XTB Beneish M-Score Historical Data
The historical data trend for XTB'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.
XTB Beneish M-Score Chart
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XTB Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.01 |
-1.09 |
-1.38 |
-2.00 |
-2.38 |
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XTB 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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-2.78 |
-2.38 |
-2.34 |
4.42 |
5.42 |
Competitive Comparison of XTB's Beneish M-Score
For the Capital Markets subindustry, XTB'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.
XTB's Beneish M-Score Distribution in the Capital Markets Industry
For the Capital Markets industry and Financial Services sector, XTB's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where XTB's Beneish M-Score falls into.
XTB 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 XTB 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 | + | 0.528 * 0.9844 | + | 0.404 * 19.3203 | + | 0.892 * 1.4305 | + | 0.115 * 0.8653 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.7826 | + | 4.679 * 0.023168 | - | 0.327 * 1.0346 |
| = | 5.42 |
* 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 €12.2 Mil.
Revenue was 114.698 + 91.086 + 133.769 + 113.084 = €452.6 Mil.
Gross Profit was 92.356 + 65.822 + 113.72 + 94.725 = €366.6 Mil.
Total Current Assets was €1,159.4 Mil.
Total Assets was €1,331.0 Mil.
Property, Plant and Equipment(Net PPE) was €13.0 Mil.
Depreciation, Depletion and Amortization(DDA) was €4.7 Mil.
Selling, General, & Admin. Expense(SGA) was €72.4 Mil.
Total Current Liabilities was €882.3 Mil.
Long-Term Debt & Capital Lease Obligation was €4.0 Mil.
Net Income was 47.297 + 37.191 + 70.231 + 57.771 = €212.5 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0.0 Mil.
Cash Flow from Operations was 29.766 + 32.672 + 75.229 + 43.987 = €181.7 Mil.
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Total Receivables was €0.0 Mil.
Revenue was 68.403 + 67.989 + 127.417 + 52.604 = €316.4 Mil.
Gross Profit was 51.559 + 50.518 + 110.67 + 39.544 = €252.3 Mil.
Total Current Assets was €1,003.2 Mil.
Total Assets was €1,021.4 Mil.
Property, Plant and Equipment(Net PPE) was €11.9 Mil.
Depreciation, Depletion and Amortization(DDA) was €3.5 Mil.
Selling, General, & Admin. Expense(SGA) was €64.7 Mil.
Total Current Liabilities was €652.2 Mil.
Long-Term Debt & Capital Lease Obligation was €5.3 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) |
| = | (12.168 / 452.637) | / | (0 / 316.413) |
| = | 0.026882 | / | 0 |
| | = | 1 |
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) |
| = | (252.291 / 316.413) | / | (366.623 / 452.637) |
| = | 0.797347 | / | 0.809971 |
| | = | 0.9844 |
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 - (1159.366 + 12.97) / 1330.97) | / | (1 - (1003.222 + 11.902) / 1021.425) |
| = | 0.119187 | / | 0.006169 |
| | = | 19.3203 |
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 |
| = | 452.637 | / | 316.413 |
| | = | 1.4305 |
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)) |
| = | (3.523 / (3.523 + 11.902)) | / | (4.651 / (4.651 + 12.97)) |
| = | 0.228395 | / | 0.263946 |
| | = | 0.8653 |
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) |
| = | (72.434 / 452.637) | / | (64.699 / 316.413) |
| = | 0.160027 | / | 0.204476 |
| | = | 0.7826 |
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) |
| = | ((4.028 + 882.261) / 1330.97) | / | ((5.251 + 652.175) / 1021.425) |
| = | 0.665897 | / | 0.643636 |
| | = | 1.0346 |
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 |
| = | (212.49 - 0 | - | 181.654) | / | 1330.97 |
| | = | 0.023168 |
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.
XTB has a M-score of 5.42 signals that the company is likely to be a manipulator.
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