Open Text Beneish M-Score Historical Data
The historical data trend for Open Text'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.
Open Text Beneish M-Score Chart
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Open Text Annual Data
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Trend |
Jun14 |
Jun15 |
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Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-2.85 |
-2.76 |
-2.97 |
-2.77 |
-2.02 |
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Open Text Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
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Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.65 |
-2.02 |
-2.02 |
-1.85 |
-2.12 |
Competitive Comparison of Open Text's Beneish M-Score
For the Software - Application subindustry, Open Text'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.
Open Text's Beneish M-Score Distribution in the Software Industry
For the Software industry and Technology sector, Open Text's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Open Text's Beneish M-Score falls into.
Open Text 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 Open Text 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 * 0.9972 | + | 0.528 * 0.9746 | + | 0.404 * 1.0971 | + | 0.892 * 1.6116 | + | 0.115 * 0.8825 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.028 | + | 4.679 * -0.029997 | - | 0.327 * 1.1579 |
| = | -2.12 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $814 Mil.
Revenue was 1534.868 + 1425.429 + 1490.83 + 1244.674 = $5,696 Mil.
Gross Profit was 1129.12 + 1018.418 + 1064.014 + 874.944 = $4,086 Mil.
Total Current Assets was $4,084 Mil.
Total Assets was $16,443 Mil.
Property, Plant and Equipment(Net PPE) was $598 Mil.
Depreciation, Depletion and Amortization(DDA) was $869 Mil.
Selling, General, & Admin. Expense(SGA) was $1,725 Mil.
Total Current Liabilities was $2,959 Mil.
Long-Term Debt & Capital Lease Obligation was $8,711 Mil.
Net Income was 37.675 + 80.901 + -48.734 + 57.556 = $127 Mil.
Non Operating Income was -130.653 + -0.086 + -104.406 + 5.94 = $-229 Mil.
Cash Flow from Operations was 350.653 + 47.121 + 115.301 + 336.775 = $850 Mil.
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Total Receivables was $507 Mil.
Revenue was 897.44 + 852.036 + 902.454 + 882.283 = $3,534 Mil.
Gross Profit was 635.747 + 593.688 + 633.793 + 608.047 = $2,471 Mil.
Total Current Assets was $3,459 Mil.
Total Assets was $11,218 Mil.
Property, Plant and Equipment(Net PPE) was $445 Mil.
Depreciation, Depletion and Amortization(DDA) was $488 Mil.
Selling, General, & Admin. Expense(SGA) was $1,041 Mil.
Total Current Liabilities was $1,494 Mil.
Long-Term Debt & Capital Lease Obligation was $5,382 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) |
| = | (814.344 / 5695.801) | / | (506.707 / 3534.213) |
| = | 0.142973 | / | 0.143372 |
| | = | 0.9972 |
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) |
| = | (2471.275 / 3534.213) | / | (4086.496 / 5695.801) |
| = | 0.699243 | / | 0.717458 |
| | = | 0.9746 |
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 - (4083.99 + 597.688) / 16443.264) | / | (1 - (3458.806 + 445.121) / 11218.206) |
| = | 0.715283 | / | 0.652001 |
| | = | 1.0971 |
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 |
| = | 5695.801 | / | 3534.213 |
| | = | 1.6116 |
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)) |
| = | (487.886 / (487.886 + 445.121)) | / | (869.166 / (869.166 + 597.688)) |
| = | 0.522918 | / | 0.592537 |
| | = | 0.8825 |
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) |
| = | (1724.709 / 5695.801) | / | (1041.053 / 3534.213) |
| = | 0.302804 | / | 0.294564 |
| | = | 1.028 |
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) |
| = | ((8711.08 + 2959.175) / 16443.264) | / | ((5381.967 + 1494.434) / 11218.206) |
| = | 0.709729 | / | 0.612968 |
| | = | 1.1579 |
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 |
| = | (127.398 - -229.205 | - | 849.85) | / | 16443.264 |
| | = | -0.029997 |
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.
Open Text has a M-score of -2.12 suggests that the company is unlikely to be a manipulator.
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