Owens-Corning Beneish M-Score Historical Data
The historical data trend for Owens-Corning'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.
|
Owens-Corning Annual Data
|
|
Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
|
|
|
|
|
|
-2.75 |
-2.72 |
-2.75 |
-2.73 |
-2.72 |
|
Owens-Corning Quarterly Data
|
|
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
-2.73 |
-2.62 |
-2.60 |
-2.80 |
-2.72 |
Competitive Comparison
For the Building Products & Equipment subindustry, Owens-Corning'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.
Owens-Corning Beneish M-Score Distribution
For the Construction industry and Industrials sector, Owens-Corning's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Owens-Corning's Beneish M-Score falls into.
Owens-Corning 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 Owens-Corning 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 * 1.036 | + | 0.528 * 0.9666 | + | 0.404 * 0.9551 | + | 0.892 * 0.9914 | + | 0.115 * 0.9126 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0439 | + | 4.679 * -0.050458 | - | 0.327 * 0.9306 |
| = | -2.72 |
* 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 $987 Mil.
Revenue was 2304 + 2479 + 2563 + 2331 = $9,677 Mil.
Gross Profit was 615 + 727 + 752 + 589 = $2,683 Mil.
Total Current Assets was $3,917 Mil.
Total Assets was $11,237 Mil.
Property, Plant and Equipment(Net PPE) was $4,063 Mil.
Depreciation, Depletion and Amortization(DDA) was $609 Mil.
Selling, General, & Admin. Expense(SGA) was $831 Mil.
Total Current Liabilities was $2,324 Mil.
Long-Term Debt & Capital Lease Obligation was $2,780 Mil.
Net Income was 131 + 337 + 345 + 383 = $1,196 Mil.
Non Operating Income was -146 + 1 + 0 + 189 = $44 Mil.
Cash Flow from Operations was 698 + 691 + 494 + -164 = $1,719 Mil.
|
Total Receivables was $961 Mil.
Revenue was 2285 + 2529 + 2601 + 2346 = $9,761 Mil.
Gross Profit was 570 + 693 + 734 + 619 = $2,616 Mil.
Total Current Assets was $3,556 Mil.
Total Assets was $10,752 Mil.
Property, Plant and Equipment(Net PPE) was $3,933 Mil.
Depreciation, Depletion and Amortization(DDA) was $531 Mil.
Selling, General, & Admin. Expense(SGA) was $803 Mil.
Total Current Liabilities was $2,104 Mil.
Long-Term Debt & Capital Lease Obligation was $3,144 Mil.
|
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) |
| = | (987 / 9677) | / | (961 / 9761) |
| = | 0.101994 | / | 0.098453 |
| | = | 1.036 |
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) |
| = | (2616 / 9761) | / | (2683 / 9677) |
| = | 0.268005 | / | 0.277255 |
| | = | 0.9666 |
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 - (3917 + 4063) / 11237) | / | (1 - (3556 + 3933) / 10752) |
| = | 0.289846 | / | 0.303478 |
| | = | 0.9551 |
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 |
| = | 9677 | / | 9761 |
| | = | 0.9914 |
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)) |
| = | (531 / (531 + 3933)) | / | (609 / (609 + 4063)) |
| = | 0.118952 | / | 0.130351 |
| | = | 0.9126 |
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) |
| = | (831 / 9677) | / | (803 / 9761) |
| = | 0.085874 | / | 0.082266 |
| | = | 1.0439 |
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) |
| = | ((2780 + 2324) / 11237) | / | ((3144 + 2104) / 10752) |
| = | 0.454214 | / | 0.488095 |
| | = | 0.9306 |
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 |
| = | (1196 - 44 | - | 1719) | / | 11237 |
| | = | -0.050458 |
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.
Owens-Corning has a M-score of -2.72 suggests that the company is unlikely to be a manipulator.
Quick Browse
Personalize
Premium Gurus 
Create New Portfolio
Portfolio Contest
OC has been successfully added to your