Nestle Pakistan Beneish M-Score Historical Data
The historical data trend for Nestle Pakistan'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.
Nestle Pakistan Beneish M-Score Chart
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Nestle Pakistan Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.83 |
-3.49 |
-2.04 |
-2.83 |
0.91 |
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Nestle Pakistan 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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2.15 |
1.38 |
3.16 |
0.91 |
-2.34 |
Competitive Comparison of Nestle Pakistan's Beneish M-Score
For the Packaged Foods subindustry, Nestle Pakistan'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.
Nestle Pakistan's Beneish M-Score Distribution in the Consumer Packaged Goods Industry
For the Consumer Packaged Goods industry and Consumer Defensive sector, Nestle Pakistan's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Nestle Pakistan's Beneish M-Score falls into.
Nestle Pakistan 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 Nestle Pakistan 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 * 0.9319 | + | 0.528 * 0.9741 | + | 0.404 * 1.9907 | + | 0.892 * 1.1783 | + | 0.115 * 0.9948 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1465 | + | 4.679 * -0.070072 | - | 0.327 * 0.9725 |
| = | -2.34 |
* 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 ₨10,230 Mil.
Revenue was 54394.903 + 49451.739 + 49723.087 + 51838.551 = ₨205,408 Mil.
Gross Profit was 19743.328 + 21079.762 + 15281.098 + 17807.641 = ₨73,912 Mil.
Total Current Assets was ₨70,411 Mil.
Total Assets was ₨104,592 Mil.
Property, Plant and Equipment(Net PPE) was ₨31,503 Mil.
Depreciation, Depletion and Amortization(DDA) was ₨3,906 Mil.
Selling, General, & Admin. Expense(SGA) was ₨29,662 Mil.
Total Current Liabilities was ₨76,279 Mil.
Long-Term Debt & Capital Lease Obligation was ₨9,426 Mil.
Net Income was 5067.684 + 701.573 + 4805.299 + 5324.038 = ₨15,899 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = ₨0 Mil.
Cash Flow from Operations was 3517.678 + 7301.288 + 4581.233 + 7827.42 = ₨23,228 Mil.
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Total Receivables was ₨9,317 Mil.
Revenue was 49591.628 + 41537.758 + 40535.899 + 42661.176 = ₨174,326 Mil.
Gross Profit was 18317.878 + 17629.374 + 11658.762 + 13498.05 = ₨61,104 Mil.
Total Current Assets was ₨62,117 Mil.
Total Assets was ₨94,695 Mil.
Property, Plant and Equipment(Net PPE) was ₨31,360 Mil.
Depreciation, Depletion and Amortization(DDA) was ₨3,865 Mil.
Selling, General, & Admin. Expense(SGA) was ₨21,956 Mil.
Total Current Liabilities was ₨70,520 Mil.
Long-Term Debt & Capital Lease Obligation was ₨9,270 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) |
| = | (10229.973 / 205408.28) | / | (9316.559 / 174326.461) |
| = | 0.049803 | / | 0.053443 |
| | = | 0.9319 |
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) |
| = | (61104.064 / 174326.461) | / | (73911.829 / 205408.28) |
| = | 0.350515 | / | 0.359829 |
| | = | 0.9741 |
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 - (70410.708 + 31503.349) / 104592.077) | / | (1 - (62116.713 + 31360.058) / 94694.751) |
| = | 0.025604 | / | 0.012862 |
| | = | 1.9907 |
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 |
| = | 205408.28 | / | 174326.461 |
| | = | 1.1783 |
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)) |
| = | (3865.428 / (3865.428 + 31360.058)) | / | (3905.761 / (3905.761 + 31503.349)) |
| = | 0.109734 | / | 0.110304 |
| | = | 0.9948 |
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) |
| = | (29662.103 / 205408.28) | / | (21956.232 / 174326.461) |
| = | 0.144406 | / | 0.125949 |
| | = | 1.1465 |
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) |
| = | ((9426.134 + 76279.082) / 104592.077) | / | ((9269.738 + 70520.49) / 94694.751) |
| = | 0.819424 | / | 0.842605 |
| | = | 0.9725 |
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 |
| = | (15898.594 - 0 | - | 23227.619) | / | 104592.077 |
| | = | -0.070072 |
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.
Nestle Pakistan has a M-score of -2.34 suggests that the company is unlikely to be a manipulator.
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