Meb PCL Beneish M-Score Historical Data
The historical data trend for Meb PCL'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.
Meb PCL Beneish M-Score Chart
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Meb PCL Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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- |
- |
- |
-2.06 |
-2.22 |
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Meb PCL Quarterly Data
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Dec19 |
Dec20 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.06 |
-2.30 |
-2.03 |
-1.86 |
-2.22 |
Competitive Comparison of Meb PCL's Beneish M-Score
For the Software - Application subindustry, Meb PCL'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.
Meb PCL's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Meb PCL's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Meb PCL's Beneish M-Score falls into.
Meb PCL 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 Meb PCL 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 * 1.0575 | + | 0.528 * 0.9761 | + | 0.404 * 1.5586 | + | 0.892 * 1.1322 | + | 0.115 * 0.6781 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1473 | + | 4.679 * -0.019494 | - | 0.327 * 0.9169 |
| = | -2.22 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ฿103 Mil.
Revenue was 564.052 + 542.896 + 540.033 + 522.333 = ฿2,169 Mil.
Gross Profit was 176.703 + 172.52 + 169.194 + 165.871 = ฿684 Mil.
Total Current Assets was ฿1,721 Mil.
Total Assets was ฿1,749 Mil.
Property, Plant and Equipment(Net PPE) was ฿3 Mil.
Depreciation, Depletion and Amortization(DDA) was ฿5 Mil.
Selling, General, & Admin. Expense(SGA) was ฿163 Mil.
Total Current Liabilities was ฿294 Mil.
Long-Term Debt & Capital Lease Obligation was ฿0 Mil.
Net Income was 114.505 + 104.791 + 115.848 + 104.933 = ฿440 Mil.
Non Operating Income was 13.101 + 0.027 + 12.251 + 0.001 = ฿25 Mil.
Cash Flow from Operations was 143.534 + 76.58 + 90.465 + 138.208 = ฿449 Mil.
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Total Receivables was ฿86 Mil.
Revenue was 519.055 + 473.333 + 468.48 + 455.074 = ฿1,916 Mil.
Gross Profit was 162.552 + 146.056 + 142.002 + 139.296 = ฿590 Mil.
Total Current Assets was ฿1,438 Mil.
Total Assets was ฿1,458 Mil.
Property, Plant and Equipment(Net PPE) was ฿6 Mil.
Depreciation, Depletion and Amortization(DDA) was ฿5 Mil.
Selling, General, & Admin. Expense(SGA) was ฿125 Mil.
Total Current Liabilities was ฿266 Mil.
Long-Term Debt & Capital Lease Obligation was ฿1 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) |
| = | (103.451 / 2169.314) | / | (86.398 / 1915.942) |
| = | 0.047688 | / | 0.045094 |
| | = | 1.0575 |
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) |
| = | (589.906 / 1915.942) | / | (684.288 / 2169.314) |
| = | 0.307893 | / | 0.31544 |
| | = | 0.9761 |
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 - (1720.54 + 3.176) / 1748.718) | / | (1 - (1438.498 + 6.362) / 1458.237) |
| = | 0.014297 | / | 0.009173 |
| | = | 1.5586 |
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 |
| = | 2169.314 | / | 1915.942 |
| | = | 1.1322 |
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)) |
| = | (4.599 / (4.599 + 6.362)) | / | (5.155 / (5.155 + 3.176)) |
| = | 0.419579 | / | 0.618773 |
| | = | 0.6781 |
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) |
| = | (162.505 / 2169.314) | / | (125.093 / 1915.942) |
| = | 0.074911 | / | 0.065291 |
| | = | 1.1473 |
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) |
| = | ((0 + 294.019) / 1748.718) | / | ((1.239 + 266.163) / 1458.237) |
| = | 0.168134 | / | 0.183373 |
| | = | 0.9169 |
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 |
| = | (440.077 - 25.38 | - | 448.787) | / | 1748.718 |
| | = | -0.019494 |
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.
Meb PCL has a M-score of -2.22 suggests that the company is unlikely to be a manipulator.
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