PT Berlina Tbk Beneish M-Score Historical Data
The historical data trend for PT Berlina Tbk'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.
PT Berlina Tbk Beneish M-Score Chart
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PT Berlina Tbk Annual Data
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Trend |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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- |
- |
- |
- |
-3.41 |
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PT Berlina Tbk Quarterly Data
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Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
Mar24 |
Jun24 |
Sep24 |
| Beneish M-Score |
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- |
-3.41 |
-3.09 |
-2.77 |
-2.89 |
Competitive Comparison of PT Berlina Tbk's Beneish M-Score
For the Packaging & Containers subindustry, PT Berlina Tbk'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.
PT Berlina Tbk's Beneish M-Score Distribution in the Packaging & Containers Industry
For the Packaging & Containers industry and Consumer Cyclical sector, PT Berlina Tbk's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where PT Berlina Tbk's Beneish M-Score falls into.
PT Berlina Tbk 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 PT Berlina Tbk 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 * 1.2445 | + | 0.528 * 0.5503 | + | 0.404 * 0.969 | + | 0.892 * 1.0142 | + | 0.115 * 1.0726 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8565 | + | 4.679 * -0.087512 | - | 0.327 * 1.0667 |
| = | -2.89 |
* 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 Rp218,984 Mil.
Revenue was 263172.079 + 240254.111 + 268855.344 + 246514.72 = Rp1,018,796 Mil.
Gross Profit was 41871.371 + 30133.662 + 33134.938 + 11060.015 = Rp116,200 Mil.
Total Current Assets was Rp453,773 Mil.
Total Assets was Rp1,798,599 Mil.
Property, Plant and Equipment(Net PPE) was Rp944,095 Mil.
Depreciation, Depletion and Amortization(DDA) was Rp3,536 Mil.
Selling, General, & Admin. Expense(SGA) was Rp39,109 Mil.
Total Current Liabilities was Rp432,613 Mil.
Long-Term Debt & Capital Lease Obligation was Rp635,441 Mil.
Net Income was -3966.061 + -8887.983 + -8047.696 + -23349.931 = Rp-44,252 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = Rp0 Mil.
Cash Flow from Operations was 41894.212 + -38480.875 + 12391.679 + 97342.375 = Rp113,147 Mil.
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Total Receivables was Rp173,496 Mil.
Revenue was 252853.415 + 230126.674 + 270710.127 + 250822.87 = Rp1,004,513 Mil.
Gross Profit was 19590.874 + 13518.981 + 25674.985 + 4268.409 = Rp63,053 Mil.
Total Current Assets was Rp403,748 Mil.
Total Assets was Rp1,742,519 Mil.
Property, Plant and Equipment(Net PPE) was Rp938,120 Mil.
Depreciation, Depletion and Amortization(DDA) was Rp3,770 Mil.
Selling, General, & Admin. Expense(SGA) was Rp45,019 Mil.
Total Current Liabilities was Rp400,999 Mil.
Long-Term Debt & Capital Lease Obligation was Rp569,075 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) |
| = | (218984.275 / 1018796.254) | / | (173495.871 / 1004513.086) |
| = | 0.214944 | / | 0.172716 |
| | = | 1.2445 |
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) |
| = | (63053.249 / 1004513.086) | / | (116199.986 / 1018796.254) |
| = | 0.06277 | / | 0.114056 |
| | = | 0.5503 |
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 - (453773.455 + 944095.209) / 1798599.36) | / | (1 - (403747.537 + 938119.615) / 1742518.938) |
| = | 0.222802 | / | 0.229927 |
| | = | 0.969 |
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 |
| = | 1018796.254 | / | 1004513.086 |
| | = | 1.0142 |
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)) |
| = | (3770.05 / (3770.05 + 938119.615)) | / | (3536.087 / (3536.087 + 944095.209)) |
| = | 0.004003 | / | 0.003732 |
| | = | 1.0726 |
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) |
| = | (39108.825 / 1018796.254) | / | (45018.971 / 1004513.086) |
| = | 0.038387 | / | 0.044817 |
| | = | 0.8565 |
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) |
| = | ((635441.031 + 432612.708) / 1798599.36) | / | ((569075.24 + 400998.742) / 1742518.938) |
| = | 0.593825 | / | 0.556708 |
| | = | 1.0667 |
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 |
| = | (-44251.671 - 0 | - | 113147.391) | / | 1798599.36 |
| | = | -0.087512 |
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.
PT Berlina Tbk has a M-score of -2.89 suggests that the company is unlikely to be a manipulator.
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