Clean Harbors Beneish M-Score Historical Data
The historical data trend for Clean Harbors'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.
Clean Harbors Beneish M-Score Chart
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Clean Harbors Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-2.89 |
-2.30 |
-2.41 |
-2.71 |
-2.65 |
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Clean Harbors Quarterly Data
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Jun20 |
Sep20 |
Dec20 |
Mar21 |
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Mar22 |
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Sep22 |
Dec22 |
Mar23 |
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Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
Mar25 |
| Beneish M-Score |
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-2.61 |
-2.58 |
-2.59 |
-2.65 |
-2.70 |
Competitive Comparison of Clean Harbors's Beneish M-Score
For the Waste Management subindustry, Clean Harbors'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.
Clean Harbors's Beneish M-Score Distribution in the Waste Management Industry
For the Waste Management industry and Industrials sector, Clean Harbors's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Clean Harbors's Beneish M-Score falls into.
Clean Harbors 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 Clean Harbors 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 * 0.9546 | + | 0.528 * 1.0045 | + | 0.404 * 0.9276 | + | 0.892 * 1.0852 | + | 0.115 * 0.9667 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9944 | + | 4.679 * -0.050793 | - | 0.327 * 0.9535 |
| = | -2.70 |
* 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 (Mar25) TTM: | Last Year (Mar24) TTM: |
Total Receivables was $1,249 Mil.
Revenue was 1431.95 + 1431.116 + 1529.422 + 1552.719 = $5,945 Mil.
Gross Profit was 410.066 + 427.614 + 473.823 + 517.177 = $1,829 Mil.
Total Current Assets was $2,311 Mil.
Total Assets was $7,246 Mil.
Property, Plant and Equipment(Net PPE) was $2,711 Mil.
Depreciation, Depletion and Amortization(DDA) was $418 Mil.
Selling, General, & Admin. Expense(SGA) was $741 Mil.
Total Current Liabilities was $976 Mil.
Long-Term Debt & Capital Lease Obligation was $2,948 Mil.
Net Income was 58.68 + 83.974 + 115.213 + 133.28 = $391 Mil.
Non Operating Income was -0.932 + 0.606 + -1.123 + -0.167 = $-2 Mil.
Cash Flow from Operations was 1.605 + 303.938 + 239.239 + 216.045 = $761 Mil.
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Total Receivables was $1,205 Mil.
Revenue was 1376.695 + 1338.169 + 1365.696 + 1397.9 = $5,478 Mil.
Gross Profit was 405.625 + 415.022 + 421.745 + 450.388 = $1,693 Mil.
Total Current Assets was $2,106 Mil.
Total Assets was $6,940 Mil.
Property, Plant and Equipment(Net PPE) was $2,537 Mil.
Depreciation, Depletion and Amortization(DDA) was $376 Mil.
Selling, General, & Admin. Expense(SGA) was $686 Mil.
Total Current Liabilities was $1,018 Mil.
Long-Term Debt & Capital Lease Obligation was $2,924 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) |
| = | (1248.599 / 5945.207) | / | (1205.355 / 5478.46) |
| = | 0.210018 | / | 0.220017 |
| | = | 0.9546 |
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) |
| = | (1692.78 / 5478.46) | / | (1828.68 / 5945.207) |
| = | 0.308988 | / | 0.307589 |
| | = | 1.0045 |
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 - (2310.682 + 2711.034) / 7246.387) | / | (1 - (2105.796 + 2537.061) / 6939.823) |
| = | 0.307004 | / | 0.330983 |
| | = | 0.9276 |
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 |
| = | 5945.207 | / | 5478.46 |
| | = | 1.0852 |
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)) |
| = | (376.068 / (376.068 + 2537.061)) | / | (417.837 / (417.837 + 2711.034)) |
| = | 0.129094 | / | 0.133542 |
| | = | 0.9667 |
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) |
| = | (740.608 / 5945.207) | / | (686.276 / 5478.46) |
| = | 0.124572 | / | 0.125268 |
| | = | 0.9944 |
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) |
| = | ((2948.269 + 976.343) / 7246.387) | / | ((2924.168 + 1017.523) / 6939.823) |
| = | 0.541596 | / | 0.567981 |
| | = | 0.9535 |
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 |
| = | (391.147 - -1.616 | - | 760.827) | / | 7246.387 |
| | = | -0.050793 |
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.
Clean Harbors has a M-score of -2.70 suggests that the company is unlikely to be a manipulator.
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