Cencora Beneish M-Score Historical Data
The historical data trend for Cencora'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.
Cencora Beneish M-Score Chart
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Cencora Annual Data
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Trend |
Sep14 |
Sep15 |
Sep16 |
Sep17 |
Sep18 |
Sep19 |
Sep20 |
Sep21 |
Sep22 |
Sep23 |
| Beneish M-Score |
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-2.54 |
-2.17 |
-2.26 |
-2.65 |
-2.49 |
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Cencora 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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-2.53 |
-2.47 |
-2.43 |
-2.49 |
-2.48 |
Competitive Comparison of Cencora's Beneish M-Score
For the Medical Distribution subindustry, Cencora'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.
Cencora's Beneish M-Score Distribution in the Medical Distribution Industry
For the Medical Distribution industry and Healthcare sector, Cencora's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Cencora's Beneish M-Score falls into.
Cencora 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 Cencora 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 * 1.0277 | + | 0.528 * 1.0142 | + | 0.404 * 1.053 | + | 0.892 * 1.1231 | + | 0.115 * 0.7318 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9706 | + | 4.679 * -0.030787 | - | 0.327 * 0.9955 |
| = | -2.48 |
* 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 $21,598 Mil.
Revenue was 72252.833 + 68922.331 + 66947.043 + 63457.205 = $271,579 Mil.
Gross Profit was 2468.812 + 2253.452 + 2264.646 + 2295.442 = $9,282 Mil.
Total Current Assets was $44,859 Mil.
Total Assets was $64,690 Mil.
Property, Plant and Equipment(Net PPE) was $2,117 Mil.
Depreciation, Depletion and Amortization(DDA) was $1,084 Mil.
Selling, General, & Admin. Expense(SGA) was $5,418 Mil.
Total Current Liabilities was $50,773 Mil.
Long-Term Debt & Capital Lease Obligation was $4,186 Mil.
Net Income was 601.5 + 350.565 + 479.581 + 435.402 = $1,867 Mil.
Non Operating Income was 24.5 + -76.033 + -19.541 + -156.65 = $-228 Mil.
Cash Flow from Operations was 885.157 + 1826.811 + 744.935 + 629.508 = $4,086 Mil.
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Total Receivables was $18,713 Mil.
Revenue was 62846.832 + 61174.149 + 60064.601 + 57719.446 = $241,805 Mil.
Gross Profit was 2145.953 + 1985.559 + 2015.369 + 2235.08 = $8,382 Mil.
Total Current Assets was $40,708 Mil.
Total Assets was $57,907 Mil.
Property, Plant and Equipment(Net PPE) was $2,140 Mil.
Depreciation, Depletion and Amortization(DDA) was $705 Mil.
Selling, General, & Admin. Expense(SGA) was $4,970 Mil.
Total Current Liabilities was $44,761 Mil.
Long-Term Debt & Capital Lease Obligation was $4,656 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) |
| = | (21598.185 / 271579.412) | / | (18712.571 / 241805.028) |
| = | 0.079528 | / | 0.077387 |
| | = | 1.0277 |
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) |
| = | (8381.961 / 241805.028) | / | (9282.352 / 271579.412) |
| = | 0.034664 | / | 0.034179 |
| | = | 1.0142 |
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 - (44858.731 + 2117.283) / 64690.297) | / | (1 - (40708.125 + 2139.782) / 57906.893) |
| = | 0.273832 | / | 0.260055 |
| | = | 1.053 |
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 |
| = | 271579.412 | / | 241805.028 |
| | = | 1.1231 |
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)) |
| = | (704.845 / (704.845 + 2139.782)) | / | (1083.881 / (1083.881 + 2117.283)) |
| = | 0.247781 | / | 0.33859 |
| | = | 0.7318 |
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) |
| = | (5417.803 / 271579.412) | / | (4969.78 / 241805.028) |
| = | 0.019949 | / | 0.020553 |
| | = | 0.9706 |
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) |
| = | ((4185.944 + 50773.472) / 64690.297) | / | ((4656.029 + 44760.623) / 57906.893) |
| = | 0.849577 | / | 0.853381 |
| | = | 0.9955 |
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 |
| = | (1867.048 - -227.724 | - | 4086.411) | / | 64690.297 |
| | = | -0.030787 |
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.
Cencora has a M-score of -2.48 suggests that the company is unlikely to be a manipulator.
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