Western Forest Products Beneish M-Score Historical Data
The historical data trend for Western Forest Products'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.
Western Forest Products Beneish M-Score Chart
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Western Forest Products Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.36 |
-2.53 |
-3.14 |
-1.24 |
-1.43 |
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Western Forest Products 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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-1.24 |
-1.58 |
-1.21 |
-0.78 |
-1.43 |
Competitive Comparison of Western Forest Products's Beneish M-Score
For the Lumber & Wood Production subindustry, Western Forest Products'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.
Western Forest Products's Beneish M-Score Distribution in the Forest Products Industry
For the Forest Products industry and Basic Materials sector, Western Forest Products's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Western Forest Products's Beneish M-Score falls into.
Western Forest Products 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 Western Forest Products 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 * 1.3554 | + | 0.528 * 3.5232 | + | 0.404 * 1.0092 | + | 0.892 * 0.7046 | + | 0.115 * 0.9195 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1404 | + | 4.679 * -0.028512 | - | 0.327 * 1.5608 |
| = | -1.43 |
* 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 C$74 Mil.
Revenue was 246.6 + 231.1 + 276 + 263.8 = C$1,018 Mil.
Gross Profit was 28.6 + -0.5 + 6.3 + 16.5 = C$51 Mil.
Total Current Assets was C$335 Mil.
Total Assets was C$915 Mil.
Property, Plant and Equipment(Net PPE) was C$354 Mil.
Depreciation, Depletion and Amortization(DDA) was C$54 Mil.
Selling, General, & Admin. Expense(SGA) was C$116 Mil.
Total Current Liabilities was C$121 Mil.
Long-Term Debt & Capital Lease Obligation was C$97 Mil.
Net Income was -13.8 + -16.7 + -21 + -17 = C$-69 Mil.
Non Operating Income was -3.4 + 2.4 + -2.4 + -5.3 = C$-9 Mil.
Cash Flow from Operations was -0.8 + -14.1 + 7 + -25.8 = C$-34 Mil.
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Total Receivables was C$78 Mil.
Revenue was 291 + 356 + 437.4 + 359.6 = C$1,444 Mil.
Gross Profit was 27.5 + 41.4 + 94.2 + 91.4 = C$255 Mil.
Total Current Assets was C$340 Mil.
Total Assets was C$933 Mil.
Property, Plant and Equipment(Net PPE) was C$365 Mil.
Depreciation, Depletion and Amortization(DDA) was C$50 Mil.
Selling, General, & Admin. Expense(SGA) was C$145 Mil.
Total Current Liabilities was C$126 Mil.
Long-Term Debt & Capital Lease Obligation was C$16 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) |
| = | (74.4 / 1017.5) | / | (77.9 / 1444) |
| = | 0.07312 | / | 0.053947 |
| | = | 1.3554 |
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) |
| = | (254.5 / 1444) | / | (50.9 / 1017.5) |
| = | 0.176247 | / | 0.050025 |
| | = | 3.5232 |
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 - (334.9 + 354.4) / 915.4) | / | (1 - (339.8 + 364.7) / 932.8) |
| = | 0.246996 | / | 0.244747 |
| | = | 1.0092 |
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 |
| = | 1017.5 | / | 1444 |
| | = | 0.7046 |
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)) |
| = | (50.2 / (50.2 + 364.7)) | / | (53.7 / (53.7 + 354.4)) |
| = | 0.120993 | / | 0.131585 |
| | = | 0.9195 |
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) |
| = | (116.2 / 1017.5) | / | (144.6 / 1444) |
| = | 0.114201 | / | 0.100139 |
| | = | 1.1404 |
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) |
| = | ((96.8 + 121) / 915.4) | / | ((16.4 + 125.8) / 932.8) |
| = | 0.237929 | / | 0.152444 |
| | = | 1.5608 |
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 |
| = | (-68.5 - -8.7 | - | -33.7) | / | 915.4 |
| | = | -0.028512 |
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.
Western Forest Products has a M-score of -1.43 signals that the company is likely to be a manipulator.
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