Alrov Properties & Lodgings Beneish M-Score Historical Data
The historical data trend for Alrov Properties & Lodgings'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.
Alrov Properties & Lodgings Beneish M-Score Chart
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Alrov Properties & Lodgings Annual Data
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Trend |
Dec08 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.73 |
-1.80 |
-2.69 |
-2.11 |
-1.36 |
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Alrov Properties & Lodgings 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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-2.11 |
-2.21 |
-2.01 |
-2.21 |
-1.36 |
Competitive Comparison of Alrov Properties & Lodgings's Beneish M-Score
For the Real Estate - Diversified subindustry, Alrov Properties & Lodgings'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.
Alrov Properties & Lodgings's Beneish M-Score Distribution in the Real Estate Industry
For the Real Estate industry and Real Estate sector, Alrov Properties & Lodgings's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Alrov Properties & Lodgings's Beneish M-Score falls into.
Alrov Properties & Lodgings 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 Alrov Properties & Lodgings 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 * 2.1867 | + | 0.528 * 1.0435 | + | 0.404 * 1.0204 | + | 0.892 * 1.1358 | + | 0.115 * 0.9452 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9571 | + | 4.679 * -0.021599 | - | 0.327 * 1.0754 |
| = | -1.36 |
* 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 ₪168 Mil.
Revenue was 288.385 + 337.778 + 379.434 + 279.808 = ₪1,285 Mil.
Gross Profit was 298.073 + 125.491 + 165.065 + 93.342 = ₪682 Mil.
Total Current Assets was ₪1,139 Mil.
Total Assets was ₪17,636 Mil.
Property, Plant and Equipment(Net PPE) was ₪5,478 Mil.
Depreciation, Depletion and Amortization(DDA) was ₪131 Mil.
Selling, General, & Admin. Expense(SGA) was ₪134 Mil.
Total Current Liabilities was ₪2,140 Mil.
Long-Term Debt & Capital Lease Obligation was ₪6,699 Mil.
Net Income was -136.574 + 4.011 + 28.658 + -105.222 = ₪-209 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₪0 Mil.
Cash Flow from Operations was -6.695 + 59.66 + 72.581 + 46.261 = ₪172 Mil.
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Total Receivables was ₪68 Mil.
Revenue was 330.253 + 302.196 + 298.579 + 200.653 = ₪1,132 Mil.
Gross Profit was 315.148 + 124.748 + 124.14 + 62.525 = ₪627 Mil.
Total Current Assets was ₪1,060 Mil.
Total Assets was ₪16,588 Mil.
Property, Plant and Equipment(Net PPE) was ₪5,371 Mil.
Depreciation, Depletion and Amortization(DDA) was ₪121 Mil.
Selling, General, & Admin. Expense(SGA) was ₪124 Mil.
Total Current Liabilities was ₪1,361 Mil.
Long-Term Debt & Capital Lease Obligation was ₪6,370 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) |
| = | (168.372 / 1285.405) | / | (67.79 / 1131.681) |
| = | 0.130988 | / | 0.059902 |
| | = | 2.1867 |
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) |
| = | (626.561 / 1131.681) | / | (681.971 / 1285.405) |
| = | 0.553655 | / | 0.53055 |
| | = | 1.0435 |
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 - (1139.433 + 5477.604) / 17636.319) | / | (1 - (1059.719 + 5371.046) / 16588.286) |
| = | 0.624806 | / | 0.612331 |
| | = | 1.0204 |
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 |
| = | 1285.405 | / | 1131.681 |
| | = | 1.1358 |
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)) |
| = | (121.464 / (121.464 + 5371.046)) | / | (131.222 / (131.222 + 5477.604)) |
| = | 0.022114 | / | 0.023396 |
| | = | 0.9452 |
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) |
| = | (134.462 / 1285.405) | / | (123.693 / 1131.681) |
| = | 0.104607 | / | 0.1093 |
| | = | 0.9571 |
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) |
| = | ((6699.441 + 2139.667) / 17636.319) | / | ((6369.884 + 1361.043) / 16588.286) |
| = | 0.501188 | / | 0.466047 |
| | = | 1.0754 |
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 |
| = | (-209.127 - 0 | - | 171.807) | / | 17636.319 |
| | = | -0.021599 |
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.
Alrov Properties & Lodgings has a M-score of -1.36 signals that the company is likely to be a manipulator.
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