BXP Beneish M-Score Historical Data
The historical data trend for BXP'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.
BXP Beneish M-Score Chart
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BXP Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.56 |
-2.63 |
-2.57 |
-2.58 |
-2.60 |
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BXP Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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-2.58 |
-2.60 |
-2.56 |
-2.55 |
-2.58 |
Competitive Comparison of BXP's Beneish M-Score
For the REIT - Office subindustry, BXP'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.
BXP's Beneish M-Score Distribution in the REITs Industry
For the REITs industry and Real Estate sector, BXP's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where BXP's Beneish M-Score falls into.
BXP 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 BXP 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 * 0.9916 | + | 0.528 * 1.0238 | + | 0.404 * 0.9806 | + | 0.892 * 1.0246 | + | 0.115 * 1 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9436 | + | 4.679 * -0.034542 | - | 0.327 * 1.0171 |
| = | -2.62 |
* 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 (Sep24) TTM: | Last Year (Sep23) TTM: |
Total Receivables was €1,482 Mil.
Revenue was 774.164 + 790.098 + 772.284 + 760.132 = €3,097 Mil.
Gross Profit was 469.869 + 482.353 + 477.726 + 476.06 = €1,906 Mil.
Total Current Assets was €2,808 Mil.
Total Assets was €23,791 Mil.
Property, Plant and Equipment(Net PPE) was €0 Mil.
Depreciation, Depletion and Amortization(DDA) was €798 Mil.
Selling, General, & Admin. Expense(SGA) was €167 Mil.
Total Current Liabilities was €1,115 Mil.
Long-Term Debt & Capital Lease Obligation was €14,847 Mil.
Net Income was 75.349 + 73.962 + 73.492 + 109.971 = €333 Mil.
Non Operating Income was -3.955 + -5.216 + 7.108 + 21.073 = €19 Mil.
Cash Flow from Operations was 257.772 + 341.002 + 181.787 + 355.015 = €1,136 Mil.
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Total Receivables was €1,459 Mil.
Revenue was 772.353 + 754.232 + 750.189 + 745.594 = €3,022 Mil.
Gross Profit was 482.622 + 478.073 + 471.876 + 471.918 = €1,904 Mil.
Total Current Assets was €2,331 Mil.
Total Assets was €23,181 Mil.
Property, Plant and Equipment(Net PPE) was €0 Mil.
Depreciation, Depletion and Amortization(DDA) was €765 Mil.
Selling, General, & Admin. Expense(SGA) was €173 Mil.
Total Current Liabilities was €715 Mil.
Long-Term Debt & Capital Lease Obligation was €14,576 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) |
| = | (1482.462 / 3096.678) | / | (1459.111 / 3022.368) |
| = | 0.478727 | / | 0.482771 |
| | = | 0.9916 |
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) |
| = | (1904.489 / 3022.368) | / | (1906.008 / 3096.678) |
| = | 0.630131 | / | 0.615501 |
| | = | 1.0238 |
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 - (2808.269 + 0) / 23791.388) | / | (1 - (2330.885 + 0) / 23180.582) |
| = | 0.881963 | / | 0.899447 |
| | = | 0.9806 |
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 |
| = | 3096.678 | / | 3022.368 |
| | = | 1.0246 |
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)) |
| = | (765.479 / (765.479 + 0)) | / | (797.864 / (797.864 + 0)) |
| = | 1 | / | 1 |
| | = | 1 |
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) |
| = | (167.375 / 3096.678) | / | (173.12 / 3022.368) |
| = | 0.05405 | / | 0.05728 |
| | = | 0.9436 |
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) |
| = | ((14846.633 + 1115.293) / 23791.388) | / | ((14576.152 + 714.536) / 23180.582) |
| = | 0.670912 | / | 0.659633 |
| | = | 1.0171 |
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 |
| = | (332.774 - 19.01 | - | 1135.576) | / | 23791.388 |
| | = | -0.034542 |
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.
BXP has a M-score of -2.62 suggests that the company is unlikely to be a manipulator.
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