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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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-2.52 |
-1.74 |
-1.75 |
-1.88 |
-1.91 |
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 * 1.056 | + | 0.528 * 1.0323 | + | 0.404 * 1.2631 | + | 0.892 * 1.323 | + | 0.115 * 0.8908 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9486 | + | 4.679 * -0.012745 | - | 0.327 * 0.6376 |
| = | -1.96 |
* 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 R$8,172 Mil.
Revenue was 10123.933 + 10377.776 + 10252.741 + 8358.071 = R$39,113 Mil.
Gross Profit was 3744.81 + 3704.249 + 3773.167 + 3159.759 = R$14,382 Mil.
Total Current Assets was R$19,386 Mil.
Total Assets was R$79,298 Mil.
Property, Plant and Equipment(Net PPE) was R$5,682 Mil.
Depreciation, Depletion and Amortization(DDA) was R$2,511 Mil.
Selling, General, & Admin. Expense(SGA) was R$9,233 Mil.
Total Current Liabilities was R$11,608 Mil.
Long-Term Debt & Capital Lease Obligation was R$9,885 Mil.
Net Income was 761.909 + 1303.347 + 750.682 + 446.54 = R$3,262 Mil.
Non Operating Income was -44.818 + -166.593 + -64.203 + -101.928 = R$-378 Mil.
Cash Flow from Operations was 443.202 + 2229.409 + 1842.135 + 135.904 = R$4,651 Mil.
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Total Receivables was R$5,849 Mil.
Revenue was 7542.053 + 7899.572 + 7236.168 + 6885.063 = R$29,563 Mil.
Gross Profit was 2843.896 + 3005.614 + 2747.646 + 2624.804 = R$11,222 Mil.
Total Current Assets was R$15,678 Mil.
Total Assets was R$41,356 Mil.
Property, Plant and Equipment(Net PPE) was R$3,287 Mil.
Depreciation, Depletion and Amortization(DDA) was R$1,234 Mil.
Selling, General, & Admin. Expense(SGA) was R$7,357 Mil.
Total Current Liabilities was R$7,782 Mil.
Long-Term Debt & Capital Lease Obligation was R$9,797 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) |
| = | (8171.852 / 39112.521) | / | (5849.258 / 29562.856) |
| = | 0.208932 | / | 0.197858 |
| | = | 1.056 |
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) |
| = | (11221.96 / 29562.856) | / | (14381.985 / 39112.521) |
| = | 0.379597 | / | 0.367708 |
| | = | 1.0323 |
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 - (19386.361 + 5681.952) / 79298.335) | / | (1 - (15677.886 + 3286.627) / 41356.284) |
| = | 0.683873 | / | 0.541436 |
| | = | 1.2631 |
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 |
| = | 39112.521 | / | 29562.856 |
| | = | 1.323 |
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)) |
| = | (1234.231 / (1234.231 + 3286.627)) | / | (2511.095 / (2511.095 + 5681.952)) |
| = | 0.273008 | / | 0.306491 |
| | = | 0.8908 |
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) |
| = | (9233.384 / 39112.521) | / | (7356.845 / 29562.856) |
| = | 0.236072 | / | 0.248854 |
| | = | 0.9486 |
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) |
| = | ((9884.903 + 11607.914) / 79298.335) | / | ((9797.377 + 7781.648) / 41356.284) |
| = | 0.271037 | / | 0.425063 |
| | = | 0.6376 |
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 |
| = | (3262.478 - -377.542 | - | 4650.65) | / | 79298.335 |
| | = | -0.012745 |
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 -1.96 suggests that the company is unlikely to be a manipulator.
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