Post Holdings Beneish M-Score Historical Data
The historical data trend for Post Holdings'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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Post Holdings Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.70 |
-2.58 |
-2.56 |
-2.42 |
-2.69 |
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Post Holdings 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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-2.53 |
-2.41 |
-2.60 |
-2.69 |
-2.61 |
Competitive Comparison
For the Packaged Foods subindustry, Post Holdings'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.
Post Holdings Beneish M-Score Distribution
For the Consumer Packaged Goods industry and Consumer Defensive sector, Post Holdings's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Post Holdings's Beneish M-Score falls into.
Post Holdings 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 Post Holdings 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 * 0.8953 | + | 0.528 * 0.9243 | + | 0.404 * 1.0532 | + | 0.892 * 1.2156 | + | 0.115 * 1.0547 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0567 | + | 4.679 * -0.043695 | - | 0.327 * 1.0074 |
| = | -2.61 |
* 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 $587 Mil.
Revenue was 1965.9 + 1945.4 + 1859.4 + 1619.9 = $7,391 Mil.
Gross Profit was 572.6 + 551.4 + 501.6 + 413.8 = $2,039 Mil.
Total Current Assets was $1,661 Mil.
Total Assets was $12,072 Mil.
Property, Plant and Equipment(Net PPE) was $2,125 Mil.
Depreciation, Depletion and Amortization(DDA) was $427 Mil.
Selling, General, & Admin. Expense(SGA) was $1,173 Mil.
Total Current Liabilities was $835 Mil.
Long-Term Debt & Capital Lease Obligation was $6,314 Mil.
Net Income was 88.1 + 65.7 + 89.6 + 57.5 = $301 Mil.
Non Operating Income was -14.5 + -23.6 + 39.5 + 0.6 = $2 Mil.
Cash Flow from Operations was 174.4 + 269.8 + 282.2 + 100 = $826 Mil.
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Total Receivables was $539 Mil.
Revenue was 1566.3 + 1579.1 + 1524.9 + 1409.7 = $6,080 Mil.
Gross Profit was 414.9 + 392.6 + 364.7 + 378.5 = $1,551 Mil.
Total Current Assets was $2,197 Mil.
Total Assets was $11,355 Mil.
Property, Plant and Equipment(Net PPE) was $1,757 Mil.
Depreciation, Depletion and Amortization(DDA) was $376 Mil.
Selling, General, & Admin. Expense(SGA) was $913 Mil.
Total Current Liabilities was $788 Mil.
Long-Term Debt & Capital Lease Obligation was $5,887 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) |
| = | (586.7 / 7390.6) | / | (539.1 / 6080) |
| = | 0.079385 | / | 0.088668 |
| | = | 0.8953 |
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) |
| = | (1550.7 / 6080) | / | (2039.4 / 7390.6) |
| = | 0.255049 | / | 0.275945 |
| | = | 0.9243 |
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 - (1660.7 + 2124.6) / 12072.4) | / | (1 - (2197.4 + 1756.5) / 11355) |
| = | 0.68645 | / | 0.651792 |
| | = | 1.0532 |
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 |
| = | 7390.6 | / | 6080 |
| | = | 1.2156 |
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)) |
| = | (376.4 / (376.4 + 1756.5)) | / | (426.9 / (426.9 + 2124.6)) |
| = | 0.176473 | / | 0.167313 |
| | = | 1.0547 |
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) |
| = | (1172.6 / 7390.6) | / | (912.9 / 6080) |
| = | 0.158661 | / | 0.150148 |
| | = | 1.0567 |
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) |
| = | ((6314 + 835.3) / 12072.4) | / | ((5886.8 + 788.2) / 11355) |
| = | 0.592202 | / | 0.587847 |
| | = | 1.0074 |
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 |
| = | (300.9 - 2 | - | 826.4) | / | 12072.4 |
| | = | -0.043695 |
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.
Post Holdings has a M-score of -2.61 suggests that the company is unlikely to be a manipulator.
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