HYBE Beneish M-Score Historical Data
The historical data trend for HYBE'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.
HYBE Beneish M-Score Chart
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HYBE Annual Data
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Trend |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
-1.29 |
-2.33 |
-2.47 |
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HYBE Quarterly Data
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Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.33 |
-2.38 |
-2.56 |
-2.11 |
-2.47 |
Competitive Comparison of HYBE's Beneish M-Score
For the Entertainment subindustry, HYBE'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.
HYBE's Beneish M-Score Distribution in the Media - Diversified Industry
For the Media - Diversified industry and Communication Services sector, HYBE's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where HYBE's Beneish M-Score falls into.
HYBE 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 HYBE 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 * 0.8194 | + | 0.528 * 1.0241 | + | 0.404 * 1.1661 | + | 0.892 * 1.2263 | + | 0.115 * 0.9783 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.829 | + | 4.679 * -0.023079 | - | 0.327 * 1.0774 |
| = | -2.47 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was ₩283,071 Mil.
Revenue was 608603.97 + 537859.338 + 620990.222 + 410634.676 = ₩2,178,088 Mil.
Gross Profit was 284969.277 + 246828.141 + 268408.728 + 208802.862 = ₩1,009,009 Mil.
Total Current Assets was ₩1,888,752 Mil.
Total Assets was ₩5,345,681 Mil.
Property, Plant and Equipment(Net PPE) was ₩294,890 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩127,352 Mil.
Selling, General, & Admin. Expense(SGA) was ₩232,774 Mil.
Total Current Liabilities was ₩1,772,169 Mil.
Long-Term Debt & Capital Lease Obligation was ₩248,988 Mil.
Net Income was -57064.129 + 102684.91 + 117339.001 + 24293.434 = ₩187,253 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 263022.818 + 25692.422 + -38836.778 + 60748.734 = ₩310,627 Mil.
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Total Receivables was ₩281,712 Mil.
Revenue was 533462.979 + 445499.466 + 512217.587 + 284973.925 = ₩1,776,154 Mil.
Gross Profit was 246611.516 + 210665.729 + 230247.11 + 155115.026 = ₩842,639 Mil.
Total Current Assets was ₩2,115,847 Mil.
Total Assets was ₩4,870,434 Mil.
Property, Plant and Equipment(Net PPE) was ₩284,002 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩118,877 Mil.
Selling, General, & Admin. Expense(SGA) was ₩228,982 Mil.
Total Current Liabilities was ₩849,485 Mil.
Long-Term Debt & Capital Lease Obligation was ₩859,690 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) |
| = | (283071.156 / 2178088.206) | / | (281711.828 / 1776153.957) |
| = | 0.129963 | / | 0.158608 |
| | = | 0.8194 |
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) |
| = | (842639.381 / 1776153.957) | / | (1009009.008 / 2178088.206) |
| = | 0.474418 | / | 0.463254 |
| | = | 1.0241 |
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 - (1888752.497 + 294889.748) / 5345681.487) | / | (1 - (2115847.172 + 284002.119) / 4870434.315) |
| = | 0.591513 | / | 0.507262 |
| | = | 1.1661 |
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 |
| = | 2178088.206 | / | 1776153.957 |
| | = | 1.2263 |
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)) |
| = | (118876.827 / (118876.827 + 284002.119)) | / | (127352.454 / (127352.454 + 294889.748)) |
| = | 0.295068 | / | 0.30161 |
| | = | 0.9783 |
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) |
| = | (232773.816 / 2178088.206) | / | (228982.155 / 1776153.957) |
| = | 0.106871 | / | 0.12892 |
| | = | 0.829 |
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) |
| = | ((248987.598 + 1772168.712) / 5345681.487) | / | ((859689.707 + 849484.677) / 4870434.315) |
| = | 0.378091 | / | 0.350929 |
| | = | 1.0774 |
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 |
| = | (187253.216 - 0 | - | 310627.196) | / | 5345681.487 |
| | = | -0.023079 |
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.
HYBE has a M-score of -2.47 suggests that the company is unlikely to be a manipulator.
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