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.
Moog Beneish M-Score Chart
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Moog Annual Data
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Trend |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
Sep24 |
| Beneish M-Score |
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-2.63 |
-2.59 |
-2.55 |
-2.26 |
-2.42 |
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Moog Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.26 |
-2.38 |
-2.34 |
-2.40 |
-2.42 |
Competitive Comparison of Moog's Beneish M-Score
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's Beneish M-Score Distribution in the Aerospace & Defense Industry
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 * 0.9097 | + | 0.528 * 0.9724 | + | 0.404 * 0.9488 | + | 0.892 * 1.0874 | + | 0.115 * 1.0842 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9687 | + | 4.679 * 0.015685 | - | 0.327 * 0.9529 |
| = | -2.42 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was $1,129 Mil.
Revenue was 917.272 + 904.735 + 930.303 + 856.85 = $3,609 Mil.
Gross Profit was 245.479 + 251.463 + 266.778 + 233.199 = $997 Mil.
Total Current Assets was $2,141 Mil.
Total Assets was $4,094 Mil.
Property, Plant and Equipment(Net PPE) was $982 Mil.
Depreciation, Depletion and Amortization(DDA) was $93 Mil.
Selling, General, & Admin. Expense(SGA) was $495 Mil.
Total Current Liabilities was $999 Mil.
Long-Term Debt & Capital Lease Obligation was $874 Mil.
Net Income was 43.045 + 56.36 + 60.003 + 47.812 = $207 Mil.
Non Operating Income was -29.808 + -8.253 + -16.683 + -4.59 = $-59 Mil.
Cash Flow from Operations was 155.789 + 30.166 + -44.002 + 60.391 = $202 Mil.
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Total Receivables was $1,141 Mil.
Revenue was 872.051 + 850.176 + 836.792 + 760.103 = $3,319 Mil.
Gross Profit was 243.898 + 222.633 + 221.315 + 203.686 = $892 Mil.
Total Current Assets was $1,985 Mil.
Total Assets was $3,808 Mil.
Property, Plant and Equipment(Net PPE) was $871 Mil.
Depreciation, Depletion and Amortization(DDA) was $90 Mil.
Selling, General, & Admin. Expense(SGA) was $470 Mil.
Total Current Liabilities was $965 Mil.
Long-Term Debt & Capital Lease Obligation was $863 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) |
| = | (1128.985 / 3609.16) | / | (1141.324 / 3319.122) |
| = | 0.312811 | / | 0.343863 |
| | = | 0.9097 |
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) |
| = | (891.532 / 3319.122) | / | (996.919 / 3609.16) |
| = | 0.268605 | / | 0.276219 |
| | = | 0.9724 |
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 - (2140.749 + 981.948) / 4093.626) | / | (1 - (1985.332 + 870.763) / 3808.036) |
| = | 0.237181 | / | 0.249982 |
| | = | 0.9488 |
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 |
| = | 3609.16 | / | 3319.122 |
| | = | 1.0874 |
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)) |
| = | (90.233 / (90.233 + 870.763)) | / | (93.106 / (93.106 + 981.948)) |
| = | 0.093895 | / | 0.086606 |
| | = | 1.0842 |
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) |
| = | (494.887 / 3609.16) | / | (469.836 / 3319.122) |
| = | 0.13712 | / | 0.141554 |
| | = | 0.9687 |
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) |
| = | ((874.139 + 999.027) / 4093.626) | / | ((863.092 + 965.473) / 3808.036) |
| = | 0.457581 | / | 0.480186 |
| | = | 0.9529 |
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 |
| = | (207.22 - -59.334 | - | 202.344) | / | 4093.626 |
| | = | 0.015685 |
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 -2.42 suggests that the company is unlikely to be a manipulator.
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