Hubbell Beneish M-Score Historical Data
The historical data trend for Hubbell'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.
Hubbell Beneish M-Score Chart
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Hubbell Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.72 |
-2.91 |
-2.38 |
-2.48 |
-2.52 |
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Hubbell 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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-2.48 |
-2.69 |
-2.64 |
-2.57 |
-2.52 |
Competitive Comparison of Hubbell's Beneish M-Score
For the Electrical Equipment & Parts subindustry, Hubbell'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.
Hubbell's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Hubbell's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Hubbell's Beneish M-Score falls into.
Hubbell 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 Hubbell 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 * 0.9753 | + | 0.528 * 0.8464 | + | 0.404 * 1.1213 | + | 0.892 * 1.0859 | + | 0.115 * 1.1764 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0168 | + | 4.679 * -0.014825 | - | 0.327 * 1.037 |
| = | -2.52 |
* 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 $785 Mil.
Revenue was 1345.8 + 1375.8 + 1365.9 + 1285.4 = $5,373 Mil.
Gross Profit was 456.2 + 487.4 + 496.2 + 448.3 = $1,888 Mil.
Total Current Assets was $2,167 Mil.
Total Assets was $6,914 Mil.
Property, Plant and Equipment(Net PPE) was $653 Mil.
Depreciation, Depletion and Amortization(DDA) was $150 Mil.
Selling, General, & Admin. Expense(SGA) was $850 Mil.
Total Current Liabilities was $1,323 Mil.
Long-Term Debt & Capital Lease Obligation was $2,142 Mil.
Net Income was 171 + 200.1 + 206.8 + 181.9 = $760 Mil.
Non Operating Income was -6.1 + -3.5 + -4.8 + -4.1 = $-19 Mil.
Cash Flow from Operations was 345.5 + 193.9 + 227.7 + 113.7 = $881 Mil.
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Total Receivables was $742 Mil.
Revenue was 1219.6 + 1316.2 + 1256 + 1156.1 = $4,948 Mil.
Gross Profit was 366.8 + 398.5 + 383.2 + 323.1 = $1,472 Mil.
Total Current Assets was $2,021 Mil.
Total Assets was $5,403 Mil.
Property, Plant and Equipment(Net PPE) was $528 Mil.
Depreciation, Depletion and Amortization(DDA) was $149 Mil.
Selling, General, & Admin. Expense(SGA) was $770 Mil.
Total Current Liabilities was $1,089 Mil.
Long-Term Debt & Capital Lease Obligation was $1,523 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) |
| = | (785.4 / 5372.9) | / | (741.6 / 4947.9) |
| = | 0.146178 | / | 0.149882 |
| | = | 0.9753 |
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) |
| = | (1471.6 / 4947.9) | / | (1888.1 / 5372.9) |
| = | 0.297419 | / | 0.351412 |
| | = | 0.8464 |
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 - (2167.2 + 652.6) / 6914) | / | (1 - (2021.4 + 528) / 5402.6) |
| = | 0.592161 | / | 0.528116 |
| | = | 1.1213 |
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 |
| = | 5372.9 | / | 4947.9 |
| | = | 1.0859 |
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)) |
| = | (148.5 / (148.5 + 528)) | / | (149.7 / (149.7 + 652.6)) |
| = | 0.219512 | / | 0.186589 |
| | = | 1.1764 |
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) |
| = | (849.6 / 5372.9) | / | (769.5 / 4947.9) |
| = | 0.158127 | / | 0.155521 |
| | = | 1.0168 |
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) |
| = | ((2142 + 1323.4) / 6914) | / | ((1522.8 + 1088.5) / 5402.6) |
| = | 0.501215 | / | 0.483341 |
| | = | 1.037 |
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 |
| = | (759.8 - -18.5 | - | 880.8) | / | 6914 |
| | = | -0.014825 |
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.
Hubbell has a M-score of -2.52 suggests that the company is unlikely to be a manipulator.
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