FedEx Beneish M-Score Historical Data
The historical data trend for FedEx'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.
FedEx Beneish M-Score Chart
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FedEx Annual Data
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Trend |
May15 |
May16 |
May17 |
May18 |
May19 |
May20 |
May21 |
May22 |
May23 |
May24 |
| Beneish M-Score |
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-2.55 |
-0.21 |
-2.55 |
-2.48 |
-2.66 |
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FedEx Quarterly Data
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Nov19 |
Feb20 |
May20 |
Aug20 |
Nov20 |
Feb21 |
May21 |
Aug21 |
Nov21 |
Feb22 |
May22 |
Aug22 |
Nov22 |
Feb23 |
May23 |
Aug23 |
Nov23 |
Feb24 |
May24 |
Aug24 |
| Beneish M-Score |
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-2.47 |
-2.46 |
-2.47 |
-2.66 |
-2.57 |
Competitive Comparison of FedEx's Beneish M-Score
For the Integrated Freight & Logistics subindustry, FedEx'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.
FedEx's Beneish M-Score Distribution in the Transportation Industry
For the Transportation industry and Industrials sector, FedEx's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where FedEx's Beneish M-Score falls into.
FedEx 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 FedEx 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 * 1.0219 | + | 0.528 * 1.0183 | + | 0.404 * 1.0179 | + | 0.892 * 0.9887 | + | 0.115 * 0.9822 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.6964 | + | 4.679 * -0.036247 | - | 0.327 * 0.9987 |
| = | -2.57 |
* 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 (Aug24) TTM: | Last Year (Aug23) TTM: |
Total Receivables was $10,312 Mil.
Revenue was 21579 + 22109 + 21738 + 22165 = $87,591 Mil.
Gross Profit was 4376 + 5123 + 4539 + 4577 = $18,615 Mil.
Total Current Assets was $18,094 Mil.
Total Assets was $86,711 Mil.
Property, Plant and Equipment(Net PPE) was $58,349 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,294 Mil.
Selling, General, & Admin. Expense(SGA) was $-683 Mil.
Total Current Liabilities was $14,111 Mil.
Long-Term Debt & Capital Lease Obligation was $34,633 Mil.
Net Income was 794 + 1474 + 879 + 900 = $4,047 Mil.
Non Operating Income was -68 + 194 + -83 + -122 = $-79 Mil.
Cash Flow from Operations was 1187 + 2698 + 1610 + 1774 = $7,269 Mil.
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Total Receivables was $10,207 Mil.
Revenue was 21681 + 21930 + 22169 + 22814 = $88,594 Mil.
Gross Profit was 4713 + 5243 + 4575 + 4641 = $19,172 Mil.
Total Current Assets was $18,887 Mil.
Total Assets was $87,576 Mil.
Property, Plant and Equipment(Net PPE) was $58,501 Mil.
Depreciation, Depletion and Amortization(DDA) was $4,223 Mil.
Selling, General, & Admin. Expense(SGA) was $-992 Mil.
Total Current Liabilities was $13,811 Mil.
Long-Term Debt & Capital Lease Obligation was $35,483 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) |
| = | (10312 / 87591) | / | (10207 / 88594) |
| = | 0.117729 | / | 0.115211 |
| | = | 1.0219 |
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) |
| = | (19172 / 88594) | / | (18615 / 87591) |
| = | 0.216403 | / | 0.212522 |
| | = | 1.0183 |
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 - (18094 + 58349) / 86711) | / | (1 - (18887 + 58501) / 87576) |
| = | 0.118416 | / | 0.116333 |
| | = | 1.0179 |
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 |
| = | 87591 | / | 88594 |
| | = | 0.9887 |
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)) |
| = | (4223 / (4223 + 58501)) | / | (4294 / (4294 + 58349)) |
| = | 0.067327 | / | 0.068547 |
| | = | 0.9822 |
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) |
| = | (-683 / 87591) | / | (-992 / 88594) |
| = | -0.007798 | / | -0.011197 |
| | = | 0.6964 |
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) |
| = | ((34633 + 14111) / 86711) | / | ((35483 + 13811) / 87576) |
| = | 0.562143 | / | 0.562871 |
| | = | 0.9987 |
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 |
| = | (4047 - -79 | - | 7269) | / | 86711 |
| | = | -0.036247 |
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.
FedEx has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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