IFAD Autos Beneish M-Score Historical Data
The historical data trend for IFAD Autos'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.
IFAD Autos Beneish M-Score Chart
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IFAD Autos Annual Data
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Trend |
Jun15 |
Jun16 |
Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-0.72 |
-1.94 |
-2.47 |
-0.99 |
-2.28 |
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IFAD Autos Quarterly Data
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Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
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Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-1.11 |
-2.41 |
-2.45 |
-2.28 |
-2.16 |
Competitive Comparison of IFAD Autos's Beneish M-Score
For the Auto & Truck Dealerships subindustry, IFAD Autos'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.
IFAD Autos's Beneish M-Score Distribution in the Vehicles & Parts Industry
For the Vehicles & Parts industry and Consumer Cyclical sector, IFAD Autos's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where IFAD Autos's Beneish M-Score falls into.
IFAD Autos 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 IFAD Autos 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 * 1.2554 | + | 0.528 * 1.1422 | + | 0.404 * 1.2211 | + | 0.892 * 0.8287 | + | 0.115 * 0.9727 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.97 | + | 4.679 * 0.016798 | - | 0.327 * 1.0151 |
| = | -2.16 |
* 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 (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was BDT27,378 Mil.
Revenue was 1696.647 + 1885.244 + 2776.567 + 2020.69 = BDT8,379 Mil.
Gross Profit was 285.222 + 229.567 + 399.451 + 374.514 = BDT1,289 Mil.
Total Current Assets was BDT35,427 Mil.
Total Assets was BDT41,271 Mil.
Property, Plant and Equipment(Net PPE) was BDT4,373 Mil.
Depreciation, Depletion and Amortization(DDA) was BDT110 Mil.
Selling, General, & Admin. Expense(SGA) was BDT112 Mil.
Total Current Liabilities was BDT16,258 Mil.
Long-Term Debt & Capital Lease Obligation was BDT14,627 Mil.
Net Income was 2.843 + -74.646 + 93.646 + 33.638 = BDT55 Mil.
Non Operating Income was 0 + 0 + 0 + 0 = BDT0 Mil.
Cash Flow from Operations was 127.527 + -354.367 + 402.463 + -813.43 = BDT-638 Mil.
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Total Receivables was BDT26,316 Mil.
Revenue was 2354.803 + 2746.898 + 2609.66 + 2399.615 = BDT10,111 Mil.
Gross Profit was 435.898 + 415.406 + 483.742 + 441.158 = BDT1,776 Mil.
Total Current Assets was BDT34,014 Mil.
Total Assets was BDT39,765 Mil.
Property, Plant and Equipment(Net PPE) was BDT4,591 Mil.
Depreciation, Depletion and Amortization(DDA) was BDT112 Mil.
Selling, General, & Admin. Expense(SGA) was BDT140 Mil.
Total Current Liabilities was BDT15,878 Mil.
Long-Term Debt & Capital Lease Obligation was BDT13,439 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) |
| = | (27378.146 / 8379.148) | / | (26316.174 / 10110.976) |
| = | 3.267414 | / | 2.602733 |
| | = | 1.2554 |
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) |
| = | (1776.204 / 10110.976) | / | (1288.754 / 8379.148) |
| = | 0.175671 | / | 0.153805 |
| | = | 1.1422 |
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 - (35426.693 + 4373.406) / 41270.972) | / | (1 - (34014.022 + 4590.656) / 39765.231) |
| = | 0.035639 | / | 0.029185 |
| | = | 1.2211 |
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 |
| = | 8379.148 | / | 10110.976 |
| | = | 0.8287 |
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)) |
| = | (112.271 / (112.271 + 4590.656)) | / | (110.044 / (110.044 + 4373.406)) |
| = | 0.023873 | / | 0.024544 |
| | = | 0.9727 |
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) |
| = | (112.258 / 8379.148) | / | (139.64 / 10110.976) |
| = | 0.013397 | / | 0.013811 |
| | = | 0.97 |
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) |
| = | ((14627.289 + 16258.3) / 41270.972) | / | ((13439.315 + 15877.527) / 39765.231) |
| = | 0.748361 | / | 0.737248 |
| | = | 1.0151 |
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 |
| = | (55.481 - 0 | - | -637.807) | / | 41270.972 |
| | = | 0.016798 |
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.
IFAD Autos has a M-score of -2.16 suggests that the company is unlikely to be a manipulator.
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