GoDaddy Beneish M-Score Historical Data
The historical data trend for GoDaddy'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.
GoDaddy Beneish M-Score Chart
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GoDaddy Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.78 |
-3.06 |
-2.44 |
-2.92 |
-1.92 |
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GoDaddy Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.76 |
-2.77 |
-2.70 |
-1.92 |
-1.66 |
Competitive Comparison of GoDaddy's Beneish M-Score
For the Software - Infrastructure subindustry, GoDaddy'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.
GoDaddy's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, GoDaddy's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where GoDaddy's Beneish M-Score falls into.
GoDaddy 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 GoDaddy 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 * 1.303 | + | 0.528 * 1.0103 | + | 0.404 * 1.0977 | + | 0.892 * 1.049 | + | 0.115 * 0.9539 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8824 | + | 4.679 * 0.08698 | - | 0.327 * 0.9001 |
| = | -1.66 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was $94 Mil.
Revenue was 1108.5 + 1100.3 + 1069.7 + 1048.1 = $4,327 Mil.
Gross Profit was 694 + 698.1 + 672.8 + 659.7 = $2,725 Mil.
Total Current Assets was $1,496 Mil.
Total Assets was $7,979 Mil.
Property, Plant and Equipment(Net PPE) was $221 Mil.
Depreciation, Depletion and Amortization(DDA) was $160 Mil.
Selling, General, & Admin. Expense(SGA) was $720 Mil.
Total Current Liabilities was $2,722 Mil.
Long-Term Debt & Capital Lease Obligation was $3,879 Mil.
Net Income was 401.5 + 1113.9 + 130.7 + 82.9 = $1,729 Mil.
Non Operating Income was -13.8 + -10 + -5 + -10.7 = $-40 Mil.
Cash Flow from Operations was 297.2 + 297.7 + 281.6 + 198 = $1,075 Mil.
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Total Receivables was $69 Mil.
Revenue was 1036 + 1039.9 + 1033.2 + 1015.5 = $4,125 Mil.
Gross Profit was 649.9 + 660.4 + 658.9 + 655 = $2,624 Mil.
Total Current Assets was $1,730 Mil.
Total Assets was $7,092 Mil.
Property, Plant and Equipment(Net PPE) was $291 Mil.
Depreciation, Depletion and Amortization(DDA) was $195 Mil.
Selling, General, & Admin. Expense(SGA) was $777 Mil.
Total Current Liabilities was $2,599 Mil.
Long-Term Debt & Capital Lease Obligation was $3,920 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) |
| = | (93.9 / 4326.6) | / | (68.7 / 4124.6) |
| = | 0.021703 | / | 0.016656 |
| | = | 1.303 |
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) |
| = | (2624.2 / 4124.6) | / | (2724.6 / 4326.6) |
| = | 0.636231 | / | 0.629732 |
| | = | 1.0103 |
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 - (1495.8 + 220.6) / 7978.8) | / | (1 - (1730.1 + 291.1) / 7092.3) |
| = | 0.78488 | / | 0.715015 |
| | = | 1.0977 |
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 |
| = | 4326.6 | / | 4124.6 |
| | = | 1.049 |
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)) |
| = | (194.9 / (194.9 + 291.1)) | / | (160 / (160 + 220.6)) |
| = | 0.401029 | / | 0.420389 |
| | = | 0.9539 |
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) |
| = | (719.6 / 4326.6) | / | (777.4 / 4124.6) |
| = | 0.16632 | / | 0.188479 |
| | = | 0.8824 |
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) |
| = | ((3878.7 + 2722.3) / 7978.8) | / | ((3919.5 + 2599.3) / 7092.3) |
| = | 0.827317 | / | 0.919138 |
| | = | 0.9001 |
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 |
| = | (1729 - -39.5 | - | 1074.5) | / | 7978.8 |
| | = | 0.08698 |
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.
GoDaddy has a M-score of -1.66 signals that the company is likely to be a manipulator.
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