StarHub Beneish M-Score Historical Data
The historical data trend for StarHub'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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StarHub 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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|
|
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-2.76 |
-3.19 |
-3.15 |
-2.84 |
-2.81 |
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StarHub Semi-Annual Data
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Jun14 |
Dec14 |
Jun15 |
Dec15 |
Jun16 |
Dec16 |
Jun17 |
Dec17 |
Jun18 |
Dec18 |
Jun19 |
Dec19 |
Jun20 |
Dec20 |
Jun21 |
Dec21 |
Jun22 |
Dec22 |
Jun23 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
|
|
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|
|
|
|
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-3.15 |
- |
-2.84 |
- |
-2.81 |
Competitive Comparison
For the Telecom Services subindustry, StarHub'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.
StarHub Beneish M-Score Distribution
For the Telecommunication Services industry and Communication Services sector, StarHub's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where StarHub's Beneish M-Score falls into.
StarHub 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 StarHub 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 * 0.9549 | + | 0.528 * 0.977 | + | 0.404 * 1.0066 | + | 0.892 * 1.0348 | + | 0.115 * 1.0377 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.884 | + | 4.679 * -0.068861 | - | 0.327 * 0.9868 |
| = | -2.79 |
* 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 $465 Mil.
Revenue was $1,781 Mil.
Gross Profit was $953 Mil.
Total Current Assets was $1,037 Mil.
Total Assets was $2,278 Mil.
Property, Plant and Equipment(Net PPE) was $528 Mil.
Depreciation, Depletion and Amortization(DDA) was $181 Mil.
Selling, General, & Admin. Expense(SGA) was $20 Mil.
Total Current Liabilities was $721 Mil.
Long-Term Debt & Capital Lease Obligation was $901 Mil.
Net Income was $112 Mil.
Gross Profit was $0 Mil.
Cash Flow from Operations was $269 Mil.
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Total Receivables was $470 Mil.
Revenue was $1,722 Mil.
Gross Profit was $900 Mil.
Total Current Assets was $1,050 Mil.
Total Assets was $2,318 Mil.
Property, Plant and Equipment(Net PPE) was $547 Mil.
Depreciation, Depletion and Amortization(DDA) was $197 Mil.
Selling, General, & Admin. Expense(SGA) was $22 Mil.
Total Current Liabilities was $858 Mil.
Long-Term Debt & Capital Lease Obligation was $814 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) |
| = | (464.605 / 1781.473) | / | (470.188 / 1721.63) |
| = | 0.260798 | / | 0.273106 |
| | = | 0.9549 |
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) |
| = | (900.059 / 1721.63) | / | (953.232 / 1781.473) |
| = | 0.522795 | / | 0.535081 |
| | = | 0.977 |
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 - (1036.859 + 527.963) / 2278.433) | / | (1 - (1049.933 + 547.048) / 2318.316) |
| = | 0.313203 | / | 0.311146 |
| | = | 1.0066 |
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 |
| = | 1781.473 | / | 1721.63 |
| | = | 1.0348 |
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)) |
| = | (197.145 / (197.145 + 547.048)) | / | (180.992 / (180.992 + 527.963)) |
| = | 0.264911 | / | 0.255294 |
| | = | 1.0377 |
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) |
| = | (19.893 / 1781.473) | / | (21.749 / 1721.63) |
| = | 0.011167 | / | 0.012633 |
| | = | 0.884 |
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) |
| = | ((900.758 + 721.117) / 2278.433) | / | ((814.1 + 858.263) / 2318.316) |
| = | 0.711838 | / | 0.72137 |
| | = | 0.9868 |
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 |
| = | (112.304 - 0 | - | 269.199) | / | 2278.433 |
| | = | -0.068861 |
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.
StarHub has a M-score of -2.79 suggests that the company is unlikely to be a manipulator.
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