Ptt PCL Beneish M-Score Historical Data
The historical data trend for Ptt 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.
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Ptt 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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|
|
|
|
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-2.82 |
-3.12 |
-2.36 |
-2.10 |
-2.87 |
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Ptt PCL Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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|
|
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|
|
|
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|
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|
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|
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-2.10 |
-2.60 |
-2.87 |
-3.07 |
-2.87 |
Competitive Comparison
For the Oil & Gas Integrated subindustry, Ptt 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.
Ptt PCL Beneish M-Score Distribution
For the Oil & Gas industry and Energy sector, Ptt PCL's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Ptt PCL's Beneish M-Score falls into.
Ptt 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 Ptt 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 * 1.0061 | + | 0.528 * 1.1506 | + | 0.404 * 0.9593 | + | 0.892 * 0.9327 | + | 0.115 * 0.9769 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9837 | + | 4.679 * -0.089892 | - | 0.327 * 0.9431 |
| = | -2.87 |
* 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 $9,458 Mil.
Revenue was 23072.898 + 22368.21 + 22287.099 + 21956.013 = $89,684 Mil.
Gross Profit was 2193.461 + 3558.844 + 2309.641 + 2680.437 = $10,742 Mil.
Total Current Assets was $30,924 Mil.
Total Assets was $98,924 Mil.
Property, Plant and Equipment(Net PPE) was $50,074 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,933 Mil.
Selling, General, & Admin. Expense(SGA) was $3,774 Mil.
Total Current Liabilities was $16,829 Mil.
Long-Term Debt & Capital Lease Obligation was $27,013 Mil.
Net Income was 936.652 + 872.151 + 575.947 + 808.232 = $3,193 Mil.
Non Operating Income was 1215.892 + -399.651 + -37.657 + 397.877 = $1,176 Mil.
Cash Flow from Operations was 2468.586 + 2433.074 + 3005.678 + 3001.676 = $10,909 Mil.
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Total Receivables was $10,079 Mil.
Revenue was 22928.313 + 23865.693 + 26541.425 + 22815.151 = $96,151 Mil.
Gross Profit was 2015.489 + 2207.935 + 5026.05 + 4001.602 = $13,251 Mil.
Total Current Assets was $29,937 Mil.
Total Assets was $98,240 Mil.
Property, Plant and Equipment(Net PPE) was $49,745 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,776 Mil.
Selling, General, & Admin. Expense(SGA) was $4,114 Mil.
Total Current Liabilities was $17,043 Mil.
Long-Term Debt & Capital Lease Obligation was $29,125 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) |
| = | (9458.106 / 89684.22) | / | (10078.98 / 96150.582) |
| = | 0.10546 | / | 0.104825 |
| | = | 1.0061 |
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) |
| = | (13251.076 / 96150.582) | / | (10742.383 / 89684.22) |
| = | 0.137816 | / | 0.11978 |
| | = | 1.1506 |
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 - (30923.608 + 50074.012) / 98924.042) | / | (1 - (29937.294 + 49745.14) / 98240.407) |
| = | 0.181214 | / | 0.188904 |
| | = | 0.9593 |
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 |
| = | 89684.22 | / | 96150.582 |
| | = | 0.9327 |
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)) |
| = | (4775.989 / (4775.989 + 49745.14)) | / | (4932.605 / (4932.605 + 50074.012)) |
| = | 0.087599 | / | 0.089673 |
| | = | 0.9769 |
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) |
| = | (3774.341 / 89684.22) | / | (4113.548 / 96150.582) |
| = | 0.042085 | / | 0.042782 |
| | = | 0.9837 |
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) |
| = | ((27013.385 + 16829.415) / 98924.042) | / | ((29125.077 + 17042.645) / 98240.407) |
| = | 0.443197 | / | 0.469946 |
| | = | 0.9431 |
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 |
| = | (3192.982 - 1176.461 | - | 10909.014) | / | 98924.042 |
| | = | -0.089892 |
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.
Ptt PCL has a M-score of -2.87 suggests that the company is unlikely to be a manipulator.
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