Amazon.com Beneish M-Score Historical Data
The historical data trend for Amazon.com'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.
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Amazon.com Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
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-2.93 |
-2.94 |
-2.59 |
-2.44 |
-2.79 |
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Amazon.com Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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|
|
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|
|
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-2.44 |
-2.73 |
-2.77 |
-2.89 |
-2.79 |
Competitive Comparison
For the Internet Retail subindustry, Amazon.com'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.
Amazon.com Beneish M-Score Distribution
For the Retail - Cyclical industry and Consumer Cyclical sector, Amazon.com's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Amazon.com's Beneish M-Score falls into.
Amazon.com 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 Amazon.com 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 * 1.101 | + | 0.528 * 0.8068 | + | 0.404 * 1.0957 | + | 0.892 * 1.0884 | + | 0.115 * 0.9494 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9265 | + | 4.679 * -0.105739 | - | 0.327 * 0.8914 |
| = | -2.82 |
* 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 €47,916 Mil.
Revenue was 155854.237 + 134068.771 + 124035.509 + 118952.372 = €532,911 Mil.
Gross Profit was 26845.175 + 22997.728 + 20097.402 + 17010.008 = €86,950 Mil.
Total Current Assets was €158,046 Mil.
Total Assets was €484,042 Mil.
Property, Plant and Equipment(Net PPE) was €253,725 Mil.
Depreciation, Depletion and Amortization(DDA) was €45,125 Mil.
Selling, General, & Admin. Expense(SGA) was €52,093 Mil.
Total Current Liabilities was €151,229 Mil.
Long-Term Debt & Capital Lease Obligation was €124,355 Mil.
Net Income was 9742.208 + 9256.623 + 6230.25 + 2962.648 = €28,192 Mil.
Non Operating Income was 265.013 + 966.047 + 56.303 + -413.762 = €874 Mil.
Cash Flow from Operations was 38940.405 + 19880.329 + 15207.348 + 4471.992 = €78,500 Mil.
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Total Receivables was €39,988 Mil.
Revenue was 140848.576 + 128372.01 + 114687.364 + 105731.152 = €489,639 Mil.
Gross Profit was 18546.768 + 16932.65 + 15510.616 + 13467.456 = €64,457 Mil.
Total Current Assets was €138,571 Mil.
Total Assets was €436,765 Mil.
Property, Plant and Equipment(Net PPE) was €238,679 Mil.
Depreciation, Depletion and Amortization(DDA) was €39,943 Mil.
Selling, General, & Admin. Expense(SGA) was €51,660 Mil.
Total Current Liabilities was €146,691 Mil.
Long-Term Debt & Capital Lease Obligation was €132,271 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) |
| = | (47916.001 / 532910.889) | / | (39987.84 / 489639.102) |
| = | 0.089914 | / | 0.081668 |
| | = | 1.101 |
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) |
| = | (64457.49 / 489639.102) | / | (86950.313 / 532910.889) |
| = | 0.131643 | / | 0.163161 |
| | = | 0.8068 |
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 - (158045.867 + 253724.73) / 484042.118) | / | (1 - (138570.704 + 238679.072) / 436765.2) |
| = | 0.149308 | / | 0.136264 |
| | = | 1.0957 |
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 |
| = | 532910.889 | / | 489639.102 |
| | = | 1.0884 |
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)) |
| = | (39943.49 / (39943.49 + 238679.072)) | / | (45125.216 / (45125.216 + 253724.73)) |
| = | 0.143361 | / | 0.150996 |
| | = | 0.9494 |
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) |
| = | (52093.139 / 532910.889) | / | (51659.8 / 489639.102) |
| = | 0.097752 | / | 0.105506 |
| | = | 0.9265 |
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) |
| = | ((124355.287 + 151228.889) / 484042.118) | / | ((132271.392 + 146690.992) / 436765.2) |
| = | 0.569339 | / | 0.638701 |
| | = | 0.8914 |
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 |
| = | (28191.729 - 873.601 | - | 78500.074) | / | 484042.118 |
| | = | -0.105739 |
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.
Amazon.com has a M-score of -2.82 suggests that the company is unlikely to be a manipulator.
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