LY Beneish M-Score Historical Data
The historical data trend for LY'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.
LY Beneish M-Score Chart
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LY Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-2.52 |
-2.62 |
-2.09 |
-2.55 |
-2.17 |
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LY Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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-2.22 |
-2.17 |
-2.17 |
-2.09 |
-2.32 |
Competitive Comparison of LY's Beneish M-Score
For the Internet Retail subindustry, LY'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.
LY's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, LY's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where LY's Beneish M-Score falls into.
LY 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 LY 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 * 1.1322 | + | 0.528 * 0.9738 | + | 0.404 * 1.0102 | + | 0.892 * 1.0819 | + | 0.115 * 1.0095 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0201 | + | 4.679 * -0.002115 | - | 0.327 * 1.04 |
| = | -2.32 |
* 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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was 円2,218,947 Mil.
Revenue was 475041 + 441276 + 430523 + 433781 = 円1,780,621 Mil.
Gross Profit was 344145 + 315610 + 302849 + 300727 = 円1,263,331 Mil.
Total Current Assets was 円3,778,068 Mil.
Total Assets was 円8,983,716 Mil.
Property, Plant and Equipment(Net PPE) was 円462,672 Mil.
Depreciation, Depletion and Amortization(DDA) was 円166,553 Mil.
Selling, General, & Admin. Expense(SGA) was 円1,082,982 Mil.
Total Current Liabilities was 円1,562,125 Mil.
Long-Term Debt & Capital Lease Obligation was 円1,928,637 Mil.
Net Income was 28712 + 56420 + 37316 + -1283 = 円121,165 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = 円0 Mil.
Cash Flow from Operations was 189985 + 71180 + 32240 + -153239 = 円140,166 Mil.
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Total Receivables was 円1,811,478 Mil.
Revenue was 453687 + 394343 + 390565 + 407285 = 円1,645,880 Mil.
Gross Profit was 321543 + 270659 + 268316 + 276672 = 円1,137,190 Mil.
Total Current Assets was 円3,699,875 Mil.
Total Assets was 円8,573,818 Mil.
Property, Plant and Equipment(Net PPE) was 円393,024 Mil.
Depreciation, Depletion and Amortization(DDA) was 円143,321 Mil.
Selling, General, & Admin. Expense(SGA) was 円981,263 Mil.
Total Current Liabilities was 円1,367,626 Mil.
Long-Term Debt & Capital Lease Obligation was 円1,835,879 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) |
| = | (2218947 / 1780621) | / | (1811478 / 1645880) |
| = | 1.246165 | / | 1.100614 |
| | = | 1.1322 |
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) |
| = | (1137190 / 1645880) | / | (1263331 / 1780621) |
| = | 0.690931 | / | 0.709489 |
| | = | 0.9738 |
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 - (3778068 + 462672) / 8983716) | / | (1 - (3699875 + 393024) / 8573818) |
| = | 0.527953 | / | 0.522628 |
| | = | 1.0102 |
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 |
| = | 1780621 | / | 1645880 |
| | = | 1.0819 |
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)) |
| = | (143321 / (143321 + 393024)) | / | (166553 / (166553 + 462672)) |
| = | 0.267218 | / | 0.264695 |
| | = | 1.0095 |
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) |
| = | (1082982 / 1780621) | / | (981263 / 1645880) |
| = | 0.608205 | / | 0.596194 |
| | = | 1.0201 |
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) |
| = | ((1928637 + 1562125) / 8983716) | / | ((1835879 + 1367626) / 8573818) |
| = | 0.388565 | / | 0.373638 |
| | = | 1.04 |
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 |
| = | (121165 - 0 | - | 140166) | / | 8983716 |
| | = | -0.002115 |
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.
LY has a M-score of -2.32 suggests that the company is unlikely to be a manipulator.
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