Reginn hf Beneish M-Score Historical Data
The historical data trend for Reginn hf'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.
Reginn hf Beneish M-Score Chart
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Reginn hf Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.86 |
-1.82 |
-2.57 |
-2.69 |
-2.37 |
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Reginn hf Quarterly Data
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Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
| Beneish M-Score |
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-3.37 |
-2.74 |
-2.83 |
-2.37 |
-1.64 |
Competitive Comparison of Reginn hf's Beneish M-Score
For the Real Estate Services subindustry, Reginn hf'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.
Reginn hf's Beneish M-Score Distribution in the Real Estate Industry
For the Real Estate industry and Real Estate sector, Reginn hf's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Reginn hf's Beneish M-Score falls into.
Reginn hf 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 Reginn hf 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 * 1.7174 | + | 0.528 * 0.9926 | + | 0.404 * 0.9904 | + | 0.892 * 1.1118 | + | 0.115 * 0.7955 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.5417 | + | 4.679 * 0.005429 | - | 0.327 * 0.9827 |
| = | -1.64 |
* 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 (Mar24) TTM: | Last Year (Mar23) TTM: |
Total Receivables was kr1,012 Mil.
Revenue was 3532 + 3632 + 3463 + 3432 = kr14,059 Mil.
Gross Profit was 2571 + 4419 + 2611 + 2475 = kr12,076 Mil.
Total Current Assets was kr3,861 Mil.
Total Assets was kr198,560 Mil.
Property, Plant and Equipment(Net PPE) was kr724 Mil.
Depreciation, Depletion and Amortization(DDA) was kr39 Mil.
Selling, General, & Admin. Expense(SGA) was kr156 Mil.
Total Current Liabilities was kr5,838 Mil.
Long-Term Debt & Capital Lease Obligation was kr116,260 Mil.
Net Income was 3919 + -1257 + -1005 + 4925 = kr6,582 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = kr0 Mil.
Cash Flow from Operations was 1408 + 1694 + 1204 + 1198 = kr5,504 Mil.
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Total Receivables was kr530 Mil.
Revenue was 3250 + 3329 + 3108 + 2958 = kr12,645 Mil.
Gross Profit was 2371 + 3913 + 2333 + 2164 = kr10,781 Mil.
Total Current Assets was kr1,762 Mil.
Total Assets was kr184,895 Mil.
Property, Plant and Equipment(Net PPE) was kr755 Mil.
Depreciation, Depletion and Amortization(DDA) was kr32 Mil.
Selling, General, & Admin. Expense(SGA) was kr259 Mil.
Total Current Liabilities was kr9,421 Mil.
Long-Term Debt & Capital Lease Obligation was kr106,276 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) |
| = | (1012 / 14059) | / | (530 / 12645) |
| = | 0.071982 | / | 0.041914 |
| | = | 1.7174 |
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) |
| = | (10781 / 12645) | / | (12076 / 14059) |
| = | 0.85259 | / | 0.858952 |
| | = | 0.9926 |
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 - (3861 + 724) / 198560) | / | (1 - (1762 + 755) / 184895) |
| = | 0.976909 | / | 0.986387 |
| | = | 0.9904 |
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 |
| = | 14059 | / | 12645 |
| | = | 1.1118 |
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)) |
| = | (32 / (32 + 755)) | / | (39 / (39 + 724)) |
| = | 0.040661 | / | 0.051114 |
| | = | 0.7955 |
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 / 14059) | / | (259 / 12645) |
| = | 0.011096 | / | 0.020482 |
| | = | 0.5417 |
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) |
| = | ((116260 + 5838) / 198560) | / | ((106276 + 9421) / 184895) |
| = | 0.614917 | / | 0.625744 |
| | = | 0.9827 |
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 |
| = | (6582 - 0 | - | 5504) | / | 198560 |
| | = | 0.005429 |
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.
Reginn hf has a M-score of -1.64 signals that the company is likely to be a manipulator.
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