Oshkosh Beneish M-Score Historical Data
The historical data trend for Oshkosh'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.
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Oshkosh Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
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-2.39 |
-2.53 |
-2.79 |
-2.46 |
-2.36 |
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Oshkosh Quarterly Data
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Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
|
|
|
|
|
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|
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|
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-2.46 |
-2.31 |
-2.53 |
-2.35 |
-2.36 |
Competitive Comparison
For the Farm & Heavy Construction Machinery subindustry, Oshkosh'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.
Oshkosh Beneish M-Score Distribution
For the Farm & Heavy Construction Machinery industry and Industrials sector, Oshkosh's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Oshkosh's Beneish M-Score falls into.
Oshkosh 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 Oshkosh 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 * 1.0321 | + | 0.528 * 0.7315 | + | 0.404 * 1.3153 | + | 0.892 * 1.1661 | + | 0.115 * 0.8584 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0485 | + | 4.679 * -0.001687 | - | 0.327 * 1.0324 |
| = | -2.36 |
* 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 $2,130 Mil.
Revenue was 2466.8 + 2509.9 + 2413.1 + 2268.1 = $9,658 Mil.
Gross Profit was 454.4 + 468.1 + 424.5 + 333.8 = $1,681 Mil.
Total Current Assets was $4,481 Mil.
Total Assets was $9,129 Mil.
Property, Plant and Equipment(Net PPE) was $1,334 Mil.
Depreciation, Depletion and Amortization(DDA) was $160 Mil.
Selling, General, & Admin. Expense(SGA) was $810 Mil.
Total Current Liabilities was $3,090 Mil.
Long-Term Debt & Capital Lease Obligation was $598 Mil.
Net Income was 150.8 + 183.7 + 175 + 88.5 = $598 Mil.
Non Operating Income was 0.6 + 2.6 + 4.8 + 5.8 = $14 Mil.
Cash Flow from Operations was 479.6 + 166.6 + -126.4 + 79.8 = $600 Mil.
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Total Receivables was $1,770 Mil.
Revenue was 2203.6 + 2066.7 + 2066 + 1945.7 = $8,282 Mil.
Gross Profit was 334.3 + 278.7 + 240.1 + 201.3 = $1,054 Mil.
Total Current Assets was $4,532 Mil.
Total Assets was $7,729 Mil.
Property, Plant and Equipment(Net PPE) was $1,063 Mil.
Depreciation, Depletion and Amortization(DDA) was $108 Mil.
Selling, General, & Admin. Expense(SGA) was $663 Mil.
Total Current Liabilities was $2,429 Mil.
Long-Term Debt & Capital Lease Obligation was $595 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) |
| = | (2130.2 / 9657.9) | / | (1769.9 / 8282) |
| = | 0.220566 | / | 0.213704 |
| | = | 1.0321 |
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) |
| = | (1054.4 / 8282) | / | (1680.8 / 9657.9) |
| = | 0.127312 | / | 0.174034 |
| | = | 0.7315 |
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 - (4480.8 + 1333.8) / 9129.2) | / | (1 - (4532.1 + 1063.4) / 7729) |
| = | 0.363077 | / | 0.276038 |
| | = | 1.3153 |
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 |
| = | 9657.9 | / | 8282 |
| | = | 1.1661 |
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)) |
| = | (107.6 / (107.6 + 1063.4)) | / | (159.9 / (159.9 + 1333.8)) |
| = | 0.091887 | / | 0.10705 |
| | = | 0.8584 |
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) |
| = | (810.4 / 9657.9) | / | (662.8 / 8282) |
| = | 0.083911 | / | 0.080029 |
| | = | 1.0485 |
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) |
| = | ((597.5 + 3089.6) / 9129.2) | / | ((595 + 2428.6) / 7729) |
| = | 0.40388 | / | 0.391202 |
| | = | 1.0324 |
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 |
| = | (598 - 13.8 | - | 599.6) | / | 9129.2 |
| | = | -0.001687 |
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.
Oshkosh has a M-score of -2.36 suggests that the company is unlikely to be a manipulator.
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