ASEFA PCL Beneish M-Score Historical Data
The historical data trend for ASEFA 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.
ASEFA PCL Beneish M-Score Chart
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ASEFA PCL Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.25 |
-2.09 |
-2.20 |
-2.14 |
-2.27 |
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ASEFA PCL Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-1.90 |
-2.16 |
-2.35 |
-2.27 |
-2.60 |
Competitive Comparison of ASEFA PCL's Beneish M-Score
For the Electrical Equipment & Parts subindustry, ASEFA 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.
ASEFA PCL's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, ASEFA PCL's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where ASEFA PCL's Beneish M-Score falls into.
ASEFA 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 ASEFA 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 * 0.8778 | + | 0.528 * 0.8906 | + | 0.404 * 1.4969 | + | 0.892 * 0.9489 | + | 0.115 * 1.2253 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1172 | + | 4.679 * -0.018061 | - | 0.327 * 1.066 |
| = | -2.60 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was ฿966 Mil.
Revenue was 674.994 + 979.638 + 794.618 + 795.93 = ฿3,245 Mil.
Gross Profit was 129.751 + 200.597 + 146.872 + 146.751 = ฿624 Mil.
Total Current Assets was ฿1,960 Mil.
Total Assets was ฿3,098 Mil.
Property, Plant and Equipment(Net PPE) was ฿792 Mil.
Depreciation, Depletion and Amortization(DDA) was ฿44 Mil.
Selling, General, & Admin. Expense(SGA) was ฿477 Mil.
Total Current Liabilities was ฿1,408 Mil.
Long-Term Debt & Capital Lease Obligation was ฿13 Mil.
Net Income was 10.09 + 66.438 + 34.458 + 33.218 = ฿144 Mil.
Non Operating Income was -1.447 + 5.702 + -0.017 + -0.419 = ฿4 Mil.
Cash Flow from Operations was 177.555 + -17.671 + 53.413 + -16.952 = ฿196 Mil.
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Total Receivables was ฿1,159 Mil.
Revenue was 863.157 + 937.249 + 853.252 + 766.311 = ฿3,420 Mil.
Gross Profit was 142.795 + 179.259 + 122.02 + 141.536 = ฿586 Mil.
Total Current Assets was ฿2,128 Mil.
Total Assets was ฿2,952 Mil.
Property, Plant and Equipment(Net PPE) was ฿604 Mil.
Depreciation, Depletion and Amortization(DDA) was ฿42 Mil.
Selling, General, & Admin. Expense(SGA) was ฿450 Mil.
Total Current Liabilities was ฿1,267 Mil.
Long-Term Debt & Capital Lease Obligation was ฿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) |
| = | (965.773 / 3245.18) | / | (1159.42 / 3419.969) |
| = | 0.297602 | / | 0.339015 |
| | = | 0.8778 |
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) |
| = | (585.61 / 3419.969) | / | (623.971 / 3245.18) |
| = | 0.171233 | / | 0.192276 |
| | = | 0.8906 |
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 - (1959.588 + 791.83) / 3098.322) | / | (1 - (2128.019 + 603.523) / 2952.375) |
| = | 0.111965 | / | 0.074798 |
| | = | 1.4969 |
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 |
| = | 3245.18 | / | 3419.969 |
| | = | 0.9489 |
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)) |
| = | (41.593 / (41.593 + 603.523)) | / | (43.979 / (43.979 + 791.83)) |
| = | 0.064474 | / | 0.052618 |
| | = | 1.2253 |
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) |
| = | (477.02 / 3245.18) | / | (449.964 / 3419.969) |
| = | 0.146993 | / | 0.13157 |
| | = | 1.1172 |
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) |
| = | ((13.437 + 1408.067) / 3098.322) | / | ((3.284 + 1267.347) / 2952.375) |
| = | 0.458798 | / | 0.430376 |
| | = | 1.066 |
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 |
| = | (144.204 - 3.819 | - | 196.345) | / | 3098.322 |
| | = | -0.018061 |
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.
ASEFA PCL has a M-score of -2.60 suggests that the company is unlikely to be a manipulator.
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