OSI Systems Beneish M-Score Historical Data
The historical data trend for OSI Systems'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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OSI Systems Annual Data
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Trend |
Jun14 |
Jun15 |
Jun16 |
Jun17 |
Jun18 |
Jun19 |
Jun20 |
Jun21 |
Jun22 |
Jun23 |
| Beneish M-Score |
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-2.87 |
-2.41 |
-2.59 |
-2.29 |
-2.22 |
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OSI Systems 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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-2.25 |
-2.39 |
-2.22 |
-2.41 |
-2.31 |
Competitive Comparison
For the Electronic Components subindustry, OSI Systems'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.
OSI Systems Beneish M-Score Distribution
For the Hardware industry and Technology sector, OSI Systems's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where OSI Systems's Beneish M-Score falls into.
OSI Systems 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 OSI Systems 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 * 0.9991 | + | 0.528 * 0.9645 | + | 0.404 * 0.8811 | + | 0.892 * 1.148 | + | 0.115 * 1.0052 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9458 | + | 4.679 * 0.02403 | - | 0.327 * 1.0432 |
| = | -2.31 |
* 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 $370 Mil.
Revenue was 373.235 + 279.21 + 411.87 + 302.889 = $1,367 Mil.
Gross Profit was 141.301 + 98.745 + 143.02 + 103.786 = $487 Mil.
Total Current Assets was $1,003 Mil.
Total Assets was $1,726 Mil.
Property, Plant and Equipment(Net PPE) was $110 Mil.
Depreciation, Depletion and Amortization(DDA) was $39 Mil.
Selling, General, & Admin. Expense(SGA) was $250 Mil.
Total Current Liabilities was $700 Mil.
Long-Term Debt & Capital Lease Obligation was $133 Mil.
Net Income was 36.553 + 12.879 + 42.381 + 21.808 = $114 Mil.
Non Operating Income was -0.698 + -0.466 + -6.355 + -0.611 = $-8 Mil.
Cash Flow from Operations was -23.528 + 17.144 + 22.134 + 64.514 = $80 Mil.
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Total Receivables was $323 Mil.
Revenue was 295.597 + 268.071 + 336.821 + 290.477 = $1,191 Mil.
Gross Profit was 96.207 + 87.497 + 122.466 + 102.858 = $409 Mil.
Total Current Assets was $767 Mil.
Total Assets was $1,466 Mil.
Property, Plant and Equipment(Net PPE) was $108 Mil.
Depreciation, Depletion and Amortization(DDA) was $39 Mil.
Selling, General, & Admin. Expense(SGA) was $230 Mil.
Total Current Liabilities was $538 Mil.
Long-Term Debt & Capital Lease Obligation was $140 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) |
| = | (370.168 / 1367.204) | / | (322.756 / 1190.966) |
| = | 0.270748 | / | 0.271004 |
| | = | 0.9991 |
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) |
| = | (409.028 / 1190.966) | / | (486.852 / 1367.204) |
| = | 0.343442 | / | 0.356093 |
| | = | 0.9645 |
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 - (1003.083 + 110.188) / 1726.477) | / | (1 - (767.435 + 107.763) / 1466.23) |
| = | 0.355178 | / | 0.403096 |
| | = | 0.8811 |
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 |
| = | 1367.204 | / | 1190.966 |
| | = | 1.148 |
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)) |
| = | (38.632 / (38.632 + 107.763)) | / | (39.226 / (39.226 + 110.188)) |
| = | 0.263889 | / | 0.262532 |
| | = | 1.0052 |
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) |
| = | (249.726 / 1367.204) | / | (230.013 / 1190.966) |
| = | 0.182655 | / | 0.193131 |
| | = | 0.9458 |
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) |
| = | ((132.792 + 700.391) / 1726.477) | / | ((140.057 + 538.242) / 1466.23) |
| = | 0.482591 | / | 0.462614 |
| | = | 1.0432 |
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 |
| = | (113.621 - -8.13 | - | 80.264) | / | 1726.477 |
| | = | 0.02403 |
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.
OSI Systems has a M-score of -2.31 suggests that the company is unlikely to be a manipulator.
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