Airports Of Thailand Beneish M-Score Historical Data
The historical data trend for Airports Of Thailand'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.
Airports Of Thailand Beneish M-Score Chart
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Airports Of Thailand Annual Data
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Trend |
Sep14 |
Sep15 |
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Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.67 |
-0.51 |
-2.66 |
2.13 |
-1.63 |
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Airports Of Thailand Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
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Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-1.63 |
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Competitive Comparison of Airports Of Thailand's Beneish M-Score
For the Airports & Air Services subindustry, Airports Of Thailand'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.
Airports Of Thailand's Beneish M-Score Distribution in the Transportation Industry
For the Transportation industry and Industrials sector, Airports Of Thailand's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Airports Of Thailand's Beneish M-Score falls into.
Airports Of Thailand 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 Airports Of Thailand 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 * 1.0965 | + | 0.528 * -0.339 | + | 0.404 * 0.8502 | + | 0.892 * 3.0027 | + | 0.115 * 1.0321 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.039134 | - | 0.327 * 0.9691 |
| = | -1.54 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was $340 Mil.
Revenue was $1,342 Mil.
Gross Profit was $699 Mil.
Total Current Assets was $530 Mil.
Total Assets was $5,451 Mil.
Property, Plant and Equipment(Net PPE) was $4,206 Mil.
Depreciation, Depletion and Amortization(DDA) was $247 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $649 Mil.
Long-Term Debt & Capital Lease Obligation was $1,434 Mil.
Net Income was $245 Mil.
Gross Profit was $-12 Mil.
Cash Flow from Operations was $470 Mil.
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Total Receivables was $103 Mil.
Revenue was $447 Mil.
Gross Profit was $-79 Mil.
Total Current Assets was $229 Mil.
Total Assets was $4,959 Mil.
Property, Plant and Equipment(Net PPE) was $3,965 Mil.
Depreciation, Depletion and Amortization(DDA) was $241 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $391 Mil.
Long-Term Debt & Capital Lease Obligation was $1,565 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) |
| = | (340.059 / 1341.533) | / | (103.284 / 446.769) |
| = | 0.253485 | / | 0.23118 |
| | = | 1.0965 |
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) |
| = | (-78.917 / 446.769) | / | (698.96 / 1341.533) |
| = | -0.176639 | / | 0.521016 |
| | = | -0.339 |
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 - (529.856 + 4206.072) / 5451.055) | / | (1 - (228.678 + 3965.177) / 4959.044) |
| = | 0.131191 | / | 0.154302 |
| | = | 0.8502 |
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 |
| = | 1341.533 | / | 446.769 |
| | = | 3.0027 |
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)) |
| = | (240.968 / (240.968 + 3965.177)) | / | (247.187 / (247.187 + 4206.072)) |
| = | 0.05729 | / | 0.055507 |
| | = | 1.0321 |
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 / 1341.533) | / | (0 / 446.769) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | ((1434.136 + 649.088) / 5451.055) | / | ((1564.523 + 391.058) / 4959.044) |
| = | 0.382169 | / | 0.394346 |
| | = | 0.9691 |
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 |
| = | (244.973 - -11.894 | - | 470.189) | / | 5451.055 |
| | = | -0.039134 |
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.
Airports Of Thailand has a M-score of -1.54 signals that the company is likely to be a manipulator.
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