Inpost Beneish M-Score Historical Data
The historical data trend for Inpost'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.
Inpost Beneish M-Score Chart
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Inpost Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-0.96 |
-2.73 |
-2.85 |
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Inpost Quarterly Data
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Dec17 |
Dec18 |
Sep19 |
Dec19 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.73 |
-2.62 |
-2.75 |
-2.81 |
-2.85 |
Competitive Comparison of Inpost's Beneish M-Score
For the Specialty Business Services subindustry, Inpost'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.
Inpost's Beneish M-Score Distribution in the Business Services Industry
For the Business Services industry and Industrials sector, Inpost's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Inpost's Beneish M-Score falls into.
Inpost 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 Inpost 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 * 0.9232 | + | 0.528 * 0.9955 | + | 0.404 * 0.9231 | + | 0.892 * 1.2526 | + | 0.115 * 0.9687 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0 | + | 4.679 * -0.146762 | - | 0.327 * 0.9163 |
| = | -2.85 |
* 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 €329 Mil.
Revenue was 607.376 + 471.317 + 487.514 + 454.047 = €2,020 Mil.
Gross Profit was 588.964 + 462.796 + 468.873 + 436.937 = €1,958 Mil.
Total Current Assets was €478 Mil.
Total Assets was €2,223 Mil.
Property, Plant and Equipment(Net PPE) was €1,106 Mil.
Depreciation, Depletion and Amortization(DDA) was €263 Mil.
Selling, General, & Admin. Expense(SGA) was €0 Mil.
Total Current Liabilities was €509 Mil.
Long-Term Debt & Capital Lease Obligation was €1,347 Mil.
Net Income was 34.974 + 57.201 + 29.24 + 26.476 = €148 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = €0 Mil.
Cash Flow from Operations was 140.787 + 149.674 + 86.213 + 97.521 = €474 Mil.
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Total Receivables was €284 Mil.
Revenue was 491.009 + 385.812 + 384.967 + 351.044 = €1,613 Mil.
Gross Profit was 472.711 + 370.278 + 373.522 + 339.256 = €1,556 Mil.
Total Current Assets was €404 Mil.
Total Assets was €2,000 Mil.
Property, Plant and Equipment(Net PPE) was €973 Mil.
Depreciation, Depletion and Amortization(DDA) was €222 Mil.
Selling, General, & Admin. Expense(SGA) was €409 Mil.
Total Current Liabilities was €496 Mil.
Long-Term Debt & Capital Lease Obligation was €1,327 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) |
| = | (328.931 / 2020.254) | / | (284.453 / 1612.832) |
| = | 0.162817 | / | 0.176369 |
| | = | 0.9232 |
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) |
| = | (1555.767 / 1612.832) | / | (1957.57 / 2020.254) |
| = | 0.964618 | / | 0.968972 |
| | = | 0.9955 |
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 - (477.919 + 1105.992) / 2223.36) | / | (1 - (403.722 + 973.2) / 2000.06) |
| = | 0.287605 | / | 0.31156 |
| | = | 0.9231 |
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 |
| = | 2020.254 | / | 1612.832 |
| | = | 1.2526 |
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)) |
| = | (222.112 / (222.112 + 973.2)) | / | (262.5 / (262.5 + 1105.992)) |
| = | 0.185819 | / | 0.191817 |
| | = | 0.9687 |
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) |
| = | (0 / 2020.254) | / | (408.907 / 1612.832) |
| = | 0 | / | 0.253534 |
| | = | 0 |
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) |
| = | ((1347.019 + 509.352) / 2223.36) | / | ((1326.87 + 495.646) / 2000.06) |
| = | 0.834939 | / | 0.911231 |
| | = | 0.9163 |
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 |
| = | (147.891 - 0 | - | 474.195) | / | 2223.36 |
| | = | -0.146762 |
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.
Inpost has a M-score of -2.85 suggests that the company is unlikely to be a manipulator.
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