Keyera Beneish M-Score Historical Data
The historical data trend for Keyera'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.
Keyera Beneish M-Score Chart
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Keyera Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.62 |
-1.85 |
-2.49 |
-2.89 |
-2.99 |
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Keyera Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-2.89 |
-3.02 |
-2.57 |
-2.74 |
-2.99 |
Competitive Comparison of Keyera's Beneish M-Score
For the Oil & Gas Midstream subindustry, Keyera'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.
Keyera's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Keyera's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Keyera's Beneish M-Score falls into.
Keyera 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 Keyera 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 * 0.8838 | + | 0.528 * 1.0861 | + | 0.404 * 0.8664 | + | 0.892 * 0.991 | + | 0.115 * 0.879 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1277 | + | 4.679 * -0.091973 | - | 0.327 * 0.9756 |
| = | -3.06 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was $449 Mil.
Revenue was 1359.091 + 1449.599 + 1253.434 + 1123.438 = $5,186 Mil.
Gross Profit was 152.617 + 249.369 + 205.399 + 145.155 = $753 Mil.
Total Current Assets was $795 Mil.
Total Assets was $6,146 Mil.
Property, Plant and Equipment(Net PPE) was $5,187 Mil.
Depreciation, Depletion and Amortization(DDA) was $256 Mil.
Selling, General, & Admin. Expense(SGA) was $131 Mil.
Total Current Liabilities was $837 Mil.
Long-Term Debt & Capital Lease Obligation was $2,478 Mil.
Net Income was 62.403 + 136.299 + 103.741 + 52.389 = $355 Mil.
Non Operating Income was -0.105 + 1.946 + 2.209 + -4.797 = $-1 Mil.
Cash Flow from Operations was 222.104 + 205.567 + 199.092 + 294.06 = $921 Mil.
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Total Receivables was $513 Mil.
Revenue was 1715.586 + 1081.047 + 1128.427 + 1307.829 = $5,233 Mil.
Gross Profit was 265.517 + 147.332 + 221.738 + 190.2 = $825 Mil.
Total Current Assets was $796 Mil.
Total Assets was $6,544 Mil.
Property, Plant and Equipment(Net PPE) was $5,547 Mil.
Depreciation, Depletion and Amortization(DDA) was $239 Mil.
Selling, General, & Admin. Expense(SGA) was $117 Mil.
Total Current Liabilities was $593 Mil.
Long-Term Debt & Capital Lease Obligation was $3,026 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) |
| = | (449.294 / 5185.562) | / | (512.997 / 5232.889) |
| = | 0.086643 | / | 0.098033 |
| | = | 0.8838 |
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) |
| = | (824.787 / 5232.889) | / | (752.54 / 5185.562) |
| = | 0.157616 | / | 0.145122 |
| | = | 1.0861 |
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 - (794.673 + 5187.439) / 6145.758) | / | (1 - (796.074 + 5547.221) / 6544.433) |
| = | 0.026627 | / | 0.030734 |
| | = | 0.8664 |
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 |
| = | 5185.562 | / | 5232.889 |
| | = | 0.991 |
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)) |
| = | (239.366 / (239.366 + 5547.221)) | / | (256.172 / (256.172 + 5187.439)) |
| = | 0.041366 | / | 0.047059 |
| | = | 0.879 |
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) |
| = | (130.53 / 5185.562) | / | (116.807 / 5232.889) |
| = | 0.025172 | / | 0.022322 |
| | = | 1.1277 |
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) |
| = | ((2477.861 + 837.44) / 6145.758) | / | ((3025.998 + 592.74) / 6544.433) |
| = | 0.539445 | / | 0.552949 |
| | = | 0.9756 |
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 |
| = | (354.832 - -0.747 | - | 920.823) | / | 6145.758 |
| | = | -0.091973 |
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.
Keyera has a M-score of -3.06 suggests that the company is unlikely to be a manipulator.
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