Hormel Foods Beneish M-Score Historical Data
The historical data trend for Hormel Foods'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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Hormel Foods Annual Data
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Trend |
Oct14 |
Oct15 |
Oct16 |
Oct17 |
Oct18 |
Oct19 |
Oct20 |
Oct21 |
Oct22 |
Oct23 |
| Beneish M-Score |
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-2.40 |
-2.59 |
-2.27 |
-2.58 |
-2.59 |
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Hormel Foods Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-2.50 |
-2.52 |
-2.58 |
-2.59 |
-2.70 |
Competitive Comparison
For the Packaged Foods subindustry, Hormel Foods'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.
Hormel Foods Beneish M-Score Distribution
For the Consumer Packaged Goods industry and Consumer Defensive sector, Hormel Foods's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Hormel Foods's Beneish M-Score falls into.
Hormel Foods 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 Hormel Foods 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 * 0.9649 | + | 0.528 * 1.033 | + | 0.404 * 0.9863 | + | 0.892 * 0.9799 | + | 0.115 * 0.9318 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1198 | + | 4.679 * -0.034662 | - | 0.327 * 0.9729 |
| = | -2.70 |
* 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 (Jan24) TTM: | Last Year (Jan23) TTM: |
Total Receivables was $751 Mil.
Revenue was 2996.911 + 3198.08 + 2963.299 + 2977.639 = $12,136 Mil.
Gross Profit was 508.733 + 514.424 + 498.048 + 491.419 = $2,013 Mil.
Total Current Assets was $3,367 Mil.
Total Assets was $13,513 Mil.
Property, Plant and Equipment(Net PPE) was $2,156 Mil.
Depreciation, Depletion and Amortization(DDA) was $256 Mil.
Selling, General, & Admin. Expense(SGA) was $960 Mil.
Total Current Liabilities was $2,261 Mil.
Long-Term Debt & Capital Lease Obligation was $2,357 Mil.
Net Income was 218.863 + 195.935 + 162.679 + 217.239 = $795 Mil.
Non Operating Income was 16.091 + -27.842 + 9.784 + 16.87 = $15 Mil.
Cash Flow from Operations was 403.98 + 319.091 + 317.002 + 208.125 = $1,248 Mil.
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Total Receivables was $794 Mil.
Revenue was 2970.992 + 3283.475 + 3034.414 + 3096.559 = $12,385 Mil.
Gross Profit was 495.949 + 566.417 + 506.049 + 553.471 = $2,122 Mil.
Total Current Assets was $3,195 Mil.
Total Assets was $13,283 Mil.
Property, Plant and Equipment(Net PPE) was $2,124 Mil.
Depreciation, Depletion and Amortization(DDA) was $233 Mil.
Selling, General, & Admin. Expense(SGA) was $875 Mil.
Total Current Liabilities was $1,373 Mil.
Long-Term Debt & Capital Lease Obligation was $3,293 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) |
| = | (751.048 / 12135.929) | / | (794.358 / 12385.44) |
| = | 0.061886 | / | 0.064136 |
| | = | 0.9649 |
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) |
| = | (2121.886 / 12385.44) | / | (2012.624 / 12135.929) |
| = | 0.171321 | / | 0.16584 |
| | = | 1.033 |
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 - (3367.164 + 2155.524) / 13512.983) | / | (1 - (3195.306 + 2124.402) / 13283.047) |
| = | 0.591305 | / | 0.599511 |
| | = | 0.9863 |
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 |
| = | 12135.929 | / | 12385.44 |
| | = | 0.9799 |
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)) |
| = | (233.108 / (233.108 + 2124.402)) | / | (255.875 / (255.875 + 2155.524)) |
| = | 0.098879 | / | 0.106111 |
| | = | 0.9318 |
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) |
| = | (960.497 / 12135.929) | / | (875.35 / 12385.44) |
| = | 0.079145 | / | 0.070676 |
| | = | 1.1198 |
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) |
| = | ((2357.176 + 2260.779) / 13512.983) | / | ((3292.559 + 1373.385) / 13283.047) |
| = | 0.341742 | / | 0.351271 |
| | = | 0.9729 |
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 |
| = | (794.716 - 14.903 | - | 1248.198) | / | 13512.983 |
| | = | -0.034662 |
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.
Hormel Foods has a M-score of -2.70 suggests that the company is unlikely to be a manipulator.
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