Tellurian Beneish M-Score Historical Data
The historical data trend for Tellurian'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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Tellurian Annual Data
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Trend |
Jun14 |
Jun15 |
Jun16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
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0.60 |
-3.43 |
-2.35 |
1.49 |
-3.64 |
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Tellurian 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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|
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1.49 |
-2.37 |
-3.64 |
-3.75 |
-3.64 |
Competitive Comparison
For the Oil & Gas E&P subindustry, Tellurian'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.
Tellurian Beneish M-Score Distribution
For the Oil & Gas industry and Energy sector, Tellurian's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Tellurian's Beneish M-Score falls into.
Tellurian 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 Tellurian 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 * 0.7929 | + | 0.528 * 1.3518 | + | 0.404 * 1.2364 | + | 0.892 * 0.4239 | + | 0.115 * 0.664 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.9022 | + | 4.679 * -0.116961 | - | 0.327 * 0.9776 |
| = | -3.64 |
* 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 $25.8 Mil.
Revenue was 39.956 + 43.25 + 31.987 + 50.935 = $166.1 Mil.
Gross Profit was 12.588 + 19.589 + 6.777 + 28.748 = $67.7 Mil.
Total Current Assets was $117.5 Mil.
Total Assets was $1,324.0 Mil.
Property, Plant and Equipment(Net PPE) was $1,149.1 Mil.
Depreciation, Depletion and Amortization(DDA) was $98.4 Mil.
Selling, General, & Admin. Expense(SGA) was $101.9 Mil.
Total Current Liabilities was $179.2 Mil.
Long-Term Debt & Capital Lease Obligation was $482.9 Mil.
Net Income was -13.648 + -65.417 + -59.619 + -27.493 = $-166.2 Mil.
Non Operating Income was 15.939 + -27.042 + 1.454 + 9.521 = $-0.1 Mil.
Cash Flow from Operations was -8.481 + -18.788 + 26.24 + -10.16 = $-11.2 Mil.
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Total Receivables was $76.7 Mil.
Revenue was 102.533 + 81.103 + 61.35 + 146.94 = $391.9 Mil.
Gross Profit was 80.911 + 68.243 + 55.496 + 11.257 = $215.9 Mil.
Total Current Assets was $574.3 Mil.
Total Assets was $1,426.7 Mil.
Property, Plant and Equipment(Net PPE) was $802.4 Mil.
Depreciation, Depletion and Amortization(DDA) was $44.4 Mil.
Selling, General, & Admin. Expense(SGA) was $126.4 Mil.
Total Current Liabilities was $297.5 Mil.
Long-Term Debt & Capital Lease Obligation was $432.2 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) |
| = | (25.79 / 166.128) | / | (76.731 / 391.926) |
| = | 0.155242 | / | 0.195779 |
| | = | 0.7929 |
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) |
| = | (215.907 / 391.926) | / | (67.702 / 166.128) |
| = | 0.550887 | / | 0.407529 |
| | = | 1.3518 |
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 - (117.53 + 1149.113) / 1324.028) | / | (1 - (574.291 + 802.379) / 1426.683) |
| = | 0.043341 | / | 0.035055 |
| | = | 1.2364 |
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 |
| = | 166.128 | / | 391.926 |
| | = | 0.4239 |
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)) |
| = | (44.357 / (44.357 + 802.379)) | / | (98.426 / (98.426 + 1149.113)) |
| = | 0.052386 | / | 0.078896 |
| | = | 0.664 |
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) |
| = | (101.902 / 166.128) | / | (126.386 / 391.926) |
| = | 0.613394 | / | 0.322474 |
| | = | 1.9022 |
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) |
| = | ((482.852 + 179.198) / 1324.028) | / | ((432.171 + 297.541) / 1426.683) |
| = | 0.500027 | / | 0.511475 |
| | = | 0.9776 |
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 |
| = | (-166.177 - -0.128 | - | -11.189) | / | 1324.028 |
| | = | -0.116961 |
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.
Tellurian has a M-score of -3.64 suggests that the company is unlikely to be a manipulator.
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