House of Investments Beneish M-Score Historical Data
The historical data trend for House of Investments'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.
House of Investments Beneish M-Score Chart
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House of Investments Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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-2.18 |
-2.36 |
-5.33 |
-2.85 |
-2.14 |
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House of Investments Quarterly Data
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Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-2.81 |
-2.14 |
-1.93 |
-2.40 |
-1.99 |
Competitive Comparison of House of Investments's Beneish M-Score
For the Engineering & Construction subindustry, House of Investments'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.
House of Investments's Beneish M-Score Distribution in the Construction Industry
For the Construction industry and Industrials sector, House of Investments's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where House of Investments's Beneish M-Score falls into.
House of Investments 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 House of Investments 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 * 0.0931 | + | 0.528 * 1.1334 | + | 0.404 * 1.2024 | + | 0.892 * 1.8542 | + | 0.115 * 0.8929 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.807 | + | 4.679 * 0.054962 | - | 0.327 * 0.6088 |
| = | -1.99 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was ₱2,375 Mil.
Revenue was 2607.885 + 2420.628 + 6707.583 + 17336.267 = ₱29,072 Mil.
Gross Profit was 754.661 + 558.809 + 1150.317 + 2767.802 = ₱5,232 Mil.
Total Current Assets was ₱6,232 Mil.
Total Assets was ₱38,122 Mil.
Property, Plant and Equipment(Net PPE) was ₱15,956 Mil.
Depreciation, Depletion and Amortization(DDA) was ₱1,219 Mil.
Selling, General, & Admin. Expense(SGA) was ₱1,675 Mil.
Total Current Liabilities was ₱6,850 Mil.
Long-Term Debt & Capital Lease Obligation was ₱3,302 Mil.
Net Income was 294.645 + -327.624 + -8.018 + 302.538 = ₱262 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₱0 Mil.
Cash Flow from Operations was -462.533 + 2253.452 + -1398.008 + -2226.609 = ₱-1,834 Mil.
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Total Receivables was ₱13,756 Mil.
Revenue was 2199.648 + 2246.906 + 5281.326 + 5951.001 = ₱15,679 Mil.
Gross Profit was 644.048 + 559.667 + 1014.731 + 979.491 = ₱3,198 Mil.
Total Current Assets was ₱25,011 Mil.
Total Assets was ₱64,652 Mil.
Property, Plant and Equipment(Net PPE) was ₱17,168 Mil.
Depreciation, Depletion and Amortization(DDA) was ₱1,162 Mil.
Selling, General, & Admin. Expense(SGA) was ₱1,119 Mil.
Total Current Liabilities was ₱20,719 Mil.
Long-Term Debt & Capital Lease Obligation was ₱7,563 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) |
| = | (2375.105 / 29072.363) | / | (13756.49 / 15678.881) |
| = | 0.081696 | / | 0.87739 |
| | = | 0.0931 |
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) |
| = | (3197.937 / 15678.881) | / | (5231.589 / 29072.363) |
| = | 0.203965 | / | 0.179951 |
| | = | 1.1334 |
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 - (6232.478 + 15955.994) / 38121.778) | / | (1 - (25011.183 + 17168.338) / 64652.3) |
| = | 0.417958 | / | 0.347594 |
| | = | 1.2024 |
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 |
| = | 29072.363 | / | 15678.881 |
| | = | 1.8542 |
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)) |
| = | (1161.821 / (1161.821 + 17168.338)) | / | (1219.233 / (1219.233 + 15955.994)) |
| = | 0.063383 | / | 0.070988 |
| | = | 0.8929 |
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) |
| = | (1674.622 / 29072.363) | / | (1119.138 / 15678.881) |
| = | 0.057602 | / | 0.071379 |
| | = | 0.807 |
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) |
| = | ((3301.957 + 6850.464) / 38121.778) | / | ((7562.573 + 20719.215) / 64652.3) |
| = | 0.266316 | / | 0.437444 |
| | = | 0.6088 |
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 |
| = | (261.541 - 0 | - | -1833.698) | / | 38121.778 |
| | = | 0.054962 |
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.
House of Investments has a M-score of -1.99 suggests that the company is unlikely to be a manipulator.
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