Payoneer Global Beneish M-Score Historical Data
The historical data trend for Payoneer Global'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.
Payoneer Global Beneish M-Score Chart
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Payoneer Global Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-2.62 |
-2.78 |
-2.29 |
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Payoneer Global Quarterly Data
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Dec18 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.78 |
-2.65 |
-2.50 |
-2.33 |
-2.29 |
Competitive Comparison of Payoneer Global's Beneish M-Score
For the Software - Infrastructure subindustry, Payoneer Global'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.
Payoneer Global's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Payoneer Global's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Payoneer Global's Beneish M-Score falls into.
Payoneer Global 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 Payoneer Global 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 * 0.8184 | + | 0.528 * 0.9667 | + | 0.404 * 1.2927 | + | 0.892 * 1.3242 | + | 0.115 * 1.0121 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8828 | + | 4.679 * -0.011467 | - | 0.327 * 0.9927 |
| = | -2.29 |
* 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 $66.3 Mil.
Revenue was 224.32 + 208.035 + 206.734 + 192.014 = $831.1 Mil.
Gross Profit was 188 + 177.642 + 178.237 + 164.933 = $708.8 Mil.
Total Current Assets was $7,108.7 Mil.
Total Assets was $7,283.1 Mil.
Property, Plant and Equipment(Net PPE) was $40.4 Mil.
Depreciation, Depletion and Amortization(DDA) was $27.8 Mil.
Selling, General, & Admin. Expense(SGA) was $297.6 Mil.
Total Current Liabilities was $6,542.0 Mil.
Long-Term Debt & Capital Lease Obligation was $36.2 Mil.
Net Income was 27.021 + 12.825 + 45.549 + 7.938 = $93.3 Mil.
Non Operating Income was 11.824 + -7.799 + 13.586 + -0.252 = $17.4 Mil.
Cash Flow from Operations was 58.161 + 41.409 + 56.017 + 3.902 = $159.5 Mil.
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Total Receivables was $61.2 Mil.
Revenue was 183.558 + 158.917 + 148.19 + 136.958 = $627.6 Mil.
Gross Profit was 153.166 + 130.931 + 121.978 + 111.383 = $517.5 Mil.
Total Current Assets was $6,471.1 Mil.
Total Assets was $6,594.7 Mil.
Property, Plant and Equipment(Net PPE) was $29.7 Mil.
Depreciation, Depletion and Amortization(DDA) was $20.9 Mil.
Selling, General, & Admin. Expense(SGA) was $254.6 Mil.
Total Current Liabilities was $5,977.5 Mil.
Long-Term Debt & Capital Lease Obligation was $22.7 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) |
| = | (66.317 / 831.103) | / | (61.195 / 627.623) |
| = | 0.079794 | / | 0.097503 |
| | = | 0.8184 |
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) |
| = | (517.458 / 627.623) | / | (708.812 / 831.103) |
| = | 0.824473 | / | 0.852857 |
| | = | 0.9667 |
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 - (7108.723 + 40.353) / 7283.119) | / | (1 - (6471.104 + 29.652) / 6594.651) |
| = | 0.018405 | / | 0.014238 |
| | = | 1.2927 |
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 |
| = | 831.103 | / | 627.623 |
| | = | 1.3242 |
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)) |
| = | (20.858 / (20.858 + 29.652)) | / | (27.814 / (27.814 + 40.353)) |
| = | 0.412948 | / | 0.408027 |
| | = | 1.0121 |
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) |
| = | (297.583 / 831.103) | / | (254.574 / 627.623) |
| = | 0.358058 | / | 0.405616 |
| | = | 0.8828 |
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) |
| = | ((36.247 + 6541.975) / 7283.119) | / | ((22.652 + 5977.512) / 6594.651) |
| = | 0.903215 | / | 0.909853 |
| | = | 0.9927 |
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 |
| = | (93.333 - 17.359 | - | 159.489) | / | 7283.119 |
| | = | -0.011467 |
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.
Payoneer Global has a M-score of -2.29 suggests that the company is unlikely to be a manipulator.
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