Kinder Morgan Beneish M-Score Historical Data
The historical data trend for Kinder Morgan'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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Kinder Morgan Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.81 |
-2.81 |
-2.26 |
-2.44 |
-3.08 |
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Kinder Morgan 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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-2.44 |
-2.77 |
-3.13 |
-3.08 |
-3.08 |
Competitive Comparison
For the Oil & Gas Midstream subindustry, Kinder Morgan'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.
Kinder Morgan Beneish M-Score Distribution
For the Oil & Gas industry and Energy sector, Kinder Morgan's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Kinder Morgan's Beneish M-Score falls into.
Kinder Morgan 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 Kinder Morgan 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 * 1.0806 | + | 0.528 * 0.7607 | + | 0.404 * 1.003 | + | 0.892 * 0.7986 | + | 0.115 * 1.0169 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.313 | + | 4.679 * -0.068262 | - | 0.327 * 0.9855 |
| = | -3.08 |
* 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 $1,588 Mil.
Revenue was 4038 + 3907 + 3501 + 3888 = $15,334 Mil.
Gross Profit was 2124 + 1941 + 1973 + 2108 = $8,146 Mil.
Total Current Assets was $2,542 Mil.
Total Assets was $71,020 Mil.
Property, Plant and Equipment(Net PPE) was $37,297 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,250 Mil.
Selling, General, & Admin. Expense(SGA) was $668 Mil.
Total Current Liabilities was $7,221 Mil.
Long-Term Debt & Capital Lease Obligation was $28,067 Mil.
Net Income was 594 + 532 + 586 + 679 = $2,391 Mil.
Non Operating Income was 172 + 222 + 204 + 150 = $748 Mil.
Cash Flow from Operations was 2322 + 1286 + 1550 + 1333 = $6,491 Mil.
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Total Receivables was $1,840 Mil.
Revenue was 4579 + 5177 + 5151 + 4293 = $19,200 Mil.
Gross Profit was 2064 + 1909 + 1925 + 1861 = $7,759 Mil.
Total Current Assets was $3,803 Mil.
Total Assets was $70,078 Mil.
Property, Plant and Equipment(Net PPE) was $35,599 Mil.
Depreciation, Depletion and Amortization(DDA) was $2,186 Mil.
Selling, General, & Admin. Expense(SGA) was $637 Mil.
Total Current Liabilities was $6,930 Mil.
Long-Term Debt & Capital Lease Obligation was $28,403 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) |
| = | (1588 / 15334) | / | (1840 / 19200) |
| = | 0.103561 | / | 0.095833 |
| | = | 1.0806 |
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) |
| = | (7759 / 19200) | / | (8146 / 15334) |
| = | 0.404115 | / | 0.531238 |
| | = | 0.7607 |
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 - (2542 + 37297) / 71020) | / | (1 - (3803 + 35599) / 70078) |
| = | 0.439045 | / | 0.437741 |
| | = | 1.003 |
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 |
| = | 15334 | / | 19200 |
| | = | 0.7986 |
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)) |
| = | (2186 / (2186 + 35599)) | / | (2250 / (2250 + 37297)) |
| = | 0.057854 | / | 0.056894 |
| | = | 1.0169 |
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) |
| = | (668 / 15334) | / | (637 / 19200) |
| = | 0.043563 | / | 0.033177 |
| | = | 1.313 |
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) |
| = | ((28067 + 7221) / 71020) | / | ((28403 + 6930) / 70078) |
| = | 0.496874 | / | 0.504195 |
| | = | 0.9855 |
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 |
| = | (2391 - 748 | - | 6491) | / | 71020 |
| | = | -0.068262 |
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.
Kinder Morgan has a M-score of -3.08 suggests that the company is unlikely to be a manipulator.
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