HSN Beneish M-Score Historical Data
The historical data trend for HSN'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.
HSN Beneish M-Score Chart
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HSN Annual Data
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Trend |
Dec07 |
Dec08 |
Dec09 |
Dec10 |
Dec11 |
Dec12 |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
| Beneish M-Score |
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-2.33 |
-2.59 |
-2.20 |
-2.82 |
-2.75 |
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HSN Quarterly Data
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Dec12 |
Mar13 |
Jun13 |
Sep13 |
Dec13 |
Mar14 |
Jun14 |
Sep14 |
Dec14 |
Mar15 |
Jun15 |
Sep15 |
Dec15 |
Mar16 |
Jun16 |
Sep16 |
Dec16 |
Mar17 |
Jun17 |
Sep17 |
| Beneish M-Score |
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-2.64 |
-2.75 |
-2.77 |
-2.78 |
-2.91 |
Competitive Comparison of HSN's Beneish M-Score
For the Specialty Retail subindustry, HSN'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.
HSN's Beneish M-Score Distribution in the Retail - Cyclical Industry
For the Retail - Cyclical industry and Consumer Cyclical sector, HSN's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where HSN's Beneish M-Score falls into.
HSN 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 HSN 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 * 0.9918 | + | 0.528 * 1.0288 | + | 0.404 * 1.0692 | + | 0.892 * 0.9639 | + | 0.115 * 0.9849 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0202 | + | 4.679 * -0.097175 | - | 0.327 * 0.9093 |
| = | -2.91 |
* 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 (Sep17) TTM: | Last Year (Sep16) TTM: |
Total Receivables was $217 Mil.
Revenue was 782.562 + 821.361 + 785.435 + 1073.389 = $3,463 Mil.
Gross Profit was 269.185 + 296.373 + 273.137 + 335.29 = $1,174 Mil.
Total Current Assets was $724 Mil.
Total Assets was $1,216 Mil.
Property, Plant and Equipment(Net PPE) was $212 Mil.
Depreciation, Depletion and Amortization(DDA) was $44 Mil.
Selling, General, & Admin. Expense(SGA) was $930 Mil.
Total Current Liabilities was $474 Mil.
Long-Term Debt & Capital Lease Obligation was $438 Mil.
Net Income was 16.227 + 32.774 + 21.248 + 43.52 = $114 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = $0 Mil.
Cash Flow from Operations was 31.16 + 56.07 + 22.339 + 122.383 = $232 Mil.
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Total Receivables was $227 Mil.
Revenue was 823.023 + 854.308 + 816.765 + 1098.178 = $3,592 Mil.
Gross Profit was 280.076 + 311.824 + 289.478 + 371.546 = $1,253 Mil.
Total Current Assets was $801 Mil.
Total Assets was $1,285 Mil.
Property, Plant and Equipment(Net PPE) was $207 Mil.
Depreciation, Depletion and Amortization(DDA) was $42 Mil.
Selling, General, & Admin. Expense(SGA) was $946 Mil.
Total Current Liabilities was $458 Mil.
Long-Term Debt & Capital Lease Obligation was $601 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) |
| = | (216.62 / 3462.747) | / | (226.589 / 3592.274) |
| = | 0.062557 | / | 0.063077 |
| | = | 0.9918 |
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) |
| = | (1252.924 / 3592.274) | / | (1173.985 / 3462.747) |
| = | 0.348783 | / | 0.339033 |
| | = | 1.0288 |
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 - (724.335 + 212.148) / 1216.183) | / | (1 - (801.011 + 207.216) / 1284.513) |
| = | 0.229982 | / | 0.21509 |
| | = | 1.0692 |
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 |
| = | 3462.747 | / | 3592.274 |
| | = | 0.9639 |
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)) |
| = | (42.221 / (42.221 + 207.216)) | / | (44.025 / (44.025 + 212.148)) |
| = | 0.169265 | / | 0.171857 |
| | = | 0.9849 |
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) |
| = | (930.331 / 3462.747) | / | (946.043 / 3592.274) |
| = | 0.268668 | / | 0.263355 |
| | = | 1.0202 |
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) |
| = | ((438.048 + 473.772) / 1216.183) | / | ((600.687 + 458.412) / 1284.513) |
| = | 0.749739 | / | 0.824514 |
| | = | 0.9093 |
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 |
| = | (113.769 - 0 | - | 231.952) | / | 1216.183 |
| | = | -0.097175 |
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.
HSN has a M-score of -2.91 suggests that the company is unlikely to be a manipulator.
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