Akamai Technologies Beneish M-Score Historical Data
The historical data trend for Akamai Technologies'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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Akamai Technologies Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.65 |
-2.58 |
-2.84 |
-2.88 |
-2.73 |
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Akamai Technologies 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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-2.88 |
-2.94 |
-2.88 |
-2.70 |
-2.73 |
Competitive Comparison
For the Software - Infrastructure subindustry, Akamai Technologies'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.
Akamai Technologies Beneish M-Score Distribution
For the Software industry and Technology sector, Akamai Technologies's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Akamai Technologies's Beneish M-Score falls into.
Akamai Technologies 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 Akamai Technologies 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 * 1.0118 | + | 0.528 * 1.0228 | + | 0.404 * 1.1296 | + | 0.892 * 1.054 | + | 0.115 * 1.1651 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0197 | + | 4.679 * -0.073037 | - | 0.327 * 1.1373 |
| = | -2.73 |
* 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 $724 Mil.
Revenue was 995.017 + 965.484 + 935.721 + 915.698 = $3,812 Mil.
Gross Profit was 601.62 + 582.409 + 562.446 + 554.382 = $2,301 Mil.
Total Current Assets was $1,805 Mil.
Total Assets was $9,900 Mil.
Property, Plant and Equipment(Net PPE) was $2,735 Mil.
Depreciation, Depletion and Amortization(DDA) was $571 Mil.
Selling, General, & Admin. Expense(SGA) was $1,058 Mil.
Total Current Liabilities was $836 Mil.
Long-Term Debt & Capital Lease Obligation was $4,313 Mil.
Net Income was 161.165 + 160.542 + 128.816 + 97.106 = $548 Mil.
Non Operating Income was -5.97 + -7.975 + -12.007 + -51.789 = $-78 Mil.
Cash Flow from Operations was 389.193 + 359.436 + 366.311 + 233.499 = $1,348 Mil.
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Total Receivables was $679 Mil.
Revenue was 927.779 + 881.896 + 903.332 + 903.647 = $3,617 Mil.
Gross Profit was 569.811 + 535.446 + 556.683 + 570.895 = $2,233 Mil.
Total Current Assets was $1,970 Mil.
Total Assets was $8,303 Mil.
Property, Plant and Equipment(Net PPE) was $2,354 Mil.
Depreciation, Depletion and Amortization(DDA) was $593 Mil.
Selling, General, & Admin. Expense(SGA) was $984 Mil.
Total Current Liabilities was $819 Mil.
Long-Term Debt & Capital Lease Obligation was $2,979 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) |
| = | (724.302 / 3811.92) | / | (679.206 / 3616.654) |
| = | 0.19001 | / | 0.1878 |
| | = | 1.0118 |
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) |
| = | (2232.835 / 3616.654) | / | (2300.857 / 3811.92) |
| = | 0.617376 | / | 0.603595 |
| | = | 1.0228 |
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 - (1804.855 + 2734.578) / 9900.037) | / | (1 - (1969.562 + 2353.554) / 8303.4) |
| = | 0.541473 | / | 0.479356 |
| | = | 1.1296 |
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 |
| = | 3811.92 | / | 3616.654 |
| | = | 1.054 |
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)) |
| = | (592.754 / (592.754 + 2353.554)) | / | (570.776 / (570.776 + 2734.578)) |
| = | 0.201185 | / | 0.172682 |
| | = | 1.1651 |
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) |
| = | (1057.809 / 3811.92) | / | (984.187 / 3616.654) |
| = | 0.2775 | / | 0.272126 |
| | = | 1.0197 |
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) |
| = | ((4313.035 + 836.038) / 9900.037) | / | ((2978.523 + 818.868) / 8303.4) |
| = | 0.520106 | / | 0.45733 |
| | = | 1.1373 |
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 |
| = | (547.629 - -77.741 | - | 1348.439) | / | 9900.037 |
| | = | -0.073037 |
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.
Akamai Technologies has a M-score of -2.73 suggests that the company is unlikely to be a manipulator.
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