Moog Beneish M-Score Historical Data
The historical data trend for Moog'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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Moog Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.28 |
-2.63 |
-2.59 |
-2.55 |
-2.26 |
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Moog 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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-2.24 |
-2.17 |
-2.16 |
-2.26 |
-2.38 |
Competitive Comparison
For the Aerospace & Defense subindustry, Moog'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.
Moog Beneish M-Score Distribution
For the Aerospace & Defense industry and Industrials sector, Moog's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Moog's Beneish M-Score falls into.
Moog 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 Moog 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 * 0.9632 | + | 0.528 * 1.004 | + | 0.404 * 0.9195 | + | 0.892 * 1.112 | + | 0.115 * 1.1081 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9502 | + | 4.679 * 0.007881 | - | 0.327 * 0.9825 |
| = | -2.38 |
* 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 $1,142 Mil.
Revenue was 856.85 + 872.051 + 850.176 + 836.792 = $3,416 Mil.
Gross Profit was 233.199 + 243.898 + 222.633 + 221.315 = $921 Mil.
Total Current Assets was $2,117 Mil.
Total Assets was $3,988 Mil.
Property, Plant and Equipment(Net PPE) was $902 Mil.
Depreciation, Depletion and Amortization(DDA) was $92 Mil.
Selling, General, & Admin. Expense(SGA) was $475 Mil.
Total Current Liabilities was $1,010 Mil.
Long-Term Debt & Capital Lease Obligation was $920 Mil.
Net Income was 47.812 + 39.582 + 42.387 + 43.013 = $173 Mil.
Non Operating Income was -4.59 + -29.077 + -6.602 + -6.61 = $-47 Mil.
Cash Flow from Operations was 60.391 + 153.032 + 15.919 + -41.099 = $188 Mil.
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Total Receivables was $1,066 Mil.
Revenue was 760.103 + 767.999 + 772.911 + 770.787 = $3,072 Mil.
Gross Profit was 203.686 + 203.166 + 211.743 + 213.012 = $832 Mil.
Total Current Assets was $1,933 Mil.
Total Assets was $3,658 Mil.
Property, Plant and Equipment(Net PPE) was $758 Mil.
Depreciation, Depletion and Amortization(DDA) was $87 Mil.
Selling, General, & Admin. Expense(SGA) was $450 Mil.
Total Current Liabilities was $886 Mil.
Long-Term Debt & Capital Lease Obligation was $916 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) |
| = | (1142.17 / 3415.869) | / | (1066.34 / 3071.8) |
| = | 0.334372 | / | 0.347138 |
| | = | 0.9632 |
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) |
| = | (831.607 / 3071.8) | / | (921.045 / 3415.869) |
| = | 0.270723 | / | 0.269637 |
| | = | 1.004 |
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 - (2116.615 + 902.171) / 3987.955) | / | (1 - (1933.183 + 757.992) / 3658.045) |
| = | 0.243024 | / | 0.264313 |
| | = | 0.9195 |
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 |
| = | 3415.869 | / | 3071.8 |
| | = | 1.112 |
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)) |
| = | (87.081 / (87.081 + 757.992)) | / | (92.496 / (92.496 + 902.171)) |
| = | 0.103046 | / | 0.092992 |
| | = | 1.1081 |
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) |
| = | (475.396 / 3415.869) | / | (449.899 / 3071.8) |
| = | 0.139173 | / | 0.146461 |
| | = | 0.9502 |
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) |
| = | ((920.103 + 1009.831) / 3987.955) | / | ((916.058 + 885.666) / 3658.045) |
| = | 0.483941 | / | 0.492537 |
| | = | 0.9825 |
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 |
| = | (172.794 - -46.879 | - | 188.243) | / | 3987.955 |
| | = | 0.007881 |
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.
Moog has a M-score of -2.38 suggests that the company is unlikely to be a manipulator.
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