Getalong Enterprise Beneish M-Score Historical Data
The historical data trend for Getalong Enterprise'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.
Getalong Enterprise Beneish M-Score Chart
|
Getalong Enterprise Annual Data
|
|
Trend |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
|
- |
- |
-1.93 |
|
Getalong Enterprise Semi-Annual Data
|
|
Mar21 |
Sep21 |
Mar22 |
Sep22 |
Mar23 |
| Beneish M-Score |
- |
- |
- |
- |
-1.93 |
Competitive Comparison of Getalong Enterprise's Beneish M-Score
For the Personal Services subindustry, Getalong Enterprise'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.
Getalong Enterprise's Beneish M-Score Distribution in the Personal Services Industry
For the Personal Services industry and Consumer Cyclical sector, Getalong Enterprise's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Getalong Enterprise's Beneish M-Score falls into.
Getalong Enterprise 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 Getalong Enterprise 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 * 0.7817 | + | 0.528 * 0.353 | + | 0.404 * 3.0619 | + | 0.892 * 0.6445 | + | 0.115 * 0.2365 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.3565 | + | 4.679 * 0.113357 | - | 0.327 * 0.9262 |
| = | -1.93 |
* 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 (Mar23) TTM: | Last Year (Mar22) TTM: |
Total Receivables was ₹479.6 Mil.
Revenue was ₹700.2 Mil.
Gross Profit was ₹93.7 Mil.
Total Current Assets was ₹546.5 Mil.
Total Assets was ₹630.0 Mil.
Property, Plant and Equipment(Net PPE) was ₹33.4 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹0.1 Mil.
Selling, General, & Admin. Expense(SGA) was ₹8.0 Mil.
Total Current Liabilities was ₹536.4 Mil.
Long-Term Debt & Capital Lease Obligation was ₹0.0 Mil.
Net Income was ₹5.6 Mil.
Gross Profit was ₹0.0 Mil.
Cash Flow from Operations was ₹-65.8 Mil.
|
Total Receivables was ₹952.0 Mil.
Revenue was ₹1,086.3 Mil.
Gross Profit was ₹51.3 Mil.
Total Current Assets was ₹1,054.8 Mil.
Total Assets was ₹1,111.5 Mil.
Property, Plant and Equipment(Net PPE) was ₹27.9 Mil.
Depreciation, Depletion and Amortization(DDA) was ₹0.0 Mil.
Selling, General, & Admin. Expense(SGA) was ₹34.6 Mil.
Total Current Liabilities was ₹1,021.9 Mil.
Long-Term Debt & Capital Lease Obligation was ₹0.0 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) |
| = | (479.642 / 700.171) | / | (952.049 / 1086.327) |
| = | 0.685036 | / | 0.876393 |
| | = | 0.7817 |
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) |
| = | (51.328 / 1086.327) | / | (93.71 / 700.171) |
| = | 0.047249 | / | 0.133839 |
| | = | 0.353 |
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 - (546.505 + 33.394) / 629.955) | / | (1 - (1054.761 + 27.931) / 1111.538) |
| = | 0.07946 | / | 0.025951 |
| | = | 3.0619 |
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 |
| = | 700.171 | / | 1086.327 |
| | = | 0.6445 |
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)) |
| = | (0.015 / (0.015 + 27.931)) | / | (0.076 / (0.076 + 33.394)) |
| = | 0.000537 | / | 0.002271 |
| | = | 0.2365 |
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) |
| = | (7.951 / 700.171) | / | (34.602 / 1086.327) |
| = | 0.011356 | / | 0.031852 |
| | = | 0.3565 |
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 + 536.373) / 629.955) | / | ((0 + 1021.879) / 1111.538) |
| = | 0.851447 | / | 0.919338 |
| | = | 0.9262 |
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 |
| = | (5.564 - 0 | - | -65.846) | / | 629.955 |
| | = | 0.113357 |
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.
Getalong Enterprise has a M-score of -1.93 suggests that the company is unlikely to be a manipulator.
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