Litoral Transmision Beneish M-Score Historical Data
The historical data trend for Litoral Transmision'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.
Litoral Transmision Beneish M-Score Chart
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Litoral Transmision Annual Data
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Trend |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-2.27 |
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Litoral Transmision Quarterly Data
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Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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- |
- |
- |
-2.27 |
-2.15 |
Competitive Comparison of Litoral Transmision's Beneish M-Score
For the Utilities - Independent Power Producers subindustry, Litoral Transmision'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.
Litoral Transmision's Beneish M-Score Distribution in the Utilities - Independent Power Producers Industry
For the Utilities - Independent Power Producers industry and Utilities sector, Litoral Transmision's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Litoral Transmision's Beneish M-Score falls into.
Litoral Transmision 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 Litoral Transmision 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 * 1.41 | + | 0.528 * 1.078 | + | 0.404 * 0.6945 | + | 0.892 * 0.7472 | + | 0.115 * 1.7747 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.8646 | + | 4.679 * 0.067647 | - | 0.327 * 0.9894 |
| = | -2.15 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was CLP1,488 Mil.
Revenue was 314.607 + 284.928 + 240.623 + 248.031 = CLP1,088 Mil.
Gross Profit was 246.405 + 199.094 + 166.292 + 179.789 = CLP792 Mil.
Total Current Assets was CLP1,531 Mil.
Total Assets was CLP4,527 Mil.
Property, Plant and Equipment(Net PPE) was CLP2,853 Mil.
Depreciation, Depletion and Amortization(DDA) was CLP22 Mil.
Selling, General, & Admin. Expense(SGA) was CLP112 Mil.
Total Current Liabilities was CLP2,483 Mil.
Long-Term Debt & Capital Lease Obligation was CLP0 Mil.
Net Income was 151.321 + 123.094 + 87.25 + 101.694 = CLP463 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = CLP0 Mil.
Cash Flow from Operations was -253.874 + 588.569 + -86.083 + -91.462 = CLP157 Mil.
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Total Receivables was CLP1,412 Mil.
Revenue was 255.329 + 888.198 + 160.868 + 151.927 = CLP1,456 Mil.
Gross Profit was 186.071 + 812.65 + 84.564 + 58.723 = CLP1,142 Mil.
Total Current Assets was CLP1,817 Mil.
Total Assets was CLP4,005 Mil.
Property, Plant and Equipment(Net PPE) was CLP2,007 Mil.
Depreciation, Depletion and Amortization(DDA) was CLP28 Mil.
Selling, General, & Admin. Expense(SGA) was CLP80 Mil.
Total Current Liabilities was CLP2,221 Mil.
Long-Term Debt & Capital Lease Obligation was CLP0 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) |
| = | (1487.74 / 1088.189) | / | (1412.106 / 1456.322) |
| = | 1.367171 | / | 0.969639 |
| | = | 1.41 |
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) |
| = | (1142.008 / 1456.322) | / | (791.58 / 1088.189) |
| = | 0.784173 | / | 0.727429 |
| | = | 1.078 |
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 - (1531.374 + 2852.522) / 4526.586) | / | (1 - (1816.885 + 2006.538) / 4005.225) |
| = | 0.031523 | / | 0.045391 |
| | = | 0.6945 |
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 |
| = | 1088.189 | / | 1456.322 |
| | = | 0.7472 |
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)) |
| = | (27.586 / (27.586 + 2006.538)) | / | (21.967 / (21.967 + 2852.522)) |
| = | 0.013562 | / | 0.007642 |
| | = | 1.7747 |
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) |
| = | (111.662 / 1088.189) | / | (80.146 / 1456.322) |
| = | 0.102613 | / | 0.055033 |
| | = | 1.8646 |
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) |
| = | ((0 + 2482.92) / 4526.586) | / | ((0 + 2220.585) / 4005.225) |
| = | 0.548519 | / | 0.554422 |
| | = | 0.9894 |
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 |
| = | (463.359 - 0 | - | 157.15) | / | 4526.586 |
| | = | 0.067647 |
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.
Litoral Transmision has a M-score of -2.15 suggests that the company is unlikely to be a manipulator.
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