LPP Beneish M-Score Historical Data
The historical data trend for LPP'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.
LPP Beneish M-Score Chart
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LPP Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
| Beneish M-Score |
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-3.35 |
-3.09 |
-2.80 |
-2.72 |
-0.18 |
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LPP Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-0.18 |
-1.05 |
-3.32 |
-3.43 |
-3.48 |
Competitive Comparison of LPP's Beneish M-Score
For the Apparel Manufacturing subindustry, LPP'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.
LPP's Beneish M-Score Distribution in the Manufacturing - Apparel & Accessories Industry
For the Manufacturing - Apparel & Accessories industry and Consumer Cyclical sector, LPP's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where LPP's Beneish M-Score falls into.
LPP 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 LPP 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 * 0.8605 | + | 0.528 * 0.9767 | + | 0.404 * 0.9016 | + | 0.892 * 1.0929 | + | 0.115 * 0.9186 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.8846 | + | 4.679 * -0.198245 | - | 0.327 * 0.9592 |
| = | -3.48 |
* 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 (Jan24) TTM: | Last Year (Jan23) TTM: |
Total Receivables was zł1,115 Mil.
Revenue was 4840.9 + 4350.5 + 4575.4 + 3639.4 = zł17,406 Mil.
Gross Profit was 2539.8 + 2426.4 + 2193.9 + 1806.4 = zł8,967 Mil.
Total Current Assets was zł5,829 Mil.
Total Assets was zł13,802 Mil.
Property, Plant and Equipment(Net PPE) was zł6,888 Mil.
Depreciation, Depletion and Amortization(DDA) was zł1,383 Mil.
Selling, General, & Admin. Expense(SGA) was zł5,646 Mil.
Total Current Liabilities was zł5,654 Mil.
Long-Term Debt & Capital Lease Obligation was zł3,382 Mil.
Net Income was 483.2 + 575.6 + 438.8 + 109.5 = zł1,607 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = zł0 Mil.
Cash Flow from Operations was 1120 + 1097.7 + 980.9 + 1144.7 = zł4,343 Mil.
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Total Receivables was zł1,186 Mil.
Revenue was 4184.9 + 4366.8 + 4340.6 + 3034.2 = zł15,927 Mil.
Gross Profit was 2074.8 + 2134.6 + 2255.8 + 1547.9 = zł8,013 Mil.
Total Current Assets was zł5,569 Mil.
Total Assets was zł12,921 Mil.
Property, Plant and Equipment(Net PPE) was zł6,224 Mil.
Depreciation, Depletion and Amortization(DDA) was zł1,129 Mil.
Selling, General, & Admin. Expense(SGA) was zł5,840 Mil.
Total Current Liabilities was zł5,214 Mil.
Long-Term Debt & Capital Lease Obligation was zł3,605 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) |
| = | (1114.9 / 17406.2) | / | (1185.5 / 15926.5) |
| = | 0.064052 | / | 0.074436 |
| | = | 0.8605 |
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) |
| = | (8013.1 / 15926.5) | / | (8966.5 / 17406.2) |
| = | 0.50313 | / | 0.515133 |
| | = | 0.9767 |
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 - (5828.7 + 6887.6) / 13802.1) | / | (1 - (5569.2 + 6224.4) / 12921) |
| = | 0.078669 | / | 0.087253 |
| | = | 0.9016 |
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 |
| = | 17406.2 | / | 15926.5 |
| | = | 1.0929 |
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)) |
| = | (1129.2 / (1129.2 + 6224.4)) | / | (1382.5 / (1382.5 + 6887.6)) |
| = | 0.153557 | / | 0.167168 |
| | = | 0.9186 |
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) |
| = | (5645.9 / 17406.2) | / | (5840.1 / 15926.5) |
| = | 0.324361 | / | 0.366691 |
| | = | 0.8846 |
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) |
| = | ((3381.8 + 5653.8) / 13802.1) | / | ((3605.1 + 5213.8) / 12921) |
| = | 0.654654 | / | 0.682525 |
| | = | 0.9592 |
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 |
| = | (1607.1 - 0 | - | 4343.3) | / | 13802.1 |
| | = | -0.198245 |
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.
LPP has a M-score of -3.48 suggests that the company is unlikely to be a manipulator.
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