Infraset PCL Beneish M-Score Historical Data
The historical data trend for Infraset 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.
Infraset PCL Beneish M-Score Chart
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Infraset PCL Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-0.64 |
-3.12 |
1.06 |
-3.15 |
-0.13 |
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Infraset PCL Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-3.15 |
-3.61 |
-3.44 |
-2.73 |
-0.13 |
Competitive Comparison of Infraset PCL's Beneish M-Score
For the Information Technology Services subindustry, Infraset 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.
Infraset PCL's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Infraset PCL's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Infraset PCL's Beneish M-Score falls into.
Infraset 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 Infraset 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 * 2.1093 | + | 0.528 * 1.366 | + | 0.404 * 0.6427 | + | 0.892 * 1.1913 | + | 0.115 * 0.935 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9315 | + | 4.679 * 0.272197 | - | 0.327 * 1.5085 |
| = | -0.13 |
* 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 ฿1,776 Mil.
Revenue was 596.251 + 762.921 + 312.352 + 272.624 = ฿1,944 Mil.
Gross Profit was 38.522 + 65.015 + 25.698 + 32.244 = ฿161 Mil.
Total Current Assets was ฿1,912 Mil.
Total Assets was ฿2,391 Mil.
Property, Plant and Equipment(Net PPE) was ฿100 Mil.
Depreciation, Depletion and Amortization(DDA) was ฿14 Mil.
Selling, General, & Admin. Expense(SGA) was ฿71 Mil.
Total Current Liabilities was ฿889 Mil.
Long-Term Debt & Capital Lease Obligation was ฿63 Mil.
Net Income was 11.419 + 39.415 + 20.833 + 17.25 = ฿89 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ฿0 Mil.
Cash Flow from Operations was -421.62 + -92.627 + -167.659 + 119.943 = ฿-562 Mil.
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Total Receivables was ฿707 Mil.
Revenue was 191.519 + 288.492 + 704.673 + 447.214 = ฿1,632 Mil.
Gross Profit was 22.473 + 59.484 + 59.804 + 43.398 = ฿185 Mil.
Total Current Assets was ฿1,338 Mil.
Total Assets was ฿1,888 Mil.
Property, Plant and Equipment(Net PPE) was ฿84 Mil.
Depreciation, Depletion and Amortization(DDA) was ฿11 Mil.
Selling, General, & Admin. Expense(SGA) was ฿64 Mil.
Total Current Liabilities was ฿375 Mil.
Long-Term Debt & Capital Lease Obligation was ฿123 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) |
| = | (1776.456 / 1944.148) | / | (706.952 / 1631.898) |
| = | 0.913745 | / | 0.433208 |
| | = | 2.1093 |
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) |
| = | (185.159 / 1631.898) | / | (161.479 / 1944.148) |
| = | 0.113462 | / | 0.083059 |
| | = | 1.366 |
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 - (1912.079 + 99.634) / 2391.209) | / | (1 - (1337.719 + 83.774) / 1887.619) |
| = | 0.158705 | / | 0.246939 |
| | = | 0.6427 |
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 |
| = | 1944.148 | / | 1631.898 |
| | = | 1.1913 |
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)) |
| = | (10.523 / (10.523 + 83.774)) | / | (13.503 / (13.503 + 99.634)) |
| = | 0.111594 | / | 0.119351 |
| | = | 0.935 |
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) |
| = | (71.093 / 1944.148) | / | (64.065 / 1631.898) |
| = | 0.036568 | / | 0.039258 |
| | = | 0.9315 |
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) |
| = | ((63.012 + 889.053) / 2391.209) | / | ((122.928 + 375.297) / 1887.619) |
| = | 0.398152 | / | 0.263944 |
| | = | 1.5085 |
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 |
| = | (88.917 - 0 | - | -561.963) | / | 2391.209 |
| | = | 0.272197 |
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.
Infraset PCL has a M-score of -0.13 signals that the company is likely to be a manipulator.
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