Etsy Beneish M-Score Historical Data
The historical data trend for Etsy'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.
Etsy Beneish M-Score Chart
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Etsy Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-1.53 |
-2.12 |
-1.29 |
-3.36 |
-2.94 |
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Etsy 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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-3.36 |
-3.37 |
-3.13 |
-2.97 |
-2.94 |
Competitive Comparison of Etsy's Beneish M-Score
For the Internet Retail subindustry, Etsy'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.
Etsy's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, Etsy's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Etsy's Beneish M-Score falls into.
Etsy 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 Etsy 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 * 1.0345 | + | 0.528 * 1.0162 | + | 0.404 * 0.9741 | + | 0.892 * 1.071 | + | 0.115 * 1.0426 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0065 | + | 4.679 * -0.119489 | - | 0.327 * 1.0063 |
| = | -2.94 |
* 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 $290 Mil.
Revenue was 842.322 + 636.302 + 628.876 + 640.877 = $2,748 Mil.
Gross Profit was 586.565 + 447.475 + 440.238 + 445.424 = $1,920 Mil.
Total Current Assets was $1,570 Mil.
Total Assets was $2,685 Mil.
Property, Plant and Equipment(Net PPE) was $250 Mil.
Depreciation, Depletion and Amortization(DDA) was $91 Mil.
Selling, General, & Admin. Expense(SGA) was $1,102 Mil.
Total Current Liabilities was $711 Mil.
Long-Term Debt & Capital Lease Obligation was $2,383 Mil.
Net Income was 83.266 + 87.85 + 61.915 + 74.537 = $308 Mil.
Non Operating Income was -28.247 + 8.411 + -60.305 + 3.072 = $-77 Mil.
Cash Flow from Operations was 295.105 + 218.506 + 136.271 + 55.631 = $706 Mil.
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Total Receivables was $262 Mil.
Revenue was 807.241 + 594.469 + 585.135 + 579.266 = $2,566 Mil.
Gross Profit was 581.466 + 420.068 + 413.714 + 406.271 = $1,822 Mil.
Total Current Assets was $1,514 Mil.
Total Assets was $2,635 Mil.
Property, Plant and Equipment(Net PPE) was $250 Mil.
Depreciation, Depletion and Amortization(DDA) was $97 Mil.
Selling, General, & Admin. Expense(SGA) was $1,023 Mil.
Total Current Liabilities was $632 Mil.
Long-Term Debt & Capital Lease Obligation was $2,385 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) |
| = | (290.121 / 2748.377) | / | (261.849 / 2566.111) |
| = | 0.105561 | / | 0.102041 |
| | = | 1.0345 |
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) |
| = | (1821.519 / 2566.111) | / | (1919.702 / 2748.377) |
| = | 0.709836 | / | 0.698486 |
| | = | 1.0162 |
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 - (1570.446 + 249.794) / 2685.4) | / | (1 - (1513.743 + 249.744) / 2634.961) |
| = | 0.322172 | / | 0.330735 |
| | = | 0.9741 |
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 |
| = | 2748.377 | / | 2566.111 |
| | = | 1.071 |
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)) |
| = | (96.702 / (96.702 + 249.744)) | / | (91.323 / (91.323 + 249.794)) |
| = | 0.279126 | / | 0.267718 |
| | = | 1.0426 |
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) |
| = | (1102.438 / 2748.377) | / | (1022.659 / 2566.111) |
| = | 0.401123 | / | 0.398525 |
| | = | 1.0065 |
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) |
| = | ((2383.437 + 710.781) / 2685.4) | / | ((2385.339 + 631.755) / 2634.961) |
| = | 1.152237 | / | 1.145024 |
| | = | 1.0063 |
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 |
| = | (307.568 - -77.069 | - | 705.513) | / | 2685.4 |
| | = | -0.119489 |
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.
Etsy has a M-score of -2.94 suggests that the company is unlikely to be a manipulator.
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