Gold Fields Beneish M-Score Historical Data
The historical data trend for Gold Fields'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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Gold Fields 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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-2.89 |
-2.43 |
-2.33 |
-2.37 |
-2.49 |
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Gold Fields 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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-2.33 |
- |
-2.37 |
- |
-2.49 |
Competitive Comparison
For the Gold subindustry, Gold Fields'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.
Gold Fields Beneish M-Score Distribution
For the Metals & Mining industry and Basic Materials sector, Gold Fields's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Gold Fields's Beneish M-Score falls into.
Gold Fields 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 Gold Fields 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 * 0.9103 | + | 0.528 * 1.0059 | + | 0.404 * 1.5663 | + | 0.892 * 1.0499 | + | 0.115 * 1.101 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.7218 | + | 4.679 * -0.032943 | - | 0.327 * 1.0238 |
| = | -2.56 |
* 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 $199 Mil.
Revenue was $4,501 Mil.
Gross Profit was $1,637 Mil.
Total Current Assets was $1,888 Mil.
Total Assets was $8,226 Mil.
Property, Plant and Equipment(Net PPE) was $5,074 Mil.
Depreciation, Depletion and Amortization(DDA) was $795 Mil.
Selling, General, & Admin. Expense(SGA) was $65 Mil.
Total Current Liabilities was $1,506 Mil.
Long-Term Debt & Capital Lease Obligation was $1,013 Mil.
Net Income was $703 Mil.
Gross Profit was $-219 Mil.
Cash Flow from Operations was $1,193 Mil.
|
Total Receivables was $208 Mil.
Revenue was $4,287 Mil.
Gross Profit was $1,569 Mil.
Total Current Assets was $1,802 Mil.
Total Assets was $7,338 Mil.
Property, Plant and Equipment(Net PPE) was $4,816 Mil.
Depreciation, Depletion and Amortization(DDA) was $844 Mil.
Selling, General, & Admin. Expense(SGA) was $36 Mil.
Total Current Liabilities was $785 Mil.
Long-Term Debt & Capital Lease Obligation was $1,409 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) |
| = | (198.5 / 4500.7) | / | (207.7 / 4286.7) |
| = | 0.044104 | / | 0.048452 |
| | = | 0.9103 |
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) |
| = | (1568.6 / 4286.7) | / | (1637.3 / 4500.7) |
| = | 0.365923 | / | 0.363788 |
| | = | 1.0059 |
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 - (1887.7 + 5074.4) / 8226.3) | / | (1 - (1802.4 + 4815.7) / 7338.1) |
| = | 0.153678 | / | 0.098118 |
| | = | 1.5663 |
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 |
| = | 4500.7 | / | 4286.7 |
| | = | 1.0499 |
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)) |
| = | (844.3 / (844.3 + 4815.7)) | / | (795.3 / (795.3 + 5074.4)) |
| = | 0.14917 | / | 0.135492 |
| | = | 1.101 |
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) |
| = | (64.9 / 4500.7) | / | (35.9 / 4286.7) |
| = | 0.01442 | / | 0.008375 |
| | = | 1.7218 |
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) |
| = | ((1013.1 + 1505.8) / 8226.3) | / | ((1409.4 + 785.4) / 7338.1) |
| = | 0.306201 | / | 0.299096 |
| | = | 1.0238 |
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 |
| = | (703.3 - -218.5 | - | 1192.8) | / | 8226.3 |
| | = | -0.032943 |
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.
Gold Fields has a M-score of -2.56 suggests that the company is unlikely to be a manipulator.
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