Sajo Industries Co Beneish M-Score Historical Data
The historical data trend for Sajo Industries Co'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.
Sajo Industries Co Beneish M-Score Chart
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Sajo Industries Co Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.01 |
-2.60 |
-2.75 |
-2.15 |
0.36 |
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Sajo Industries Co 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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-2.14 |
-1.71 |
-0.54 |
0.36 |
-0.91 |
Competitive Comparison of Sajo Industries Co's Beneish M-Score
For the Packaged Foods subindustry, Sajo Industries Co'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.
Sajo Industries Co's Beneish M-Score Distribution in the Consumer Packaged Goods Industry
For the Consumer Packaged Goods industry and Consumer Defensive sector, Sajo Industries Co's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Sajo Industries Co's Beneish M-Score falls into.
Sajo Industries Co 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 Sajo Industries Co 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 | + | 0.528 * 5.0641 | + | 0.404 * 2.1435 | + | 0.892 * 0.9917 | + | 0.115 * 0.0476 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3064 | + | 4.679 * 0.006696 | - | 0.327 * 0.952 |
| = | -0.91 |
* 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 ₩0 Mil.
Revenue was 144705.006 + 167226.068 + 158476.846 + 176355.498 = ₩646,763 Mil.
Gross Profit was 10567.525 + -1484.308 + -1147.734 + 7027.94 = ₩14,963 Mil.
Total Current Assets was ₩313,308 Mil.
Total Assets was ₩1,208,052 Mil.
Property, Plant and Equipment(Net PPE) was ₩0 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩15,930 Mil.
Selling, General, & Admin. Expense(SGA) was ₩29,264 Mil.
Total Current Liabilities was ₩482,002 Mil.
Long-Term Debt & Capital Lease Obligation was ₩0 Mil.
Net Income was 10292.691 + 6815.592 + -2754.792 + 10297.23 = ₩24,651 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₩0 Mil.
Cash Flow from Operations was 0 + 5308.446 + 5623.651 + 5629.263 = ₩16,561 Mil.
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Total Receivables was ₩60,239 Mil.
Revenue was 130181.864 + 171325.5 + 172363.811 + 178280.557 = ₩652,152 Mil.
Gross Profit was 9716.337 + 14377.335 + 22705.541 + 29607.965 = ₩76,407 Mil.
Total Current Assets was ₩354,633 Mil.
Total Assets was ₩1,187,687 Mil.
Property, Plant and Equipment(Net PPE) was ₩422,674 Mil.
Depreciation, Depletion and Amortization(DDA) was ₩21,146 Mil.
Selling, General, & Admin. Expense(SGA) was ₩22,587 Mil.
Total Current Liabilities was ₩432,617 Mil.
Long-Term Debt & Capital Lease Obligation was ₩65,131 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) |
| = | (0 / 646763.418) | / | (60239.127 / 652151.732) |
| = | 0 | / | 0.09237 |
| | = | 0 |
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) |
| = | (76407.178 / 652151.732) | / | (14963.423 / 646763.418) |
| = | 0.117162 | / | 0.023136 |
| | = | 5.0641 |
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 - (313307.618 + 0) / 1208052.117) | / | (1 - (354632.963 + 422673.717) / 1187687.062) |
| = | 0.740651 | / | 0.345529 |
| | = | 2.1435 |
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 |
| = | 646763.418 | / | 652151.732 |
| | = | 0.9917 |
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)) |
| = | (21146.209 / (21146.209 + 422673.717)) | / | (15930.232 / (15930.232 + 0)) |
| = | 0.047646 | / | 1 |
| | = | 0.0476 |
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) |
| = | (29263.89 / 646763.418) | / | (22586.693 / 652151.732) |
| = | 0.045247 | / | 0.034634 |
| | = | 1.3064 |
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) |
| = | ((0 + 482002.051) / 1208052.117) | / | ((65130.518 + 432616.97) / 1187687.062) |
| = | 0.398991 | / | 0.41909 |
| | = | 0.952 |
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 |
| = | (24650.721 - 0 | - | 16561.36) | / | 1208052.117 |
| | = | 0.006696 |
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.
Sajo Industries Co has a M-score of -0.91 signals that the company is likely to be a manipulator.
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