Five9 Beneish M-Score Historical Data
The historical data trend for Five9'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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Five9 Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.41 |
-2.19 |
-2.12 |
-3.15 |
-2.95 |
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Five9 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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-3.15 |
-3.07 |
-3.06 |
-3.00 |
-2.95 |
Competitive Comparison
For the Software - Infrastructure subindustry, Five9'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.
Five9 Beneish M-Score Distribution
For the Software industry and Technology sector, Five9's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Five9's Beneish M-Score falls into.
Five9 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 Five9 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 * 0.9555 | + | 0.528 * 1.0064 | + | 0.404 * 1.0875 | + | 0.892 * 1.169 | + | 0.115 * 0.9575 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0055 | + | 4.679 * -0.140912 | - | 0.327 * 0.8488 |
| = | -2.95 |
* 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 $101.5 Mil.
Revenue was 239.062 + 230.105 + 222.882 + 218.439 = $910.5 Mil.
Gross Profit was 126.569 + 119.025 + 118.521 + 113.683 = $477.8 Mil.
Total Current Assets was $924.1 Mil.
Total Assets was $1,494.6 Mil.
Property, Plant and Equipment(Net PPE) was $152.0 Mil.
Depreciation, Depletion and Amortization(DDA) was $61.2 Mil.
Selling, General, & Admin. Expense(SGA) was $419.8 Mil.
Total Current Liabilities was $167.2 Mil.
Long-Term Debt & Capital Lease Obligation was $781.4 Mil.
Net Income was -12.358 + -20.419 + -21.739 + -27.248 = $-81.8 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0.0 Mil.
Cash Flow from Operations was 36.544 + 37.03 + 21.852 + 33.412 = $128.8 Mil.
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Total Receivables was $90.9 Mil.
Revenue was 208.345 + 198.342 + 189.382 + 182.777 = $778.8 Mil.
Gross Profit was 112.051 + 104.231 + 101.153 + 93.91 = $411.3 Mil.
Total Current Assets was $778.7 Mil.
Total Assets was $1,244.5 Mil.
Property, Plant and Equipment(Net PPE) was $145.3 Mil.
Depreciation, Depletion and Amortization(DDA) was $55.0 Mil.
Selling, General, & Admin. Expense(SGA) was $357.1 Mil.
Total Current Liabilities was $150.8 Mil.
Long-Term Debt & Capital Lease Obligation was $779.8 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) |
| = | (101.53 / 910.488) | / | (90.895 / 778.846) |
| = | 0.111512 | / | 0.116705 |
| | = | 0.9555 |
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) |
| = | (411.345 / 778.846) | / | (477.798 / 910.488) |
| = | 0.528147 | / | 0.524771 |
| | = | 1.0064 |
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 - (924.054 + 152.009) / 1494.568) | / | (1 - (778.71 + 145.341) / 1244.485) |
| = | 0.280017 | / | 0.257483 |
| | = | 1.0875 |
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 |
| = | 910.488 | / | 778.846 |
| | = | 1.169 |
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)) |
| = | (55.048 / (55.048 + 145.341)) | / | (61.157 / (61.157 + 152.009)) |
| = | 0.274706 | / | 0.286898 |
| | = | 0.9575 |
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) |
| = | (419.792 / 910.488) | / | (357.133 / 778.846) |
| = | 0.461063 | / | 0.458541 |
| | = | 1.0055 |
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) |
| = | ((781.38 + 167.215) / 1494.568) | / | ((779.765 + 150.776) / 1244.485) |
| = | 0.634695 | / | 0.747732 |
| | = | 0.8488 |
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 |
| = | (-81.764 - 0 | - | 128.838) | / | 1494.568 |
| | = | -0.140912 |
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.
Five9 has a M-score of -2.95 suggests that the company is unlikely to be a manipulator.
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