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 |
| Beneish M-Score |
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- |
- |
-2.01 |
-2.37 |
-2.86 |
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AppLovin Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.37 |
-3.09 |
-3.18 |
-2.97 |
-2.86 |
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 * 1.1645 | + | 0.528 * 0.818 | + | 0.404 * 1.0193 | + | 0.892 * 1.1654 | + | 0.115 * 1.1588 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7662 | + | 4.679 * -0.129847 | - | 0.327 * 1.1145 |
| = | -2.86 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $954 Mil.
Revenue was 953.261 + 864.256 + 750.165 + 715.405 = $3,283 Mil.
Gross Profit was 679.654 + 599.207 + 491.59 + 453.445 = $2,224 Mil.
Total Current Assets was $1,616 Mil.
Total Assets was $5,359 Mil.
Property, Plant and Equipment(Net PPE) was $222 Mil.
Depreciation, Depletion and Amortization(DDA) was $489 Mil.
Selling, General, & Admin. Expense(SGA) was $983 Mil.
Total Current Liabilities was $944 Mil.
Long-Term Debt & Capital Lease Obligation was $2,949 Mil.
Net Income was 172.233 + 108.639 + 80.357 + -4.518 = $357 Mil.
Non Operating Income was -19.034 + 0 + 0 + 10.111 = $-9 Mil.
Cash Flow from Operations was 343.988 + 199.066 + 229.794 + 288.662 = $1,062 Mil.
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Total Receivables was $703 Mil.
Revenue was 702.307 + 713.099 + 776.231 + 625.421 = $2,817 Mil.
Gross Profit was 332.939 + 412.111 + 472.302 + 343.641 = $1,561 Mil.
Total Current Assets was $1,939 Mil.
Total Assets was $5,848 Mil.
Property, Plant and Equipment(Net PPE) was $139 Mil.
Depreciation, Depletion and Amortization(DDA) was $547 Mil.
Selling, General, & Admin. Expense(SGA) was $1,101 Mil.
Total Current Liabilities was $579 Mil.
Long-Term Debt & Capital Lease Obligation was $3,233 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) |
| = | (953.81 / 3283.087) | / | (702.814 / 2817.058) |
| = | 0.290522 | / | 0.249485 |
| | = | 1.1645 |
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) |
| = | (1560.993 / 2817.058) | / | (2223.896 / 3283.087) |
| = | 0.554122 | / | 0.67738 |
| | = | 0.818 |
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 - (1616.163 + 221.541) / 5359.187) | / | (1 - (1939.083 + 138.922) / 5847.846) |
| = | 0.657093 | / | 0.644655 |
| | = | 1.0193 |
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 |
| = | 3283.087 | / | 2817.058 |
| | = | 1.1654 |
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)) |
| = | (547.084 / (547.084 + 138.922)) | / | (489.008 / (489.008 + 221.541)) |
| = | 0.797492 | / | 0.688212 |
| | = | 1.1588 |
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) |
| = | (983.303 / 3283.087) | / | (1101.177 / 2817.058) |
| = | 0.299506 | / | 0.390896 |
| | = | 0.7662 |
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) |
| = | ((2948.811 + 944.122) / 5359.187) | / | ((3232.565 + 578.958) / 5847.846) |
| = | 0.726404 | / | 0.651782 |
| | = | 1.1145 |
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 |
| = | (356.711 - -8.923 | - | 1061.51) | / | 5359.187 |
| | = | -0.129847 |
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 -2.86 suggests that the company is unlikely to be a manipulator.
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