| = | 0.783585 | / | 0.726404 |
| | = | 1.0787 |
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 |
| = | (1468.901 - 19.119 | - | 1949.254) | / | 5605.142 |
| | = | -0.08911 |
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.
AppLovin has a M-score of -2.52 suggests that the company is unlikely to be a manipulator.
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