South32 Beneish M-Score Historical Data
The historical data trend for South32'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.
South32 Beneish M-Score Chart
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South32 Annual Data
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Jun14 |
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Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-2.85 |
-3.33 |
-3.27 |
-1.71 |
-2.69 |
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South32 Semi-Annual Data
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Dec23 |
| Beneish M-Score |
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-1.71 |
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-2.69 |
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Competitive Comparison of South32's Beneish M-Score
For the Other Industrial Metals & Mining subindustry, South32'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.
South32's Beneish M-Score Distribution in the Metals & Mining Industry
For the Metals & Mining industry and Basic Materials sector, South32's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where South32's Beneish M-Score falls into.
South32 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 South32 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 * 1.1501 | + | 0.528 * 1.3264 | + | 0.404 * 1.1819 | + | 0.892 * 0.8392 | + | 0.115 * 0.8652 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1 | + | 4.679 * -0.093656 | - | 0.327 * 0.9913 |
| = | -2.69 |
* 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 (Jun23) TTM: | Last Year (Jun22) TTM: |
Total Receivables was A$1,159 Mil.
Revenue was A$11,069 Mil.
Gross Profit was A$5,178 Mil.
Total Current Assets was A$4,826 Mil.
Total Assets was A$21,700 Mil.
Property, Plant and Equipment(Net PPE) was A$11,995 Mil.
Depreciation, Depletion and Amortization(DDA) was A$973 Mil.
Selling, General, & Admin. Expense(SGA) was A$0 Mil.
Total Current Liabilities was A$2,324 Mil.
Long-Term Debt & Capital Lease Obligation was A$2,050 Mil.
Net Income was A$-258 Mil.
Gross Profit was A$0 Mil.
Cash Flow from Operations was A$1,775 Mil.
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Total Receivables was A$1,201 Mil.
Revenue was A$13,190 Mil.
Gross Profit was A$8,184 Mil.
Total Current Assets was A$6,034 Mil.
Total Assets was A$23,246 Mil.
Property, Plant and Equipment(Net PPE) was A$12,790 Mil.
Depreciation, Depletion and Amortization(DDA) was A$888 Mil.
Selling, General, & Admin. Expense(SGA) was A$0 Mil.
Total Current Liabilities was A$2,699 Mil.
Long-Term Debt & Capital Lease Obligation was A$2,028 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) |
| = | (1159.22 / 11069.21) | / | (1201.012 / 13189.787) |
| = | 0.104725 | / | 0.091056 |
| | = | 1.1501 |
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) |
| = | (8183.673 / 13189.787) | / | (5177.75 / 11069.21) |
| = | 0.620455 | / | 0.467761 |
| | = | 1.3264 |
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 - (4826.11 + 11994.5) / 21700.36) | / | (1 - (6033.52 + 12789.924) / 23246.128) |
| = | 0.22487 | / | 0.190255 |
| | = | 1.1819 |
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 |
| = | 11069.21 | / | 13189.787 |
| | = | 0.8392 |
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)) |
| = | (887.952 / (887.952 + 12789.924)) | / | (972.97 / (972.97 + 11994.5)) |
| = | 0.064919 | / | 0.075032 |
| | = | 0.8652 |
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 / 11069.21) | / | (0 / 13189.787) |
| = | 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) |
| = | ((2050.24 + 2324.4) / 21700.36) | / | ((2027.775 + 2699.431) / 23246.128) |
| = | 0.201593 | / | 0.203355 |
| | = | 0.9913 |
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 |
| = | (-257.77 - 0 | - | 1774.59) | / | 21700.36 |
| | = | -0.093656 |
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.
South32 has a M-score of -2.69 suggests that the company is unlikely to be a manipulator.
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