Flex Beneish M-Score Historical Data
The historical data trend for Flex'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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Flex Annual Data
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Trend |
Mar14 |
Mar15 |
Mar16 |
Mar17 |
Mar18 |
Mar19 |
Mar20 |
Mar21 |
Mar22 |
Mar23 |
| Beneish M-Score |
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-1.26 |
-1.91 |
-1.98 |
-2.56 |
-2.40 |
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Flex 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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-2.39 |
-2.40 |
-2.44 |
-2.52 |
-2.55 |
Competitive Comparison
For the Electronic Components subindustry, Flex'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.
Flex Beneish M-Score Distribution
For the Hardware industry and Technology sector, Flex's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Flex's Beneish M-Score falls into.
Flex 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 Flex 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 * 0.9559 | + | 0.528 * 0.8932 | + | 0.404 * 1.1951 | + | 0.892 * 0.9888 | + | 0.115 * 0.9795 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.1029 | + | 4.679 * -0.013847 | - | 0.327 * 0.8709 |
| = | -2.55 |
* 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 $4,209 Mil.
Revenue was 7103 + 7471 + 7336 + 7477 = $29,387 Mil.
Gross Profit was 642 + 665 + 587 + 556 = $2,450 Mil.
Total Current Assets was $14,877 Mil.
Total Assets was $20,366 Mil.
Property, Plant and Equipment(Net PPE) was $2,940 Mil.
Depreciation, Depletion and Amortization(DDA) was $520 Mil.
Selling, General, & Admin. Expense(SGA) was $1,072 Mil.
Total Current Liabilities was $9,386 Mil.
Long-Term Debt & Capital Lease Obligation was $3,933 Mil.
Net Income was 197 + 228 + 186 + 142 = $753 Mil.
Non Operating Income was -18 + -16 + -17 + -11 = $-62 Mil.
Cash Flow from Operations was 284 + 357 + 6 + 450 = $1,097 Mil.
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Total Receivables was $4,453 Mil.
Revenue was 7756 + 7766 + 7347 + 6851 = $29,720 Mil.
Gross Profit was 583 + 591 + 535 + 504 = $2,213 Mil.
Total Current Assets was $15,819 Mil.
Total Assets was $20,892 Mil.
Property, Plant and Equipment(Net PPE) was $2,885 Mil.
Depreciation, Depletion and Amortization(DDA) was $498 Mil.
Selling, General, & Admin. Expense(SGA) was $983 Mil.
Total Current Liabilities was $11,668 Mil.
Long-Term Debt & Capital Lease Obligation was $4,021 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) |
| = | (4209 / 29387) | / | (4453 / 29720) |
| = | 0.143227 | / | 0.149832 |
| | = | 0.9559 |
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) |
| = | (2213 / 29720) | / | (2450 / 29387) |
| = | 0.074462 | / | 0.08337 |
| | = | 0.8932 |
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 - (14877 + 2940) / 20366) | / | (1 - (15819 + 2885) / 20892) |
| = | 0.12516 | / | 0.104729 |
| | = | 1.1951 |
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 |
| = | 29387 | / | 29720 |
| | = | 0.9888 |
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)) |
| = | (498 / (498 + 2885)) | / | (520 / (520 + 2940)) |
| = | 0.147207 | / | 0.150289 |
| | = | 0.9795 |
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) |
| = | (1072 / 29387) | / | (983 / 29720) |
| = | 0.036479 | / | 0.033075 |
| | = | 1.1029 |
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) |
| = | ((3933 + 9386) / 20366) | / | ((4021 + 11668) / 20892) |
| = | 0.653982 | / | 0.750957 |
| | = | 0.8709 |
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 |
| = | (753 - -62 | - | 1097) | / | 20366 |
| | = | -0.013847 |
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.
Flex has a M-score of -2.55 suggests that the company is unlikely to be a manipulator.
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