Pan American Silver Beneish M-Score Historical Data
The historical data trend for Pan American Silver'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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Pan American Silver Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.59 |
-3.34 |
-2.70 |
0.74 |
-3.24 |
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Pan American Silver Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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0.74 |
-0.40 |
-2.43 |
-2.87 |
-3.24 |
Competitive Comparison
For the Gold subindustry, Pan American Silver'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.
Pan American Silver Beneish M-Score Distribution
For the Metals & Mining industry and Basic Materials sector, Pan American Silver's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Pan American Silver's Beneish M-Score falls into.
Pan American Silver 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 Pan American Silver 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 * 0.7342 | + | 0.528 * 0.2532 | + | 0.404 * 0.3062 | + | 0.892 * 1.5495 | + | 0.115 * 1.5806 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3523 | + | 4.679 * -0.067267 | - | 0.327 * 1.0659 |
| = | -3.24 |
* 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 $201 Mil.
Revenue was 669.6 + 616.3 + 639.9 + 390.3 = $2,316 Mil.
Gross Profit was 87.1 + 61.9 + 70.6 + 77.2 = $297 Mil.
Total Current Assets was $1,390 Mil.
Total Assets was $7,213 Mil.
Property, Plant and Equipment(Net PPE) was $5,675 Mil.
Depreciation, Depletion and Amortization(DDA) was $484 Mil.
Selling, General, & Admin. Expense(SGA) was $61 Mil.
Total Current Liabilities was $624 Mil.
Long-Term Debt & Capital Lease Obligation was $749 Mil.
Net Income was -51.5 + -21.8 + -46.8 + 16.4 = $-104 Mil.
Non Operating Income was -18.4 + 12 + -54.1 + -8.2 = $-69 Mil.
Cash Flow from Operations was 167.3 + 114.6 + 117 + 51.3 = $450 Mil.
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Total Receivables was $177 Mil.
Revenue was 375.4 + 338.9 + 340.5 + 439.9 = $1,495 Mil.
Gross Profit was 35.1 + -21.8 + -31.6 + 66.8 = $49 Mil.
Total Current Assets was $804 Mil.
Total Assets was $3,249 Mil.
Property, Plant and Equipment(Net PPE) was $2,226 Mil.
Depreciation, Depletion and Amortization(DDA) was $316 Mil.
Selling, General, & Admin. Expense(SGA) was $29 Mil.
Total Current Liabilities was $381 Mil.
Long-Term Debt & Capital Lease Obligation was $200 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) |
| = | (200.9 / 2316.1) | / | (176.6 / 1494.7) |
| = | 0.086741 | / | 0.118151 |
| | = | 0.7342 |
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) |
| = | (48.5 / 1494.7) | / | (296.8 / 2316.1) |
| = | 0.032448 | / | 0.128146 |
| | = | 0.2532 |
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 - (1390 + 5675.1) / 7213.1) | / | (1 - (804.4 + 2226.4) / 3248.5) |
| = | 0.020518 | / | 0.067016 |
| | = | 0.3062 |
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 |
| = | 2316.1 | / | 1494.7 |
| | = | 1.5495 |
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)) |
| = | (315.9 / (315.9 + 2226.4)) | / | (484.2 / (484.2 + 5675.1)) |
| = | 0.124258 | / | 0.078613 |
| | = | 1.5806 |
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) |
| = | (61.4 / 2316.1) | / | (29.3 / 1494.7) |
| = | 0.02651 | / | 0.019603 |
| | = | 1.3523 |
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) |
| = | ((749.2 + 624.2) / 7213.1) | / | ((199.5 + 380.8) / 3248.5) |
| = | 0.190404 | / | 0.178636 |
| | = | 1.0659 |
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 |
| = | (-103.7 - -68.7 | - | 450.2) | / | 7213.1 |
| | = | -0.067267 |
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.
Pan American Silver has a M-score of -3.24 suggests that the company is unlikely to be a manipulator.
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