Xylem Beneish M-Score Historical Data
The historical data trend for Xylem'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.
Xylem Beneish M-Score Chart
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Xylem Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.61 |
-2.88 |
-2.46 |
-2.46 |
-1.88 |
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Xylem Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-1.75 |
-1.88 |
-1.91 |
-2.48 |
-2.48 |
Competitive Comparison of Xylem's Beneish M-Score
For the Specialty Industrial Machinery subindustry, Xylem'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.
Xylem's Beneish M-Score Distribution in the Industrial Products Industry
For the Industrial Products industry and Industrials sector, Xylem's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Xylem's Beneish M-Score falls into.
Xylem 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 Xylem 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 * 0.8277 | + | 0.528 * 1.0162 | + | 0.404 * 0.9692 | + | 0.892 * 1.2476 | + | 0.115 * 0.7414 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9333 | + | 4.679 * -0.015393 | - | 0.327 * 0.9132 |
| = | -2.48 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $1,707 Mil.
Revenue was 2104 + 2169 + 2033 + 2118 = $8,424 Mil.
Gross Profit was 784 + 819 + 752 + 756 = $3,111 Mil.
Total Current Assets was $4,013 Mil.
Total Assets was $16,046 Mil.
Property, Plant and Equipment(Net PPE) was $1,158 Mil.
Depreciation, Depletion and Amortization(DDA) was $557 Mil.
Selling, General, & Admin. Expense(SGA) was $1,870 Mil.
Total Current Liabilities was $2,052 Mil.
Long-Term Debt & Capital Lease Obligation was $1,977 Mil.
Net Income was 217 + 194 + 153 + 266 = $830 Mil.
Non Operating Income was -5 + -18 + -9 + -34 = $-66 Mil.
Cash Flow from Operations was 311 + 288 + 89 + 455 = $1,143 Mil.
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Total Receivables was $1,653 Mil.
Revenue was 2076 + 1722 + 1448 + 1506 = $6,752 Mil.
Gross Profit was 764 + 651 + 546 + 573 = $2,534 Mil.
Total Current Assets was $3,651 Mil.
Total Assets was $15,905 Mil.
Property, Plant and Equipment(Net PPE) was $1,132 Mil.
Depreciation, Depletion and Amortization(DDA) was $359 Mil.
Selling, General, & Admin. Expense(SGA) was $1,606 Mil.
Total Current Liabilities was $2,120 Mil.
Long-Term Debt & Capital Lease Obligation was $2,253 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) |
| = | (1707 / 8424) | / | (1653 / 6752) |
| = | 0.202635 | / | 0.244816 |
| | = | 0.8277 |
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) |
| = | (2534 / 6752) | / | (3111 / 8424) |
| = | 0.375296 | / | 0.369302 |
| | = | 1.0162 |
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 - (4013 + 1158) / 16046) | / | (1 - (3651 + 1132) / 15905) |
| = | 0.677739 | / | 0.699277 |
| | = | 0.9692 |
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 |
| = | 8424 | / | 6752 |
| | = | 1.2476 |
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)) |
| = | (359 / (359 + 1132)) | / | (557 / (557 + 1158)) |
| = | 0.240778 | / | 0.324781 |
| | = | 0.7414 |
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) |
| = | (1870 / 8424) | / | (1606 / 6752) |
| = | 0.221985 | / | 0.237855 |
| | = | 0.9333 |
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) |
| = | ((1977 + 2052) / 16046) | / | ((2253 + 2120) / 15905) |
| = | 0.251091 | / | 0.274945 |
| | = | 0.9132 |
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 |
| = | (830 - -66 | - | 1143) | / | 16046 |
| | = | -0.015393 |
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.
Xylem has a M-score of -2.48 suggests that the company is unlikely to be a manipulator.
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