Xi S&D Beneish M-Score Historical Data
The historical data trend for Xi S&D'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.
Xi S&D Beneish M-Score Chart
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Xi S&D Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
-2.02 |
-3.15 |
5.03 |
-3.47 |
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Xi S&D 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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0.75 |
-1.89 |
-2.52 |
-3.47 |
-2.72 |
Competitive Comparison of Xi S&D's Beneish M-Score
For the Real Estate - Diversified subindustry, Xi S&D'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.
Xi S&D's Beneish M-Score Distribution in the Real Estate Industry
For the Real Estate industry and Real Estate sector, Xi S&D's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Xi S&D's Beneish M-Score falls into.
Xi S&D 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 Xi S&D 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 * 0.8517 | + | 0.528 * 1.7107 | + | 0.404 * 1.2813 | + | 0.892 * 0.6676 | + | 0.115 * 1.9169 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4047 | + | 4.679 * -0.088103 | - | 0.327 * 0.7522 |
| = | -2.72 |
* 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 ₩526,532 Mil.
Revenue was 400474.917 + 479750.29 + 512666.032 + 615091.63 = ₩2,007,983 Mil.
Gross Profit was 21521.839 + 21625.978 + 40520.636 + 57278.84 = ₩140,947 Mil.
Total Current Assets was ₩1,055,343 Mil.
Total Assets was ₩1,505,060 Mil.
Property, Plant and Equipment(Net PPE) was ₩48,603 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩16,612 Mil.
Selling, General, & Admin. Expense(SGA) was ₩18,512 Mil.
Total Current Liabilities was ₩508,528 Mil.
Long-Term Debt & Capital Lease Obligation was ₩132,091 Mil.
Net Income was 569.386 + 4937.21 + 9499.915 + 11248.583 = ₩26,255 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -9435.224 + 150952.066 + -22375.655 + 39713.93 = ₩158,855 Mil.
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Total Receivables was ₩925,941 Mil.
Revenue was 767124.743 + 888151.864 + 641004.663 + 711323.057 = ₩3,007,604 Mil.
Gross Profit was 88471.08 + 98989.858 + 61844.063 + 111843.193 = ₩361,148 Mil.
Total Current Assets was ₩1,481,707 Mil.
Total Assets was ₩1,928,440 Mil.
Property, Plant and Equipment(Net PPE) was ₩45,618 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩43,529 Mil.
Selling, General, & Admin. Expense(SGA) was ₩19,739 Mil.
Total Current Liabilities was ₩961,868 Mil.
Long-Term Debt & Capital Lease Obligation was ₩129,436 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) |
| = | (526532.378 / 2007982.869) | / | (925940.942 / 3007604.327) |
| = | 0.26222 | / | 0.307867 |
| | = | 0.8517 |
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) |
| = | (361148.194 / 3007604.327) | / | (140947.293 / 2007982.869) |
| = | 0.120078 | / | 0.070193 |
| | = | 1.7107 |
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 - (1055342.555 + 48602.899) / 1505060.224) | / | (1 - (1481706.748 + 45617.511) / 1928440.033) |
| = | 0.266511 | / | 0.208 |
| | = | 1.2813 |
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 |
| = | 2007982.869 | / | 3007604.327 |
| | = | 0.6676 |
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)) |
| = | (43528.891 / (43528.891 + 45617.511)) | / | (16611.675 / (16611.675 + 48602.899)) |
| = | 0.488285 | / | 0.254723 |
| | = | 1.9169 |
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) |
| = | (18511.743 / 2007982.869) | / | (19738.588 / 3007604.327) |
| = | 0.009219 | / | 0.006563 |
| | = | 1.4047 |
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) |
| = | ((132091.349 + 508527.851) / 1505060.224) | / | ((129436.172 + 961868.039) / 1928440.033) |
| = | 0.425644 | / | 0.5659 |
| | = | 0.7522 |
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 |
| = | (26255.094 - 0 | - | 158855.117) | / | 1505060.224 |
| | = | -0.088103 |
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.
Xi S&D has a M-score of -2.72 suggests that the company is unlikely to be a manipulator.
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