HubSpot Beneish M-Score Historical Data
The historical data trend for HubSpot'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.
|
HubSpot Annual Data
|
|
Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
|
|
|
|
|
|
-2.40 |
-2.69 |
-2.40 |
-2.88 |
-2.51 |
|
HubSpot Quarterly Data
|
|
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
-2.88 |
-2.94 |
-2.99 |
-2.93 |
-2.51 |
Competitive Comparison
For the Software - Application subindustry, HubSpot'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.
HubSpot Beneish M-Score Distribution
For the Software industry and Technology sector, HubSpot's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where HubSpot's Beneish M-Score falls into.
HubSpot 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 HubSpot 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 * 1.0383 | + | 0.528 * 0.9734 | + | 0.404 * 1.9159 | + | 0.892 * 1.2538 | + | 0.115 * 0.708 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9701 | + | 4.679 * -0.138618 | - | 0.327 * 0.9242 |
| = | -2.51 |
* 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 $295 Mil.
Revenue was 581.915 + 557.557 + 529.138 + 501.62 = $2,170 Mil.
Gross Profit was 493.28 + 470.031 + 441.852 + 419.574 = $1,825 Mil.
Total Current Assets was $1,872 Mil.
Total Assets was $3,071 Mil.
Property, Plant and Equipment(Net PPE) was $354 Mil.
Depreciation, Depletion and Amortization(DDA) was $73 Mil.
Selling, General, & Admin. Expense(SGA) was $1,318 Mil.
Total Current Liabilities was $956 Mil.
Long-Term Debt & Capital Lease Obligation was $753 Mil.
Net Income was -13.604 + -5.463 + -118.946 + -38.282 = $-176 Mil.
Non Operating Income was -6.092 + -2.51 + -63.55 + -29.364 = $-102 Mil.
Cash Flow from Operations was 104.312 + 89.046 + 76.543 + 81.07 = $351 Mil.
|
Total Receivables was $227 Mil.
Revenue was 469.656 + 443.958 + 421.755 + 395.599 = $1,731 Mil.
Gross Profit was 389.395 + 361.831 + 342.824 + 322.663 = $1,417 Mil.
Total Current Assets was $1,755 Mil.
Total Assets was $2,545 Mil.
Property, Plant and Equipment(Net PPE) was $425 Mil.
Depreciation, Depletion and Amortization(DDA) was $58 Mil.
Selling, General, & Admin. Expense(SGA) was $1,084 Mil.
Total Current Liabilities was $762 Mil.
Long-Term Debt & Capital Lease Obligation was $770 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) |
| = | (295.303 / 2170.23) | / | (226.849 / 1730.968) |
| = | 0.13607 | / | 0.131053 |
| | = | 1.0383 |
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) |
| = | (1416.713 / 1730.968) | / | (1824.737 / 2170.23) |
| = | 0.818451 | / | 0.840804 |
| | = | 0.9734 |
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 - (1871.54 + 354.402) / 3071.392) | / | (1 - (1754.599 + 424.531) / 2544.738) |
| = | 0.275266 | / | 0.143672 |
| | = | 1.9159 |
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 |
| = | 2170.23 | / | 1730.968 |
| | = | 1.2538 |
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)) |
| = | (58.15 / (58.15 + 424.531)) | / | (72.673 / (72.673 + 354.402)) |
| = | 0.120473 | / | 0.170164 |
| | = | 0.708 |
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) |
| = | (1318.207 / 2170.23) | / | (1083.791 / 1730.968) |
| = | 0.607404 | / | 0.626118 |
| | = | 0.9701 |
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) |
| = | ((752.767 + 956.247) / 3071.392) | / | ((770.411 + 761.653) / 2544.738) |
| = | 0.55643 | / | 0.602052 |
| | = | 0.9242 |
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 |
| = | (-176.295 - -101.516 | - | 350.971) | / | 3071.392 |
| | = | -0.138618 |
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.
HubSpot has a M-score of -2.51 suggests that the company is unlikely to be a manipulator.
Quick Browse
Personalize
Premium Gurus 
Create New Portfolio
Portfolio Contest
HUBS has been successfully added to your