RTX Beneish M-Score Historical Data
The historical data trend for RTX'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.
RTX Beneish M-Score Chart
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RTX Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.90 |
-1.69 |
-2.61 |
-2.66 |
-2.53 |
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RTX 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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-2.51 |
-2.53 |
-2.61 |
-2.68 |
-2.67 |
Competitive Comparison of RTX's Beneish M-Score
For the Aerospace & Defense subindustry, RTX'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.
RTX's Beneish M-Score Distribution in the Aerospace & Defense Industry
For the Aerospace & Defense industry and Industrials sector, RTX's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where RTX's Beneish M-Score falls into.
RTX 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 RTX 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 * 0.9243 | + | 0.528 * 0.9038 | + | 0.404 * 0.9507 | + | 0.892 * 1.1782 | + | 0.115 * 1.0133 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8583 | + | 4.679 * -0.038981 | - | 0.327 * 1.1527 |
| = | -2.67 |
* 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 $24,781 Mil.
Revenue was 20089 + 19721 + 19305 + 19927 = $79,042 Mil.
Gross Profit was 4034 + 3580 + 3561 + 4009 = $15,184 Mil.
Total Current Assets was $51,764 Mil.
Total Assets was $164,822 Mil.
Property, Plant and Equipment(Net PPE) was $17,732 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,284 Mil.
Selling, General, & Admin. Expense(SGA) was $4,917 Mil.
Total Current Liabilities was $52,247 Mil.
Long-Term Debt & Capital Lease Obligation was $40,415 Mil.
Net Income was 1472 + 111 + 1709 + 1426 = $4,718 Mil.
Non Operating Income was 381 + -6 + 4 + 455 = $834 Mil.
Cash Flow from Operations was 2523 + 2733 + 342 + 4711 = $10,309 Mil.
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Total Receivables was $22,754 Mil.
Revenue was 13464 + 18315 + 17214 + 18093 = $67,086 Mil.
Gross Profit was 714 + 3797 + 3569 + 3567 = $11,647 Mil.
Total Current Assets was $46,518 Mil.
Total Assets was $162,443 Mil.
Property, Plant and Equipment(Net PPE) was $17,102 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,200 Mil.
Selling, General, & Admin. Expense(SGA) was $4,862 Mil.
Total Current Liabilities was $45,002 Mil.
Long-Term Debt & Capital Lease Obligation was $34,224 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) |
| = | (24781 / 79042) | / | (22754 / 67086) |
| = | 0.313517 | / | 0.339177 |
| | = | 0.9243 |
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) |
| = | (11647 / 67086) | / | (15184 / 79042) |
| = | 0.173613 | / | 0.1921 |
| | = | 0.9038 |
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 - (51764 + 17732) / 164822) | / | (1 - (46518 + 17102) / 162443) |
| = | 0.578357 | / | 0.608355 |
| | = | 0.9507 |
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 |
| = | 79042 | / | 67086 |
| | = | 1.1782 |
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)) |
| = | (4200 / (4200 + 17102)) | / | (4284 / (4284 + 17732)) |
| = | 0.197165 | / | 0.194586 |
| | = | 1.0133 |
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) |
| = | (4917 / 79042) | / | (4862 / 67086) |
| = | 0.062207 | / | 0.072474 |
| | = | 0.8583 |
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) |
| = | ((40415 + 52247) / 164822) | / | ((34224 + 45002) / 162443) |
| = | 0.562194 | / | 0.487716 |
| | = | 1.1527 |
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 |
| = | (4718 - 834 | - | 10309) | / | 164822 |
| | = | -0.038981 |
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.
RTX has a M-score of -2.67 suggests that the company is unlikely to be a manipulator.
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