Flowers Foods Beneish M-Score Historical Data
The historical data trend for Flowers 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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Flowers Foods Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.76 |
-2.75 |
-2.58 |
-2.56 |
-2.81 |
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Flowers Foods 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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-2.56 |
-2.44 |
-2.39 |
-2.76 |
-2.81 |
Competitive Comparison
For the Packaged Foods subindustry, Flowers 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.
Flowers Foods Beneish M-Score Distribution
For the Consumer Packaged Goods industry and Consumer Defensive sector, Flowers Foods's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Flowers Foods's Beneish M-Score falls into.
Flowers 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 Flowers 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 * 0.9336 | + | 0.528 * 0.9926 | + | 0.404 * 1.0477 | + | 0.892 * 1.0593 | + | 0.115 * 1.0281 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0815 | + | 4.679 * -0.061753 | - | 0.327 * 1.1099 |
| = | -2.81 |
* 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 $346 Mil.
Revenue was 1129.027 + 1199.26 + 1228.05 + 1534.493 = $5,091 Mil.
Gross Profit was 541.308 + 581.792 + 601.953 + 733.641 = $2,459 Mil.
Total Current Assets was $688 Mil.
Total Assets was $3,427 Mil.
Property, Plant and Equipment(Net PPE) was $1,240 Mil.
Depreciation, Depletion and Amortization(DDA) was $152 Mil.
Selling, General, & Admin. Expense(SGA) was $2,120 Mil.
Total Current Liabilities was $659 Mil.
Long-Term Debt & Capital Lease Obligation was $1,285 Mil.
Net Income was 35.676 + -46.73 + 63.76 + 70.71 = $123 Mil.
Non Operating Income was -6.49 + -1.213 + -2.499 + -4.112 = $-14 Mil.
Cash Flow from Operations was 92.035 + 128.411 + 70.955 + 57.952 = $349 Mil.
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Total Receivables was $349 Mil.
Revenue was 1082.67 + 1158.169 + 1129.051 + 1435.932 = $4,806 Mil.
Gross Profit was 506.972 + 542.548 + 542.967 + 711.34 = $2,304 Mil.
Total Current Assets was $805 Mil.
Total Assets was $3,313 Mil.
Property, Plant and Equipment(Net PPE) was $1,125 Mil.
Depreciation, Depletion and Amortization(DDA) was $142 Mil.
Selling, General, & Admin. Expense(SGA) was $1,850 Mil.
Total Current Liabilities was $564 Mil.
Long-Term Debt & Capital Lease Obligation was $1,129 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) |
| = | (345.608 / 5090.83) | / | (349.477 / 4805.822) |
| = | 0.067888 | / | 0.07272 |
| | = | 0.9336 |
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) |
| = | (2303.827 / 4805.822) | / | (2458.694 / 5090.83) |
| = | 0.479383 | / | 0.482965 |
| | = | 0.9926 |
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 - (687.713 + 1239.845) / 3426.953) | / | (1 - (804.94 + 1124.539) / 3312.994) |
| = | 0.43753 | / | 0.417603 |
| | = | 1.0477 |
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 |
| = | 5090.83 | / | 4805.822 |
| | = | 1.0593 |
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)) |
| = | (141.957 / (141.957 + 1124.539)) | / | (151.709 / (151.709 + 1239.845)) |
| = | 0.112086 | / | 0.109021 |
| | = | 1.0281 |
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) |
| = | (2119.532 / 5090.83) | / | (1850.059 / 4805.822) |
| = | 0.416343 | / | 0.384962 |
| | = | 1.0815 |
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) |
| = | ((1285.039 + 659.152) / 3426.953) | / | ((1128.935 + 564.425) / 3312.994) |
| = | 0.567324 | / | 0.511127 |
| | = | 1.1099 |
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 |
| = | (123.416 - -14.314 | - | 349.353) | / | 3426.953 |
| | = | -0.061753 |
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.
Flowers Foods has a M-score of -2.81 suggests that the company is unlikely to be a manipulator.
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