Curtiss-Wright Beneish M-Score Historical Data
The historical data trend for Curtiss-Wright'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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Curtiss-Wright Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.56 |
-2.49 |
-2.55 |
-2.41 |
-2.57 |
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Curtiss-Wright 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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-2.41 |
-2.43 |
-2.49 |
-2.51 |
-2.57 |
Competitive Comparison
For the Aerospace & Defense subindustry, Curtiss-Wright'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.
Curtiss-Wright Beneish M-Score Distribution
For the Aerospace & Defense industry and Industrials sector, Curtiss-Wright's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Curtiss-Wright's Beneish M-Score falls into.
Curtiss-Wright 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 Curtiss-Wright 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 * 0.9103 | + | 0.528 * 0.9954 | + | 0.404 * 0.9602 | + | 0.892 * 1.1128 | + | 0.115 * 0.9355 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0018 | + | 4.679 * -0.026713 | - | 0.327 * 0.8788 |
| = | -2.57 |
* 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 $733 Mil.
Revenue was 785.791 + 724.326 + 704.396 + 630.86 = $2,845 Mil.
Gross Profit was 304.729 + 281.468 + 259.573 + 221.408 = $1,067 Mil.
Total Current Assets was $1,717 Mil.
Total Assets was $4,621 Mil.
Property, Plant and Equipment(Net PPE) was $474 Mil.
Depreciation, Depletion and Amortization(DDA) was $116 Mil.
Selling, General, & Admin. Expense(SGA) was $497 Mil.
Total Current Liabilities was $807 Mil.
Long-Term Debt & Capital Lease Obligation was $1,165 Mil.
Net Income was 119.886 + 96.778 + 80.999 + 56.846 = $355 Mil.
Non Operating Income was 7.117 + 7.023 + 7.954 + 7.767 = $30 Mil.
Cash Flow from Operations was 282.372 + 146.364 + 110.952 + -91.599 = $448 Mil.
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Total Receivables was $723 Mil.
Revenue was 757.665 + 630.542 + 609.357 + 559.461 = $2,557 Mil.
Gross Profit was 292.484 + 232.209 + 228.514 + 201.402 = $955 Mil.
Total Current Assets was $1,516 Mil.
Total Assets was $4,448 Mil.
Property, Plant and Equipment(Net PPE) was $497 Mil.
Depreciation, Depletion and Amortization(DDA) was $112 Mil.
Selling, General, & Admin. Expense(SGA) was $446 Mil.
Total Current Liabilities was $981 Mil.
Long-Term Debt & Capital Lease Obligation was $1,178 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) |
| = | (732.678 / 2845.373) | / | (723.304 / 2557.025) |
| = | 0.257498 | / | 0.282869 |
| | = | 0.9103 |
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) |
| = | (954.609 / 2557.025) | / | (1067.178 / 2845.373) |
| = | 0.373328 | / | 0.375057 |
| | = | 0.9954 |
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 - (1717.08 + 474.231) / 4620.969) | / | (1 - (1516.014 + 496.563) / 4448.303) |
| = | 0.52579 | / | 0.547563 |
| | = | 0.9602 |
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 |
| = | 2845.373 | / | 2557.025 |
| | = | 1.1128 |
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)) |
| = | (112.027 / (112.027 + 496.563)) | / | (116.172 / (116.172 + 474.231)) |
| = | 0.184076 | / | 0.196767 |
| | = | 0.9355 |
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) |
| = | (496.812 / 2845.373) | / | (445.679 / 2557.025) |
| = | 0.174603 | / | 0.174296 |
| | = | 1.0018 |
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) |
| = | ((1164.57 + 806.544) / 4620.969) | / | ((1178.144 + 981.045) / 4448.303) |
| = | 0.426559 | / | 0.485396 |
| | = | 0.8788 |
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 |
| = | (354.509 - 29.861 | - | 448.089) | / | 4620.969 |
| | = | -0.026713 |
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.
Curtiss-Wright has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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