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.
Waste Connections Beneish M-Score Chart
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Waste Connections Annual Data
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Dec14 |
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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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Jun19 |
Sep19 |
Dec19 |
Mar20 |
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Mar21 |
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Mar23 |
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Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.69 |
-2.76 |
-2.74 |
-2.77 |
-2.71 |
Competitive Comparison of Waste Connections's Beneish M-Score
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's Beneish M-Score Distribution in the Waste Management Industry
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 * 1.0029 | + | 0.528 * 0.9667 | + | 0.404 * 0.9859 | + | 0.892 * 1.0975 | + | 0.115 * 1.0408 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0359 | + | 4.679 * -0.06026 | - | 0.327 * 1.0308 |
| = | -2.71 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was $897 Mil.
Revenue was 2072.653 + 2035.609 + 2064.744 + 2021.095 = $8,194 Mil.
Gross Profit was 850.87 + 839.989 + 860.141 + 823.746 = $3,375 Mil.
Total Current Assets was $1,217 Mil.
Total Assets was $19,083 Mil.
Property, Plant and Equipment(Net PPE) was $8,101 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,023 Mil.
Selling, General, & Admin. Expense(SGA) was $826 Mil.
Total Current Liabilities was $1,632 Mil.
Long-Term Debt & Capital Lease Obligation was $8,045 Mil.
Net Income was 230.054 + 126.753 + 229.026 + 209.208 = $795 Mil.
Non Operating Income was -2.177 + -165.46 + -51.105 + -11.059 = $-230 Mil.
Cash Flow from Operations was 490.309 + 555.941 + 554.164 + 574.354 = $2,175 Mil.
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Total Receivables was $815 Mil.
Revenue was 1900.503 + 1869.301 + 1879.868 + 1816.435 = $7,466 Mil.
Gross Profit was 753.562 + 731.328 + 759.239 + 728.543 = $2,973 Mil.
Total Current Assets was $1,134 Mil.
Total Assets was $17,227 Mil.
Property, Plant and Equipment(Net PPE) was $7,152 Mil.
Depreciation, Depletion and Amortization(DDA) was $945 Mil.
Selling, General, & Admin. Expense(SGA) was $727 Mil.
Total Current Liabilities was $1,383 Mil.
Long-Term Debt & Capital Lease Obligation was $7,091 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) |
| = | (896.682 / 8194.101) | / | (814.68 / 7466.107) |
| = | 0.10943 | / | 0.109117 |
| | = | 1.0029 |
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) |
| = | (2972.672 / 7466.107) | / | (3374.746 / 8194.101) |
| = | 0.398156 | / | 0.411851 |
| | = | 0.9667 |
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 - (1217.054 + 8100.675) / 19082.66) | / | (1 - (1134.258 + 7151.65) / 17227.094) |
| = | 0.511717 | / | 0.519019 |
| | = | 0.9859 |
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 |
| = | 8194.101 | / | 7466.107 |
| | = | 1.0975 |
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)) |
| = | (944.716 / (944.716 + 7151.65)) | / | (1022.851 / (1022.851 + 8100.675)) |
| = | 0.116684 | / | 0.112111 |
| | = | 1.0408 |
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) |
| = | (826.188 / 8194.101) | / | (726.72 / 7466.107) |
| = | 0.100827 | / | 0.097336 |
| | = | 1.0359 |
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) |
| = | ((8044.61 + 1631.541) / 19082.66) | / | ((7090.89 + 1383.184) / 17227.094) |
| = | 0.507065 | / | 0.491904 |
| | = | 1.0308 |
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 |
| = | (795.041 - -229.801 | - | 2174.768) | / | 19082.66 |
| | = | -0.06026 |
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 -2.71 suggests that the company is unlikely to be a manipulator.
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