Pakistan Refinery Beneish M-Score Historical Data
The historical data trend for Pakistan Refinery'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.
Pakistan Refinery Beneish M-Score Chart
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Pakistan Refinery Annual Data
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Trend |
Jun15 |
Jun16 |
Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
Jun24 |
| Beneish M-Score |
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-4.84 |
-1.76 |
-2.74 |
2.96 |
-2.94 |
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Pakistan Refinery 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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0.44 |
4.37 |
-2.30 |
-2.94 |
-0.94 |
Competitive Comparison of Pakistan Refinery's Beneish M-Score
For the Oil & Gas Refining & Marketing subindustry, Pakistan Refinery'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.
Pakistan Refinery's Beneish M-Score Distribution in the Oil & Gas Industry
For the Oil & Gas industry and Energy sector, Pakistan Refinery's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Pakistan Refinery's Beneish M-Score falls into.
Pakistan Refinery 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 Pakistan Refinery 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 * 0.9028 | + | 0.528 * 2.4546 | + | 0.404 * 3.0446 | + | 0.892 * 1.043 | + | 0.115 * 0.9654 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4081 | + | 4.679 * 0.014669 | - | 0.327 * 1.0045 |
| = | -0.94 |
* 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 ₨39,419 Mil.
Revenue was 82099.486 + 73895.699 + 49455.73 + 88814.093 = ₨294,265 Mil.
Gross Profit was 56.345 + 2151.062 + -559.095 + 4567.866 = ₨6,216 Mil.
Total Current Assets was ₨78,968 Mil.
Total Assets was ₨110,053 Mil.
Property, Plant and Equipment(Net PPE) was ₨30,822 Mil.
Depreciation, Depletion and Amortization(DDA) was ₨1,294 Mil.
Selling, General, & Admin. Expense(SGA) was ₨859 Mil.
Total Current Liabilities was ₨73,339 Mil.
Long-Term Debt & Capital Lease Obligation was ₨9,126 Mil.
Net Income was -2350.408 + -1207.876 + -1239.212 + 2029.627 = ₨-2,768 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₨0 Mil.
Cash Flow from Operations was 2554.743 + -19215.202 + 3892.577 + 8385.691 = ₨-4,382 Mil.
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Total Receivables was ₨41,863 Mil.
Revenue was 93374.157 + 71956.455 + 59554.649 + 57237.856 = ₨282,123 Mil.
Gross Profit was 8933.412 + 1126.44 + 4464.843 + 104.082 = ₨14,629 Mil.
Total Current Assets was ₨95,605 Mil.
Total Assets was ₨124,566 Mil.
Property, Plant and Equipment(Net PPE) was ₨28,863 Mil.
Depreciation, Depletion and Amortization(DDA) was ₨1,168 Mil.
Selling, General, & Admin. Expense(SGA) was ₨585 Mil.
Total Current Liabilities was ₨89,797 Mil.
Long-Term Debt & Capital Lease Obligation was ₨3,126 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) |
| = | (39418.589 / 294265.008) | / | (41863.204 / 282123.117) |
| = | 0.133956 | / | 0.148386 |
| | = | 0.9028 |
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) |
| = | (14628.777 / 282123.117) | / | (6216.178 / 294265.008) |
| = | 0.051852 | / | 0.021124 |
| | = | 2.4546 |
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 - (78967.877 + 30822.032) / 110052.595) | / | (1 - (95605.352 + 28863.135) / 124566.205) |
| = | 0.002387 | / | 0.000784 |
| | = | 3.0446 |
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 |
| = | 294265.008 | / | 282123.117 |
| | = | 1.043 |
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)) |
| = | (1168.105 / (1168.105 + 28863.135)) | / | (1293.956 / (1293.956 + 30822.032)) |
| = | 0.038896 | / | 0.04029 |
| | = | 0.9654 |
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) |
| = | (858.949 / 294265.008) | / | (584.701 / 282123.117) |
| = | 0.002919 | / | 0.002073 |
| | = | 1.4081 |
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) |
| = | ((9125.9 + 73339.335) / 110052.595) | / | ((3125.896 + 89796.851) / 124566.205) |
| = | 0.749326 | / | 0.745971 |
| | = | 1.0045 |
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 |
| = | (-2767.869 - 0 | - | -4382.191) | / | 110052.595 |
| | = | 0.014669 |
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.
Pakistan Refinery has a M-score of -0.94 signals that the company is likely to be a manipulator.
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