Big Lots Beneish M-Score Historical Data
The historical data trend for Big Lots'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.
Big Lots Beneish M-Score Chart
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Big Lots Annual Data
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Trend |
Jan15 |
Jan16 |
Jan17 |
Jan18 |
Jan19 |
Jan20 |
Jan21 |
Jan22 |
Jan23 |
Jan24 |
| Beneish M-Score |
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-2.96 |
-2.59 |
-2.70 |
-2.26 |
-3.53 |
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Big Lots Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-2.26 |
-1.89 |
-3.37 |
-3.47 |
-3.53 |
Competitive Comparison of Big Lots's Beneish M-Score
For the Discount Stores subindustry, Big Lots'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.
Big Lots's Beneish M-Score Distribution in the Retail - Defensive Industry
For the Retail - Defensive industry and Consumer Defensive sector, Big Lots's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Big Lots's Beneish M-Score falls into.
Big Lots 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 Big Lots 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 | + | 0.528 * 0.9797 | + | 0.404 * 0.4481 | + | 0.892 * 0.8635 | + | 0.115 * 1.0116 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2126 | + | 4.679 * -0.130873 | - | 0.327 * 1.1581 |
| = | -3.53 |
* 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 $0 Mil.
Revenue was 1432.484 + 1026.677 + 1139.361 + 1123.577 = $4,722 Mil.
Gross Profit was 544.443 + 373.815 + 375.884 + 392.469 = $1,687 Mil.
Total Current Assets was $1,086 Mil.
Total Assets was $3,325 Mil.
Property, Plant and Equipment(Net PPE) was $2,201 Mil.
Depreciation, Depletion and Amortization(DDA) was $147 Mil.
Selling, General, & Admin. Expense(SGA) was $2,135 Mil.
Total Current Liabilities was $831 Mil.
Long-Term Debt & Capital Lease Obligation was $2,023 Mil.
Net Income was -30.709 + 4.743 + -249.837 + -206.073 = $-482 Mil.
Non Operating Income was 0.553 + 204.719 + 0 + 0.005 = $205 Mil.
Cash Flow from Operations was 147.172 + -248.521 + 18.327 + -168.938 = $-252 Mil.
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Total Receivables was $0 Mil.
Revenue was 1543.113 + 1204.281 + 1346.221 + 1374.714 = $5,468 Mil.
Gross Profit was 560.901 + 409.46 + 438.548 + 504.594 = $1,914 Mil.
Total Current Assets was $1,285 Mil.
Total Assets was $3,691 Mil.
Property, Plant and Equipment(Net PPE) was $2,311 Mil.
Depreciation, Depletion and Amortization(DDA) was $156 Mil.
Selling, General, & Admin. Expense(SGA) was $2,039 Mil.
Total Current Liabilities was $920 Mil.
Long-Term Debt & Capital Lease Obligation was $1,815 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) |
| = | (0 / 4722.099) | / | (0 / 5468.329) |
| = | 0 | / | 0 |
| | = | 1 |
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) |
| = | (1913.503 / 5468.329) | / | (1686.611 / 4722.099) |
| = | 0.349925 | / | 0.357174 |
| | = | 0.9797 |
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 - (1086.023 + 2201.03) / 3325.309) | / | (1 - (1285.314 + 2310.867) / 3690.931) |
| = | 0.011504 | / | 0.025671 |
| | = | 0.4481 |
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 |
| = | 4722.099 | / | 5468.329 |
| | = | 0.8635 |
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)) |
| = | (156.427 / (156.427 + 2310.867)) | / | (147.177 / (147.177 + 2201.03)) |
| = | 0.0634 | / | 0.062676 |
| | = | 1.0116 |
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) |
| = | (2134.734 / 4722.099) | / | (2038.725 / 5468.329) |
| = | 0.452073 | / | 0.372824 |
| | = | 1.2126 |
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) |
| = | ((2022.905 + 831.019) / 3325.309) | / | ((1815.409 + 919.854) / 3690.931) |
| = | 0.858243 | / | 0.741077 |
| | = | 1.1581 |
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 |
| = | (-481.876 - 205.277 | - | -251.96) | / | 3325.309 |
| | = | -0.130873 |
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.
Big Lots has a M-score of -3.53 suggests that the company is unlikely to be a manipulator.
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