Waste Connections Beneish M-Score Historical Data
The historical data trend for Waste Connections'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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Waste Connections Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.69 |
-2.70 |
-2.67 |
-2.71 |
-2.77 |
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Waste Connections 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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-2.71 |
-2.69 |
-2.76 |
-2.74 |
-2.77 |
Competitive Comparison
For the Waste Management subindustry, Waste Connections'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.
Waste Connections Beneish M-Score Distribution
For the Waste Management industry and Industrials sector, Waste Connections's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Waste Connections's Beneish M-Score falls into.
Waste Connections 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 Waste Connections 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 * 0.9074 | + | 0.528 * 0.976 | + | 0.404 * 1.0006 | + | 0.892 * 1.1123 | + | 0.115 * 0.965 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0315 | + | 4.679 * -0.063502 | - | 0.327 * 0.9656 |
| = | -2.77 |
* 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 $885 Mil.
Revenue was 2035.609 + 2064.744 + 2021.095 + 1900.503 = $8,022 Mil.
Gross Profit was 839.989 + 860.141 + 823.746 + 753.562 = $3,277 Mil.
Total Current Assets was $1,142 Mil.
Total Assets was $17,916 Mil.
Property, Plant and Equipment(Net PPE) was $7,490 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,003 Mil.
Selling, General, & Admin. Expense(SGA) was $799 Mil.
Total Current Liabilities was $1,688 Mil.
Long-Term Debt & Capital Lease Obligation was $6,963 Mil.
Net Income was 126.753 + 229.026 + 209.208 + 197.813 = $763 Mil.
Non Operating Income was -165.46 + -51.105 + -11.059 + 1.309 = $-226 Mil.
Cash Flow from Operations was 555.941 + 554.164 + 574.354 + 442.358 = $2,127 Mil.
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Total Receivables was $877 Mil.
Revenue was 1869.301 + 1879.868 + 1816.435 + 1646.255 = $7,212 Mil.
Gross Profit was 731.328 + 759.239 + 728.543 + 656.737 = $2,876 Mil.
Total Current Assets was $1,118 Mil.
Total Assets was $17,135 Mil.
Property, Plant and Equipment(Net PPE) was $7,143 Mil.
Depreciation, Depletion and Amortization(DDA) was $919 Mil.
Selling, General, & Admin. Expense(SGA) was $696 Mil.
Total Current Liabilities was $1,513 Mil.
Long-Term Debt & Capital Lease Obligation was $7,056 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) |
| = | (885.077 / 8021.951) | / | (876.917 / 7211.859) |
| = | 0.110332 | / | 0.121594 |
| | = | 0.9074 |
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) |
| = | (2875.847 / 7211.859) | / | (3277.438 / 8021.951) |
| = | 0.398766 | / | 0.408559 |
| | = | 0.976 |
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 - (1141.785 + 7490.113) / 17915.876) | / | (1 - (1117.645 + 7143.421) / 17134.603) |
| = | 0.518198 | / | 0.517872 |
| | = | 1.0006 |
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 |
| = | 8021.951 | / | 7211.859 |
| | = | 1.1123 |
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)) |
| = | (918.96 / (918.96 + 7143.421)) | / | (1003.211 / (1003.211 + 7490.113)) |
| = | 0.113981 | / | 0.118118 |
| | = | 0.965 |
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) |
| = | (799.12 / 8021.951) | / | (696.467 / 7211.859) |
| = | 0.099617 | / | 0.096572 |
| | = | 1.0315 |
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) |
| = | ((6963.211 + 1687.932) / 17915.876) | / | ((7055.611 + 1512.643) / 17134.603) |
| = | 0.482876 | / | 0.500056 |
| | = | 0.9656 |
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 |
| = | (762.8 - -226.315 | - | 2126.817) | / | 17915.876 |
| | = | -0.063502 |
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.
Waste Connections has a M-score of -2.77 suggests that the company is unlikely to be a manipulator.
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