Barnes & Noble Education Beneish M-Score Historical Data
The historical data trend for Barnes & Noble Education'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.
Barnes & Noble Education Beneish M-Score Chart
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Barnes & Noble Education Annual Data
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| Beneish M-Score |
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-2.92 |
-2.53 |
-2.40 |
-2.89 |
-3.74 |
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Barnes & Noble Education Quarterly Data
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Jan24 |
| Beneish M-Score |
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-2.60 |
-3.74 |
-2.71 |
-2.94 |
-2.79 |
Competitive Comparison of Barnes & Noble Education's Beneish M-Score
For the Specialty Retail subindustry, Barnes & Noble Education'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.
Barnes & Noble Education's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, Barnes & Noble Education's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Barnes & Noble Education's Beneish M-Score falls into.
Barnes & Noble Education 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 Barnes & Noble Education 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 * 1.1019 | + | 0.528 * 1.0193 | + | 0.404 * 0.8817 | + | 0.892 * 1.0305 | + | 0.115 * 0.66 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9137 | + | 4.679 * -0.074708 | - | 0.327 * 1.0625 |
| = | -2.79 |
* 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 $315 Mil.
Revenue was 456.673 + 610.379 + 264.161 + 241.847 = $1,573 Mil.
Gross Profit was 100.036 + 136.242 + 50.634 + 58.282 = $345 Mil.
Total Current Assets was $764 Mil.
Total Assets was $1,152 Mil.
Property, Plant and Equipment(Net PPE) was $278 Mil.
Depreciation, Depletion and Amortization(DDA) was $42 Mil.
Selling, General, & Admin. Expense(SGA) was $320 Mil.
Total Current Liabilities was $850 Mil.
Long-Term Debt & Capital Lease Obligation was $185 Mil.
Net Income was -9.639 + 24.18 + -50.388 + -46.25 = $-82 Mil.
Non Operating Income was -9.211 + -4.274 + -4.633 + -5.341 = $-23 Mil.
Cash Flow from Operations was -35.772 + 72.025 + -123.124 + 114.267 = $27 Mil.
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Total Receivables was $278 Mil.
Revenue was 438.054 + 608.633 + 254.674 + 225.165 = $1,527 Mil.
Gross Profit was 97.011 + 138.141 + 56.005 + 50.283 = $341 Mil.
Total Current Assets was $790 Mil.
Total Assets was $1,281 Mil.
Property, Plant and Equipment(Net PPE) was $352 Mil.
Depreciation, Depletion and Amortization(DDA) was $33 Mil.
Selling, General, & Admin. Expense(SGA) was $340 Mil.
Total Current Liabilities was $610 Mil.
Long-Term Debt & Capital Lease Obligation was $474 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) |
| = | (315.126 / 1573.06) | / | (277.513 / 1526.526) |
| = | 0.200327 | / | 0.181794 |
| | = | 1.1019 |
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) |
| = | (341.44 / 1526.526) | / | (345.194 / 1573.06) |
| = | 0.223671 | / | 0.219441 |
| | = | 1.0193 |
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 - (763.651 + 277.511) / 1151.597) | / | (1 - (790.078 + 351.695) / 1281.106) |
| = | 0.095897 | / | 0.10876 |
| | = | 0.8817 |
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 |
| = | 1573.06 | / | 1526.526 |
| | = | 1.0305 |
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)) |
| = | (33.035 / (33.035 + 351.695)) | / | (41.501 / (41.501 + 277.511)) |
| = | 0.085865 | / | 0.130092 |
| | = | 0.66 |
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) |
| = | (319.668 / 1573.06) | / | (339.507 / 1526.526) |
| = | 0.203214 | / | 0.222405 |
| | = | 0.9137 |
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) |
| = | ((185.417 + 849.586) / 1151.597) | / | ((474.066 + 609.578) / 1281.106) |
| = | 0.898755 | / | 0.845866 |
| | = | 1.0625 |
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 |
| = | (-82.097 - -23.459 | - | 27.396) | / | 1151.597 |
| | = | -0.074708 |
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.
Barnes & Noble Education has a M-score of -2.79 suggests that the company is unlikely to be a manipulator.
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