Beyond Beneish M-Score Historical Data
The historical data trend for Beyond'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.
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Beyond Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
|
-3.25 |
-3.16 |
-0.45 |
-2.22 |
-3.56 |
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Beyond 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 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
-2.22 |
-2.19 |
-2.46 |
-2.52 |
-3.56 |
Competitive Comparison
For the Internet Retail subindustry, Beyond'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.
Beyond Beneish M-Score Distribution
For the Retail - Cyclical industry and Consumer Cyclical sector, Beyond's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Beyond's Beneish M-Score falls into.
Beyond 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 Beyond 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 * 1.3564 | + | 0.528 * 1.1424 | + | 0.404 * 0.8193 | + | 0.892 * 0.8092 | + | 0.115 * 0.8474 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3187 | + | 4.679 * -0.203253 | - | 0.327 * 1.6554 |
| = | -3.56 |
* 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 $19 Mil.
Revenue was 384.458 + 373.313 + 422.211 + 381.14 = $1,561 Mil.
Gross Profit was 59.961 + 69.96 + 94.372 + 89.713 = $314 Mil.
Total Current Assets was $350 Mil.
Total Assets was $636 Mil.
Property, Plant and Equipment(Net PPE) was $31 Mil.
Depreciation, Depletion and Amortization(DDA) was $19 Mil.
Selling, General, & Admin. Expense(SGA) was $315 Mil.
Total Current Liabilities was $232 Mil.
Long-Term Debt & Capital Lease Obligation was $1 Mil.
Net Income was -160.993 + -63.049 + -73.493 + -10.307 = $-308 Mil.
Non Operating Income was -33.231 + -38.731 + -80.673 + -7.389 = $-160 Mil.
Cash Flow from Operations was -27.717 + -9.641 + -1.235 + 20.007 = $-19 Mil.
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Total Receivables was $18 Mil.
Revenue was 404.896 + 460.279 + 528.122 + 536.037 = $1,929 Mil.
Gross Profit was 89.555 + 107.472 + 121.105 + 125.212 = $443 Mil.
Total Current Assets was $415 Mil.
Total Assets was $879 Mil.
Property, Plant and Equipment(Net PPE) was $34 Mil.
Depreciation, Depletion and Amortization(DDA) was $17 Mil.
Selling, General, & Admin. Expense(SGA) was $295 Mil.
Total Current Liabilities was $191 Mil.
Long-Term Debt & Capital Lease Obligation was $4 Mil.
|
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) |
| = | (19.42 / 1561.122) | / | (17.693 / 1929.334) |
| = | 0.01244 | / | 0.009171 |
| | = | 1.3564 |
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) |
| = | (443.344 / 1929.334) | / | (314.006 / 1561.122) |
| = | 0.229791 | / | 0.201141 |
| | = | 1.1424 |
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 - (350.073 + 31.045) / 635.818) | / | (1 - (414.509 + 34.483) / 878.546) |
| = | 0.400586 | / | 0.488937 |
| | = | 0.8193 |
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 |
| = | 1561.122 | / | 1929.334 |
| | = | 0.8092 |
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)) |
| = | (16.706 / (16.706 + 34.483)) | / | (19.447 / (19.447 + 31.045)) |
| = | 0.326359 | / | 0.38515 |
| | = | 0.8474 |
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) |
| = | (314.957 / 1561.122) | / | (295.178 / 1929.334) |
| = | 0.20175 | / | 0.152995 |
| | = | 1.3187 |
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) |
| = | ((0.94 + 232.395) / 635.818) | / | ((3.626 + 191.142) / 878.546) |
| = | 0.366984 | / | 0.221694 |
| | = | 1.6554 |
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 |
| = | (-307.842 - -160.024 | - | -18.586) | / | 635.818 |
| | = | -0.203253 |
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.
Beyond has a M-score of -3.56 suggests that the company is unlikely to be a manipulator.
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