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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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.97 |
-2.94 |
-3.07 |
-3.36 |
-3.59 |
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 * 0.7279 | + | 0.528 * 0.9944 | + | 0.404 * 1.0252 | + | 0.892 * 1.0314 | + | 0.115 * 0.8975 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0758 | + | 4.679 * -0.186345 | - | 0.327 * 1.0037 |
| = | -3.59 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $181 Mil.
Revenue was 662.41 + 647.806 + 645.954 + 842.322 = $2,798 Mil.
Gross Profit was 476.77 + 463.716 + 458.821 + 586.565 = $1,986 Mil.
Total Current Assets was $1,321 Mil.
Total Assets was $2,442 Mil.
Property, Plant and Equipment(Net PPE) was $243 Mil.
Depreciation, Depletion and Amortization(DDA) was $105 Mil.
Selling, General, & Admin. Expense(SGA) was $1,196 Mil.
Total Current Liabilities was $553 Mil.
Long-Term Debt & Capital Lease Obligation was $2,382 Mil.
Net Income was 57.366 + 53.005 + 63.004 + 83.266 = $257 Mil.
Non Operating Income was -13.007 + 8.808 + 11.565 + -28.247 = $-21 Mil.
Cash Flow from Operations was 217.416 + 151.061 + 69.033 + 295.105 = $733 Mil.
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Total Receivables was $241 Mil.
Revenue was 636.302 + 628.876 + 640.877 + 807.241 = $2,713 Mil.
Gross Profit was 447.475 + 440.238 + 445.424 + 581.466 = $1,915 Mil.
Total Current Assets was $1,344 Mil.
Total Assets was $2,449 Mil.
Property, Plant and Equipment(Net PPE) was $246 Mil.
Depreciation, Depletion and Amortization(DDA) was $91 Mil.
Selling, General, & Admin. Expense(SGA) was $1,078 Mil.
Total Current Liabilities was $549 Mil.
Long-Term Debt & Capital Lease Obligation was $2,384 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) |
| = | (181.206 / 2798.492) | / | (241.368 / 2713.296) |
| = | 0.064751 | / | 0.088957 |
| | = | 0.7279 |
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) |
| = | (1914.603 / 2713.296) | / | (1985.872 / 2798.492) |
| = | 0.705637 | / | 0.709622 |
| | = | 0.9944 |
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 - (1320.681 + 242.889) / 2442.206) | / | (1 - (1343.861 + 245.806) / 2449.197) |
| = | 0.359771 | / | 0.350944 |
| | = | 1.0252 |
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 |
| = | 2798.492 | / | 2713.296 |
| | = | 1.0314 |
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)) |
| = | (91.084 / (91.084 + 245.806)) | / | (104.705 / (104.705 + 242.889)) |
| = | 0.270367 | / | 0.301228 |
| | = | 0.8975 |
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) |
| = | (1196.26 / 2798.492) | / | (1078.154 / 2713.296) |
| = | 0.427466 | / | 0.39736 |
| | = | 1.0758 |
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) |
| = | ((2382.06 + 552.96) / 2442.206) | / | ((2383.865 + 548.817) / 2449.197) |
| = | 1.201791 | / | 1.197406 |
| | = | 1.0037 |
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 |
| = | (256.641 - -20.881 | - | 732.615) | / | 2442.206 |
| | = | -0.186345 |
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 -3.59 suggests that the company is unlikely to be a manipulator.
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