McCormick Beneish M-Score Historical Data
The historical data trend for McCormick'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.
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McCormick Annual Data
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Trend |
Nov14 |
Nov15 |
Nov16 |
Nov17 |
Nov18 |
Nov19 |
Nov20 |
Nov21 |
Nov22 |
Nov23 |
| Beneish M-Score |
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-2.61 |
-2.57 |
-2.42 |
-2.38 |
-2.64 |
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McCormick Quarterly Data
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May19 |
Aug19 |
Nov19 |
Feb20 |
May20 |
Aug20 |
Nov20 |
Feb21 |
May21 |
Aug21 |
Nov21 |
Feb22 |
May22 |
Aug22 |
Nov22 |
Feb23 |
May23 |
Aug23 |
Nov23 |
Feb24 |
| Beneish M-Score |
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-2.36 |
-2.40 |
-2.48 |
-2.64 |
-2.69 |
Competitive Comparison
For the Packaged Foods subindustry, McCormick'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.
McCormick Beneish M-Score Distribution
For the Consumer Packaged Goods industry and Consumer Defensive sector, McCormick's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where McCormick's Beneish M-Score falls into.
McCormick 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 McCormick 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 * 0.9485 | + | 0.528 * 0.9397 | + | 0.404 * 1.0187 | + | 0.892 * 1.0478 | + | 0.115 * 1.1009 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0551 | + | 4.679 * -0.043204 | - | 0.327 * 0.9303 |
| = | -2.69 |
* 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 (Feb24) TTM: | Last Year (Feb23) TTM: |
Total Receivables was $568 Mil.
Revenue was 1602.7 + 1752.8 + 1684.7 + 1659.2 = $6,699 Mil.
Gross Profit was 599.3 + 701.3 + 622.8 + 615.5 = $2,539 Mil.
Total Current Assets was $2,020 Mil.
Total Assets was $12,890 Mil.
Property, Plant and Equipment(Net PPE) was $1,355 Mil.
Depreciation, Depletion and Amortization(DDA) was $197 Mil.
Selling, General, & Admin. Expense(SGA) was $1,509 Mil.
Total Current Liabilities was $2,974 Mil.
Long-Term Debt & Capital Lease Obligation was $3,329 Mil.
Net Income was 166 + 219.3 + 170.1 + 152.1 = $708 Mil.
Non Operating Income was 6.9 + -3.1 + -11.1 + -0.6 = $-8 Mil.
Cash Flow from Operations was 138.4 + 577.2 + 265.9 + 290.8 = $1,272 Mil.
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Total Receivables was $571 Mil.
Revenue was 1565.5 + 1695.7 + 1595.6 + 1536.8 = $6,394 Mil.
Gross Profit was 562.9 + 624.4 + 566.7 + 523 = $2,277 Mil.
Total Current Assets was $2,411 Mil.
Total Assets was $13,205 Mil.
Property, Plant and Equipment(Net PPE) was $1,225 Mil.
Depreciation, Depletion and Amortization(DDA) was $199 Mil.
Selling, General, & Admin. Expense(SGA) was $1,365 Mil.
Total Current Liabilities was $3,321 Mil.
Long-Term Debt & Capital Lease Obligation was $3,620 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) |
| = | (567.5 / 6699.4) | / | (571 / 6393.6) |
| = | 0.084709 | / | 0.089308 |
| | = | 0.9485 |
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) |
| = | (2277 / 6393.6) | / | (2538.9 / 6699.4) |
| = | 0.356137 | / | 0.378974 |
| | = | 0.9397 |
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 - (2020.2 + 1354.5) / 12890.1) | / | (1 - (2411.3 + 1225.2) / 13205.4) |
| = | 0.738194 | / | 0.72462 |
| | = | 1.0187 |
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 |
| = | 6699.4 | / | 6393.6 |
| | = | 1.0478 |
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)) |
| = | (199.4 / (199.4 + 1225.2)) | / | (197.3 / (197.3 + 1354.5)) |
| = | 0.139969 | / | 0.127143 |
| | = | 1.1009 |
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) |
| = | (1509.1 / 6699.4) | / | (1365 / 6393.6) |
| = | 0.225259 | / | 0.213495 |
| | = | 1.0551 |
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) |
| = | ((3329.1 + 2973.8) / 12890.1) | / | ((3619.8 + 3321) / 13205.4) |
| = | 0.488972 | / | 0.525603 |
| | = | 0.9303 |
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 |
| = | (707.5 - -7.9 | - | 1272.3) | / | 12890.1 |
| | = | -0.043204 |
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.
McCormick has a M-score of -2.69 suggests that the company is unlikely to be a manipulator.
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