Showbox Beneish M-Score Historical Data
The historical data trend for Showbox'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.
Showbox Beneish M-Score Chart
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Showbox Annual Data
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Trend |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
Dec24 |
| Beneish M-Score |
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-1.68 |
-2.06 |
-0.98 |
-5.33 |
-2.98 |
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Showbox Quarterly Data
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Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
Dec24 |
| Beneish M-Score |
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-5.33 |
1.11 |
-2.73 |
-3.80 |
-2.98 |
Competitive Comparison of Showbox's Beneish M-Score
For the Entertainment subindustry, Showbox'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.
Showbox's Beneish M-Score Distribution in the Media - Diversified Industry
For the Media - Diversified industry and Communication Services sector, Showbox's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Showbox's Beneish M-Score falls into.
Showbox 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 Showbox 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 * 0.339 | + | 0.528 * -1.2342 | + | 0.404 * 0.8822 | + | 0.892 * 2.3181 | + | 0.115 * 1.0006 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.334 | + | 4.679 * -0.012277 | - | 0.327 * 0.6842 |
| = | -2.98 |
* 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 (Dec24) TTM: | Last Year (Dec23) TTM: |
Total Receivables was ₩6,177 Mil.
Revenue was 8070.333 + 4853.717 + 16979.429 + 63214.093 = ₩93,118 Mil.
Gross Profit was 1746.112 + 2158.579 + 8182.16 + 23205.786 = ₩35,293 Mil.
Total Current Assets was ₩95,038 Mil.
Total Assets was ₩154,047 Mil.
Property, Plant and Equipment(Net PPE) was ₩1,368 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩31,953 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,357 Mil.
Total Current Liabilities was ₩20,364 Mil.
Long-Term Debt & Capital Lease Obligation was ₩728 Mil.
Net Income was 998.641 + -65.455 + 6417.757 + 20077.409 = ₩27,428 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was -4128.294 + -16887.417 + 36790.533 + 13544.73 = ₩29,320 Mil.
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Total Receivables was ₩7,860 Mil.
Revenue was 7571.177 + 17497.406 + 3060.085 + 12041.541 = ₩40,170 Mil.
Gross Profit was -3540.105 + -19616.568 + 1380.044 + 2985.777 = ₩-18,791 Mil.
Total Current Assets was ₩74,095 Mil.
Total Assets was ₩132,070 Mil.
Property, Plant and Equipment(Net PPE) was ₩1,957 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩46,429 Mil.
Selling, General, & Admin. Expense(SGA) was ₩1,753 Mil.
Total Current Liabilities was ₩25,206 Mil.
Long-Term Debt & Capital Lease Obligation was ₩1,227 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) |
| = | (6177.015 / 93117.572) | / | (7860.178 / 40170.209) |
| = | 0.066336 | / | 0.195672 |
| | = | 0.339 |
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) |
| = | (-18790.852 / 40170.209) | / | (35292.637 / 93117.572) |
| = | -0.467781 | / | 0.379012 |
| | = | -1.2342 |
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 - (95037.516 + 1368.095) / 154046.788) | / | (1 - (74095.202 + 1956.611) / 132069.65) |
| = | 0.37418 | / | 0.424154 |
| | = | 0.8822 |
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 |
| = | 93117.572 | / | 40170.209 |
| | = | 2.3181 |
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)) |
| = | (46428.979 / (46428.979 + 1956.611)) | / | (31953.387 / (31953.387 + 1368.095)) |
| = | 0.959562 | / | 0.958943 |
| | = | 1.0006 |
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) |
| = | (1357.115 / 93117.572) | / | (1752.708 / 40170.209) |
| = | 0.014574 | / | 0.043632 |
| | = | 0.334 |
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) |
| = | ((728.31 + 20364.479) / 154046.788) | / | ((1226.568 + 25205.588) / 132069.65) |
| = | 0.136925 | / | 0.200138 |
| | = | 0.6842 |
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 |
| = | (27428.352 - 0 | - | 29319.552) | / | 154046.788 |
| | = | -0.012277 |
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.
Showbox has a M-score of -2.98 suggests that the company is unlikely to be a manipulator.
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