Shopify Beneish M-Score Historical Data
The historical data trend for Shopify'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.
Shopify Beneish M-Score Chart
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Shopify Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-0.60 |
-2.19 |
-0.85 |
-2.43 |
-2.52 |
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Shopify 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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-2.77 |
-2.52 |
-2.61 |
-2.24 |
-2.14 |
Competitive Comparison of Shopify's Beneish M-Score
For the Software - Application subindustry, Shopify'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.
Shopify's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Shopify's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Shopify's Beneish M-Score falls into.
Shopify 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 Shopify 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 * 1.1711 | + | 0.528 * 0.958 | + | 0.404 * 1.1465 | + | 0.892 * 1.271 | + | 0.115 * 2.1545 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7867 | + | 4.679 * -0.03238 | - | 0.327 * 0.8856 |
| = | -1.99 |
* 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 R$7,947 Mil.
Revenue was 11972.724 + 11014.575 + 9267.408 + 10505.171 = R$42,760 Mil.
Gross Profit was 6191.26 + 5628.475 + 4765.669 + 5203.588 = R$21,789 Mil.
Total Current Assets was R$36,223 Mil.
Total Assets was R$68,276 Mil.
Property, Plant and Equipment(Net PPE) was R$792 Mil.
Depreciation, Depletion and Amortization(DDA) was R$197 Mil.
Selling, General, & Admin. Expense(SGA) was R$9,147 Mil.
Total Current Liabilities was R$5,100 Mil.
Long-Term Debt & Capital Lease Obligation was R$6,219 Mil.
Net Income was 4585.298 + 921.023 + -1359.485 + 3219.169 = R$7,366 Mil.
Non Operating Income was 2768.9 + -635.56 + -1703.092 + 1592.435 = R$2,023 Mil.
Cash Flow from Operations was 2342.489 + 1831.274 + 1185.192 + 2195.11 = R$7,554 Mil.
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Total Receivables was R$5,339 Mil.
Revenue was 8464.932 + 8222.168 + 7854.569 + 9100.769 = R$33,642 Mil.
Gross Profit was 4449.769 + 4052.84 + 3734.566 + 4185.829 = R$16,423 Mil.
Total Current Assets was R$30,427 Mil.
Total Assets was R$51,679 Mil.
Property, Plant and Equipment(Net PPE) was R$612 Mil.
Depreciation, Depletion and Amortization(DDA) was R$460 Mil.
Selling, General, & Admin. Expense(SGA) was R$9,149 Mil.
Total Current Liabilities was R$4,208 Mil.
Long-Term Debt & Capital Lease Obligation was R$5,467 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) |
| = | (7946.743 / 42759.878) | / | (5338.735 / 33642.438) |
| = | 0.185846 | / | 0.15869 |
| | = | 1.1711 |
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) |
| = | (16423.004 / 33642.438) | / | (21788.992 / 42759.878) |
| = | 0.488163 | / | 0.509566 |
| | = | 0.958 |
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 - (36222.75 + 791.905) / 68275.536) | / | (1 - (30427.331 + 612.399) / 51678.557) |
| = | 0.457864 | / | 0.399369 |
| | = | 1.1465 |
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 |
| = | 42759.878 | / | 33642.438 |
| | = | 1.271 |
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)) |
| = | (460.336 / (460.336 + 612.399)) | / | (196.959 / (196.959 + 791.905)) |
| = | 0.429124 | / | 0.199177 |
| | = | 2.1545 |
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) |
| = | (9147.2 / 42759.878) | / | (9148.561 / 33642.438) |
| = | 0.21392 | / | 0.271935 |
| | = | 0.7867 |
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) |
| = | ((6218.949 + 5100.314) / 68275.536) | / | ((5467.141 + 4207.772) / 51678.557) |
| = | 0.165788 | / | 0.187213 |
| | = | 0.8856 |
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 |
| = | (7366.005 - 2022.683 | - | 7554.065) | / | 68275.536 |
| | = | -0.03238 |
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.
Shopify has a M-score of -1.99 suggests that the company is unlikely to be a manipulator.
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