NetEase Beneish M-Score Historical Data
The historical data trend for NetEase'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.
NetEase Beneish M-Score Chart
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NetEase Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.28 |
-2.47 |
-2.66 |
-2.94 |
-2.32 |
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NetEase 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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-2.43 |
-2.32 |
-2.57 |
-2.58 |
-2.79 |
Competitive Comparison of NetEase's Beneish M-Score
For the Electronic Gaming & Multimedia subindustry, NetEase'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.
NetEase's Beneish M-Score Distribution in the Interactive Media Industry
For the Interactive Media industry and Communication Services sector, NetEase's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where NetEase's Beneish M-Score falls into.
NetEase 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 NetEase 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 * 0.9365 | + | 0.528 * 0.9306 | + | 0.404 * 0.9201 | + | 0.892 * 1.0069 | + | 0.115 * 1.3344 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0738 | + | 4.679 * -0.056933 | - | 0.327 * 0.9666 |
| = | -2.83 |
* 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 €786 Mil.
Revenue was 3337.352 + 3263.583 + 3430.341 + 3485.551 = €13,517 Mil.
Gross Profit was 2097.996 + 2054.285 + 2173.804 + 2160.815 = €8,487 Mil.
Total Current Assets was €17,900 Mil.
Total Assets was €23,543 Mil.
Property, Plant and Equipment(Net PPE) was €1,044 Mil.
Depreciation, Depletion and Amortization(DDA) was €304 Mil.
Selling, General, & Admin. Expense(SGA) was €2,583 Mil.
Total Current Liabilities was €5,821 Mil.
Long-Term Debt & Capital Lease Obligation was €54 Mil.
Net Income was 832.551 + 865.491 + 975.245 + 845.345 = €3,519 Mil.
Non Operating Income was -55.201 + -6.404 + 49.592 + -49.456 = €-61 Mil.
Cash Flow from Operations was 1346.612 + 836.433 + 1220.939 + 1516.511 = €4,920 Mil.
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Total Receivables was €834 Mil.
Revenue was 3501.332 + 3094.706 + 3394.801 + 3433.065 = €13,424 Mil.
Gross Profit was 2178.356 + 1852.781 + 2019.094 + 1793.347 = €7,844 Mil.
Total Current Assets was €16,379 Mil.
Total Assets was €22,029 Mil.
Property, Plant and Equipment(Net PPE) was €974 Mil.
Depreciation, Depletion and Amortization(DDA) was €420 Mil.
Selling, General, & Admin. Expense(SGA) was €2,389 Mil.
Total Current Liabilities was €5,632 Mil.
Long-Term Debt & Capital Lease Obligation was €55 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) |
| = | (786.029 / 13516.827) | / | (833.553 / 13423.904) |
| = | 0.058152 | / | 0.062095 |
| | = | 0.9365 |
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) |
| = | (7843.578 / 13423.904) | / | (8486.9 / 13516.827) |
| = | 0.584299 | / | 0.627877 |
| | = | 0.9306 |
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 - (17900.138 + 1044.18) / 23543.18) | / | (1 - (16378.521 + 973.518) / 22029.047) |
| = | 0.195337 | / | 0.212311 |
| | = | 0.9201 |
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 |
| = | 13516.827 | / | 13423.904 |
| | = | 1.0069 |
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)) |
| = | (419.771 / (419.771 + 973.518)) | / | (304.496 / (304.496 + 1044.18)) |
| = | 0.301281 | / | 0.225774 |
| | = | 1.3344 |
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) |
| = | (2582.938 / 13516.827) | / | (2388.888 / 13423.904) |
| = | 0.191091 | / | 0.177958 |
| | = | 1.0738 |
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) |
| = | ((54.498 + 5820.593) / 23543.18) | / | ((54.952 + 5632.441) / 22029.047) |
| = | 0.249545 | / | 0.258177 |
| | = | 0.9666 |
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 |
| = | (3518.632 - -61.469 | - | 4920.495) | / | 23543.18 |
| | = | -0.056933 |
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.
NetEase has a M-score of -2.83 suggests that the company is unlikely to be a manipulator.
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