Keppel Beneish M-Score Historical Data
The historical data trend for Keppel'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.
Keppel Beneish M-Score Chart
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Keppel Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.16 |
-2.75 |
-2.09 |
-2.96 |
-1.38 |
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Keppel 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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-2.09 |
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-2.96 |
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-1.38 |
Competitive Comparison of Keppel's Beneish M-Score
For the Conglomerates subindustry, Keppel'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.
Keppel's Beneish M-Score Distribution in the Conglomerates Industry
For the Conglomerates industry and Industrials sector, Keppel's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Keppel's Beneish M-Score falls into.
Keppel 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 Keppel 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 * 1.2744 | + | 0.528 * 0.7729 | + | 0.404 * 1.4938 | + | 0.892 * 1.0679 | + | 0.115 * 1.001 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * 0.149782 | - | 0.327 * 0.9463 |
| = | -1.37 |
* 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 $1,769 Mil.
Revenue was $5,229 Mil.
Gross Profit was $1,477 Mil.
Total Current Assets was $4,779 Mil.
Total Assets was $20,147 Mil.
Property, Plant and Equipment(Net PPE) was $838 Mil.
Depreciation, Depletion and Amortization(DDA) was $166 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $4,608 Mil.
Long-Term Debt & Capital Lease Obligation was $6,516 Mil.
Net Income was $3,062 Mil.
Gross Profit was $0 Mil.
Cash Flow from Operations was $44 Mil.
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Total Receivables was $1,300 Mil.
Revenue was $4,897 Mil.
Gross Profit was $1,069 Mil.
Total Current Assets was $10,985 Mil.
Total Assets was $22,980 Mil.
Property, Plant and Equipment(Net PPE) was $901 Mil.
Depreciation, Depletion and Amortization(DDA) was $179 Mil.
Selling, General, & Admin. Expense(SGA) was $0 Mil.
Total Current Liabilities was $8,404 Mil.
Long-Term Debt & Capital Lease Obligation was $5,005 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) |
| = | (1769.095 / 5229.433) | / | (1299.945 / 4896.966) |
| = | 0.338296 | / | 0.265459 |
| | = | 1.2744 |
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) |
| = | (1069.174 / 4896.966) | / | (1477.151 / 5229.433) |
| = | 0.218334 | / | 0.282469 |
| | = | 0.7729 |
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 - (4778.731 + 837.684) / 20147.063) | / | (1 - (10984.59 + 900.909) / 22980.453) |
| = | 0.721229 | / | 0.4828 |
| | = | 1.4938 |
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 |
| = | 5229.433 | / | 4896.966 |
| | = | 1.0679 |
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)) |
| = | (178.989 / (178.989 + 900.909)) | / | (166.234 / (166.234 + 837.684)) |
| = | 0.165746 | / | 0.165585 |
| | = | 1.001 |
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 / 5229.433) | / | (0 / 4896.966) |
| = | 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) |
| = | ((6516.037 + 4608.384) / 20147.063) | / | ((5005.096 + 8403.854) / 22980.453) |
| = | 0.552161 | / | 0.583494 |
| | = | 0.9463 |
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 |
| = | (3061.521 - 0 | - | 43.862) | / | 20147.063 |
| | = | 0.149782 |
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.
Keppel has a M-score of -1.37 signals that the company is likely to be a manipulator.
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