Exela Technologies Beneish M-Score Historical Data
The historical data trend for Exela Technologies'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.
Exela Technologies Beneish M-Score Chart
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Exela Technologies Annual Data
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Trend |
Dec14 |
Dec15 |
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Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.91 |
-3.43 |
-2.81 |
-3.82 |
-3.87 |
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Exela Technologies Quarterly Data
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Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
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Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
| Beneish M-Score |
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-2.76 |
-3.62 |
-3.87 |
-3.91 |
-4.12 |
Competitive Comparison of Exela Technologies's Beneish M-Score
For the Software - Application subindustry, Exela Technologies'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.
Exela Technologies's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Exela Technologies's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Exela Technologies's Beneish M-Score falls into.
Exela Technologies 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 Exela Technologies 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 * 0.6057 | + | 0.528 * 0.8865 | + | 0.404 * 1.0292 | + | 0.892 * 0.9485 | + | 0.115 * 1.0258 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0358 | + | 4.679 * -0.241812 | - | 0.327 * 1.1536 |
| = | -4.12 |
* 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 (Jun24) TTM: | Last Year (Jun23) TTM: |
Total Receivables was $62 Mil.
Revenue was 245.653 + 258.811 + 264.441 + 253.125 = $1,022 Mil.
Gross Profit was 57.689 + 56.823 + 57.995 + 54.675 = $227 Mil.
Total Current Assets was $157 Mil.
Total Assets was $588 Mil.
Property, Plant and Equipment(Net PPE) was $90 Mil.
Depreciation, Depletion and Amortization(DDA) was $58 Mil.
Selling, General, & Admin. Expense(SGA) was $157 Mil.
Total Current Liabilities was $411 Mil.
Long-Term Debt & Capital Lease Obligation was $1,048 Mil.
Net Income was -25.677 + -24.879 + -25.726 + -23.108 = $-99 Mil.
Non Operating Income was 0.627 + -1.43 + 0.874 + 1.342 = $1 Mil.
Cash Flow from Operations was 12.154 + -29.08 + 32.776 + 25.521 = $41 Mil.
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Total Receivables was $108 Mil.
Revenue was 272.938 + 273.62 + 266.951 + 264.038 = $1,078 Mil.
Gross Profit was 60.879 + 57.153 + 48.1 + 46.196 = $212 Mil.
Total Current Assets was $194 Mil.
Total Assets was $675 Mil.
Property, Plant and Equipment(Net PPE) was $100 Mil.
Depreciation, Depletion and Amortization(DDA) was $67 Mil.
Selling, General, & Admin. Expense(SGA) was $160 Mil.
Total Current Liabilities was $456 Mil.
Long-Term Debt & Capital Lease Obligation was $997 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) |
| = | (61.95 / 1022.03) | / | (107.833 / 1077.547) |
| = | 0.060615 | / | 0.100073 |
| | = | 0.6057 |
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) |
| = | (212.328 / 1077.547) | / | (227.182 / 1022.03) |
| = | 0.197048 | / | 0.222285 |
| | = | 0.8865 |
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 - (156.601 + 89.869) / 587.953) | / | (1 - (193.861 + 100.372) / 675.343) |
| = | 0.5808 | / | 0.564321 |
| | = | 1.0292 |
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 |
| = | 1022.03 | / | 1077.547 |
| | = | 0.9485 |
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)) |
| = | (67.076 / (67.076 + 100.372)) | / | (57.575 / (57.575 + 89.869)) |
| = | 0.400578 | / | 0.390487 |
| | = | 1.0258 |
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) |
| = | (156.897 / 1022.03) | / | (159.696 / 1077.547) |
| = | 0.153515 | / | 0.148203 |
| | = | 1.0358 |
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) |
| = | ((1048.131 + 411.029) / 587.953) | / | ((996.704 + 456.192) / 675.343) |
| = | 2.481763 | / | 2.151345 |
| | = | 1.1536 |
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 |
| = | (-99.39 - 1.413 | - | 41.371) | / | 587.953 |
| | = | -0.241812 |
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.
Exela Technologies has a M-score of -4.12 suggests that the company is unlikely to be a manipulator.
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