FAT Brands Beneish M-Score Historical Data
The historical data trend for FAT Brands'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.
FAT Brands Beneish M-Score Chart
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FAT Brands Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-1.80 |
-2.01 |
2.56 |
-1.13 |
-2.64 |
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FAT Brands 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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-1.13 |
-2.24 |
-2.90 |
-3.24 |
-2.64 |
Competitive Comparison of FAT Brands's Beneish M-Score
For the Restaurants subindustry, FAT Brands'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.
FAT Brands's Beneish M-Score Distribution in the Restaurants Industry
For the Restaurants industry and Consumer Cyclical sector, FAT Brands's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where FAT Brands's Beneish M-Score falls into.
FAT Brands 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 FAT Brands 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 * 0.7505 | + | 0.528 * 1.1026 | + | 0.404 * 0.8828 | + | 0.892 * 1.1798 | + | 0.115 * 1.4719 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.761 | + | 4.679 * -0.038262 | - | 0.327 * 1.0575 |
| = | -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 $21.1 Mil.
Revenue was 158.636 + 109.366 + 106.764 + 105.691 = $480.5 Mil.
Gross Profit was 84.314 + 38.527 + 47.062 + 36.077 = $206.0 Mil.
Total Current Assets was $121.0 Mil.
Total Assets was $1,388.2 Mil.
Property, Plant and Equipment(Net PPE) was $320.5 Mil.
Depreciation, Depletion and Amortization(DDA) was $31.1 Mil.
Selling, General, & Admin. Expense(SGA) was $152.3 Mil.
Total Current Liabilities was $276.6 Mil.
Long-Term Debt & Capital Lease Obligation was $1,322.1 Mil.
Net Income was -26.237 + -24.656 + -7.091 + -32.126 = $-90.1 Mil.
Non Operating Income was 1.768 + -3.259 + 0.109 + -0.003 = $-1.4 Mil.
Cash Flow from Operations was -12.572 + -1.824 + -9.497 + -11.715 = $-35.6 Mil.
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Total Receivables was $23.9 Mil.
Revenue was 103.814 + 103.222 + 102.785 + 97.403 = $407.2 Mil.
Gross Profit was 70.926 + 36.78 + 52.439 + 32.347 = $192.5 Mil.
Total Current Assets was $95.7 Mil.
Total Assets was $1,213.3 Mil.
Property, Plant and Equipment(Net PPE) was $180.3 Mil.
Depreciation, Depletion and Amortization(DDA) was $27.0 Mil.
Selling, General, & Admin. Expense(SGA) was $169.7 Mil.
Total Current Liabilities was $267.0 Mil.
Long-Term Debt & Capital Lease Obligation was $1,054.3 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) |
| = | (21.146 / 480.457) | / | (23.88 / 407.224) |
| = | 0.044012 | / | 0.058641 |
| | = | 0.7505 |
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) |
| = | (192.492 / 407.224) | / | (205.98 / 480.457) |
| = | 0.472693 | / | 0.428717 |
| | = | 1.1026 |
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 - (121.009 + 320.535) / 1388.238) | / | (1 - (95.701 + 180.314) / 1213.303) |
| = | 0.681939 | / | 0.772509 |
| | = | 0.8828 |
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 |
| = | 480.457 | / | 407.224 |
| | = | 1.1798 |
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)) |
| = | (27.015 / (27.015 + 180.314)) | / | (31.131 / (31.131 + 320.535)) |
| = | 0.1303 | / | 0.088524 |
| | = | 1.4719 |
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) |
| = | (152.346 / 480.457) | / | (169.678 / 407.224) |
| = | 0.317086 | / | 0.41667 |
| | = | 0.761 |
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) |
| = | ((1322.052 + 276.602) / 1388.238) | / | ((1054.25 + 267.02) / 1213.303) |
| = | 1.151571 | / | 1.088986 |
| | = | 1.0575 |
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 |
| = | (-90.11 - -1.385 | - | -35.608) | / | 1388.238 |
| | = | -0.038262 |
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.
FAT Brands has a M-score of -2.64 suggests that the company is unlikely to be a manipulator.
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