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 |
-2.36 |
-2.89 |
-2.57 |
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AppLovin Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
Mar25 |
| Beneish M-Score |
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-2.61 |
-2.61 |
-2.73 |
-2.57 |
-2.49 |
Competitive Comparison of AppLovin's Beneish M-Score
For the Advertising Agencies 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 Media - Diversified Industry
For the Media - Diversified industry and Communication Services 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 * 1.076 | + | 0.528 * 0.8993 | + | 0.404 * 0.8417 | + | 0.892 * 1.4163 | + | 0.115 * 1.0171 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7017 | + | 4.679 * -0.078109 | - | 0.327 * 1.0668 |
| = | -2.49 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was $1,578 Mil.
Revenue was 1484.021 + 1372.779 + 1198.235 + 1080.119 = $5,135 Mil.
Gross Profit was 1212.789 + 1052.327 + 928.576 + 797.572 = $3,991 Mil.
Total Current Assets was $2,367 Mil.
Total Assets was $5,707 Mil.
Property, Plant and Equipment(Net PPE) was $162 Mil.
Depreciation, Depletion and Amortization(DDA) was $416 Mil.
Selling, General, & Admin. Expense(SGA) was $999 Mil.
Total Current Liabilities was $1,409 Mil.
Long-Term Debt & Capital Lease Obligation was $3,510 Mil.
Net Income was 576.419 + 599.204 + 434.42 + 309.969 = $1,920 Mil.
Non Operating Income was -181.132 + 0 + 0 + 8.947 = $-172 Mil.
Cash Flow from Operations was 831.712 + 701.003 + 550.702 + 454.527 = $2,538 Mil.
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Total Receivables was $1,035 Mil.
Revenue was 1058.115 + 953.261 + 864.256 + 750.165 = $3,626 Mil.
Gross Profit was 763.967 + 679.654 + 599.207 + 491.59 = $2,534 Mil.
Total Current Assets was $1,608 Mil.
Total Assets was $5,263 Mil.
Property, Plant and Equipment(Net PPE) was $173 Mil.
Depreciation, Depletion and Amortization(DDA) was $473 Mil.
Selling, General, & Admin. Expense(SGA) was $1,005 Mil.
Total Current Liabilities was $763 Mil.
Long-Term Debt & Capital Lease Obligation was $3,490 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) |
| = | (1577.812 / 5135.154) | / | (1035.372 / 3625.797) |
| = | 0.307257 | / | 0.285557 |
| | = | 1.076 |
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) |
| = | (2534.418 / 3625.797) | / | (3991.264 / 5135.154) |
| = | 0.698996 | / | 0.777243 |
| | = | 0.8993 |
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 - (2367.334 + 161.655) / 5706.701) | / | (1 - (1607.888 + 172.994) / 5262.517) |
| = | 0.556839 | / | 0.661591 |
| | = | 0.8417 |
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 |
| = | 5135.154 | / | 3625.797 |
| | = | 1.4163 |
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)) |
| = | (473.467 / (473.467 + 172.994)) | / | (415.9 / (415.9 + 161.655)) |
| = | 0.732398 | / | 0.720105 |
| | = | 1.0171 |
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) |
| = | (998.666 / 5135.154) | / | (1004.841 / 3625.797) |
| = | 0.194476 | / | 0.277137 |
| | = | 0.7017 |
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) |
| = | ((3509.964 + 1409.224) / 5706.701) | / | ((3489.891 + 762.524) / 5262.517) |
| = | 0.862002 | / | 0.808057 |
| | = | 1.0668 |
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 |
| = | (1920.012 - -172.185 | - | 2537.944) | / | 5706.701 |
| | = | -0.078109 |
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 -2.49 suggests that the company is unlikely to be a manipulator.
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