Whitecap Resources Beneish M-Score Historical Data
The historical data trend for Whitecap Resources'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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Whitecap Resources 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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-2.83 |
-0.76 |
-1.85 |
-2.83 |
0.71 |
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Whitecap Resources 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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-2.83 |
-3.23 |
-3.40 |
-1.95 |
0.71 |
Competitive Comparison
For the Oil & Gas E&P subindustry, Whitecap Resources'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.
Whitecap Resources Beneish M-Score Distribution
For the Oil & Gas industry and Energy sector, Whitecap Resources's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Whitecap Resources's Beneish M-Score falls into.
Whitecap Resources 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 Whitecap Resources 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 * 1.0796 | + | 0.528 * 1.06 | + | 0.404 * 10.3488 | + | 0.892 * 0.7816 | + | 0.115 * 1.0159 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1626 | + | 4.679 * -0.112816 | - | 0.327 * 0.7355 |
| = | 0.74 |
* 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 $298 Mil.
Revenue was 737.925 + 763.358 + 657.384 + 696.192 = $2,855 Mil.
Gross Profit was 450.73 + 477.644 + 404.561 + 421.18 = $1,754 Mil.
Total Current Assets was $381 Mil.
Total Assets was $7,157 Mil.
Property, Plant and Equipment(Net PPE) was $6,682 Mil.
Depreciation, Depletion and Amortization(DDA) was $642 Mil.
Selling, General, & Admin. Expense(SGA) was $275 Mil.
Total Current Liabilities was $423 Mil.
Long-Term Debt & Capital Lease Obligation was $1,025 Mil.
Net Income was 222.346 + 112.852 + 132.019 + 191.917 = $659 Mil.
Non Operating Income was 100.924 + -58.237 + 38.988 + 92.304 = $174 Mil.
Cash Flow from Operations was 354.949 + 282.906 + 312.284 + 342.469 = $1,293 Mil.
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Total Receivables was $353 Mil.
Revenue was 891.792 + 866.707 + 1054.124 + 839.731 = $3,652 Mil.
Gross Profit was 576.371 + 546.968 + 714.699 + 540.679 = $2,379 Mil.
Total Current Assets was $716 Mil.
Total Assets was $7,015 Mil.
Property, Plant and Equipment(Net PPE) was $6,290 Mil.
Depreciation, Depletion and Amortization(DDA) was $615 Mil.
Selling, General, & Admin. Expense(SGA) was $303 Mil.
Total Current Liabilities was $555 Mil.
Long-Term Debt & Capital Lease Obligation was $1,374 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) |
| = | (298.301 / 2854.859) | / | (353.478 / 3652.354) |
| = | 0.104489 | / | 0.096781 |
| | = | 1.0796 |
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) |
| = | (2378.717 / 3652.354) | / | (1754.115 / 2854.859) |
| = | 0.651283 | / | 0.614431 |
| | = | 1.06 |
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 - (381.261 + 6681.947) / 7157.275) | / | (1 - (715.789 + 6290.247) / 7014.943) |
| = | 0.013143 | / | 0.00127 |
| | = | 10.3488 |
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 |
| = | 2854.859 | / | 3652.354 |
| | = | 0.7816 |
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)) |
| = | (614.827 / (614.827 + 6290.247)) | / | (641.888 / (641.888 + 6681.947)) |
| = | 0.08904 | / | 0.087644 |
| | = | 1.0159 |
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) |
| = | (275.158 / 2854.859) | / | (302.791 / 3652.354) |
| = | 0.096382 | / | 0.082903 |
| | = | 1.1626 |
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) |
| = | ((1024.821 + 423.077) / 7157.275) | / | ((1374.31 + 555.171) / 7014.943) |
| = | 0.202297 | / | 0.275053 |
| | = | 0.7355 |
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 |
| = | (659.134 - 173.979 | - | 1292.608) | / | 7157.275 |
| | = | -0.112816 |
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.
Whitecap Resources has a M-score of 0.74 signals that the company is likely to be a manipulator.
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