Nutrien Beneish M-Score Historical Data
The historical data trend for Nutrien'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.
Nutrien Beneish M-Score Chart
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Nutrien 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 |
-2.67 |
-2.25 |
-2.41 |
-2.66 |
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Nutrien 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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-2.41 |
-2.55 |
-2.72 |
-2.61 |
-2.66 |
Competitive Comparison of Nutrien's Beneish M-Score
For the Agricultural Inputs subindustry, Nutrien'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.
Nutrien's Beneish M-Score Distribution in the Agriculture Industry
For the Agriculture industry and Basic Materials sector, Nutrien's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Nutrien's Beneish M-Score falls into.
Nutrien 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 Nutrien 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 * 1.1363 | + | 0.528 * 1.396 | + | 0.404 * 1.0123 | + | 0.892 * 0.767 | + | 0.115 * 0.9608 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2949 | + | 4.679 * -0.0513 | - | 0.327 * 0.982 |
| = | -2.64 |
* 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 $5,398 Mil.
Revenue was 5664 + 5631 + 11654 + 6107 = $29,056 Mil.
Gross Profit was 1768 + 1627 + 3166 + 1913 = $8,474 Mil.
Total Current Assets was $14,170 Mil.
Total Assets was $52,749 Mil.
Property, Plant and Equipment(Net PPE) was $22,461 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,169 Mil.
Selling, General, & Admin. Expense(SGA) was $4,064 Mil.
Total Current Liabilities was $12,121 Mil.
Long-Term Debt & Capital Lease Obligation was $9,912 Mil.
Net Income was 172 + 75 + 440 + 571 = $1,258 Mil.
Non Operating Income was -174 + -154 + -862 + 88 = $-1,102 Mil.
Cash Flow from Operations was 4150 + -469 + 2243 + -858 = $5,066 Mil.
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Total Receivables was $6,194 Mil.
Revenue was 7533 + 8188 + 14506 + 7657 = $37,884 Mil.
Gross Profit was 2906 + 3262 + 5999 + 3257 = $15,424 Mil.
Total Current Assets was $16,342 Mil.
Total Assets was $54,586 Mil.
Property, Plant and Equipment(Net PPE) was $21,767 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,012 Mil.
Selling, General, & Admin. Expense(SGA) was $4,092 Mil.
Total Current Liabilities was $14,280 Mil.
Long-Term Debt & Capital Lease Obligation was $8,939 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) |
| = | (5398 / 29056) | / | (6194 / 37884) |
| = | 0.185779 | / | 0.163499 |
| | = | 1.1363 |
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) |
| = | (15424 / 37884) | / | (8474 / 29056) |
| = | 0.407138 | / | 0.291644 |
| | = | 1.396 |
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 - (14170 + 22461) / 52749) | / | (1 - (16342 + 21767) / 54586) |
| = | 0.30556 | / | 0.301854 |
| | = | 1.0123 |
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 |
| = | 29056 | / | 37884 |
| | = | 0.767 |
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)) |
| = | (2012 / (2012 + 21767)) | / | (2169 / (2169 + 22461)) |
| = | 0.084612 | / | 0.088063 |
| | = | 0.9608 |
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) |
| = | (4064 / 29056) | / | (4092 / 37884) |
| = | 0.139868 | / | 0.108014 |
| | = | 1.2949 |
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) |
| = | ((9912 + 12121) / 52749) | / | ((8939 + 14280) / 54586) |
| = | 0.417695 | / | 0.425365 |
| | = | 0.982 |
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 |
| = | (1258 - -1102 | - | 5066) | / | 52749 |
| | = | -0.0513 |
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.
Nutrien has a M-score of -2.64 suggests that the company is unlikely to be a manipulator.
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