Spotify Technology Beneish M-Score Historical Data
The historical data trend for Spotify Technology'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.
Spotify Technology Beneish M-Score Chart
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Spotify Technology Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.49 |
-2.97 |
-2.83 |
-2.86 |
-2.95 |
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Spotify Technology 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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-2.86 |
-2.53 |
-2.54 |
-2.72 |
-2.95 |
Competitive Comparison of Spotify Technology's Beneish M-Score
For the Internet Content & Information subindustry, Spotify Technology'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.
Spotify Technology's Beneish M-Score Distribution in the Interactive Media Industry
For the Interactive Media industry and Communication Services sector, Spotify Technology's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Spotify Technology's Beneish M-Score falls into.
Spotify Technology 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 Spotify Technology 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 * 0.7378 | + | 0.528 * 0.8512 | + | 0.404 * 0.8795 | + | 0.892 * 1.1843 | + | 0.115 * 0.9586 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7467 | + | 4.679 * -0.08016 | - | 0.327 * 0.7751 |
| = | -2.95 |
* 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 $837 Mil.
Revenue was 4441.885 + 4426.193 + 4097.955 + 3952.174 = $16,918 Mil.
Gross Profit was 1432.461 + 1376.249 + 1196.986 + 1091.304 = $5,097 Mil.
Total Current Assets was $8,774 Mil.
Total Assets was $12,571 Mil.
Property, Plant and Equipment(Net PPE) was $434 Mil.
Depreciation, Depletion and Amortization(DDA) was $131 Mil.
Selling, General, & Admin. Expense(SGA) was $2,021 Mil.
Total Current Liabilities was $4,660 Mil.
Long-Term Debt & Capital Lease Obligation was $2,095 Mil.
Net Income was 384.293 + 332.963 + 294.941 + 214.13 = $1,226 Mil.
Non Operating Income was -35.602 + -123.196 + -46.286 + -38.043 = $-243 Mil.
Cash Flow from Operations was 924.607 + 793.563 + 529.602 + 229.348 = $2,477 Mil.
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Total Receivables was $957 Mil.
Revenue was 4003.272 + 3582.711 + 3442.037 + 3256.959 = $14,285 Mil.
Gross Profit was 1068.702 + 944.504 + 829.902 + 820.128 = $3,663 Mil.
Total Current Assets was $5,736 Mil.
Total Assets was $9,101 Mil.
Property, Plant and Equipment(Net PPE) was $597 Mil.
Depreciation, Depletion and Amortization(DDA) was $170 Mil.
Selling, General, & Admin. Expense(SGA) was $2,285 Mil.
Total Current Liabilities was $4,460 Mil.
Long-Term Debt & Capital Lease Obligation was $1,850 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) |
| = | (836.649 / 16918.207) | / | (957.47 / 14284.979) |
| = | 0.049453 | / | 0.067026 |
| | = | 0.7378 |
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) |
| = | (3663.236 / 14284.979) | / | (5097 / 16918.207) |
| = | 0.25644 | / | 0.301273 |
| | = | 0.8512 |
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 - (8773.822 + 433.508) / 12570.681) | / | (1 - (5736.096 + 596.51) / 9101.418) |
| = | 0.267555 | / | 0.304218 |
| | = | 0.8795 |
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 |
| = | 16918.207 | / | 14284.979 |
| | = | 1.1843 |
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)) |
| = | (170.277 / (170.277 + 596.51)) | / | (130.699 / (130.699 + 433.508)) |
| = | 0.222066 | / | 0.231651 |
| | = | 0.9586 |
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) |
| = | (2020.614 / 16918.207) | / | (2284.803 / 14284.979) |
| = | 0.119434 | / | 0.159944 |
| | = | 0.7467 |
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) |
| = | ((2095.288 + 4659.686) / 12570.681) | / | ((1849.509 + 4460.196) / 9101.418) |
| = | 0.537359 | / | 0.693266 |
| | = | 0.7751 |
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 |
| = | (1226.327 - -243.127 | - | 2477.12) | / | 12570.681 |
| | = | -0.08016 |
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.
Spotify Technology has a M-score of -2.95 suggests that the company is unlikely to be a manipulator.
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