Kirby Beneish M-Score Historical Data
The historical data trend for Kirby'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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Kirby Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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|
|
|
|
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-2.82 |
-2.43 |
-2.72 |
-2.60 |
-2.84 |
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Kirby 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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-2.60 |
-2.49 |
-2.76 |
-2.84 |
-2.84 |
Competitive Comparison
For the Marine Shipping subindustry, Kirby'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.
Kirby Beneish M-Score Distribution
For the Transportation industry and Industrials sector, Kirby's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Kirby's Beneish M-Score falls into.
Kirby 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 Kirby 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 * 0.8717 | + | 0.528 * 0.8284 | + | 0.404 * 1.0031 | + | 0.892 * 1.1102 | + | 0.115 * 1.0102 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9975 | + | 4.679 * -0.058254 | - | 0.327 * 0.9512 |
| = | -2.84 |
* 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 $579 Mil.
Revenue was 799.176 + 764.772 + 777.248 + 750.444 = $3,092 Mil.
Gross Profit was 182.539 + 180.786 + 179.482 + 157.255 = $700 Mil.
Total Current Assets was $1,135 Mil.
Total Assets was $5,722 Mil.
Property, Plant and Equipment(Net PPE) was $4,013 Mil.
Depreciation, Depletion and Amortization(DDA) was $211 Mil.
Selling, General, & Admin. Expense(SGA) was $335 Mil.
Total Current Liabilities was $676 Mil.
Long-Term Debt & Capital Lease Obligation was $1,147 Mil.
Net Income was 61.906 + 62.964 + 57.367 + 40.698 = $223 Mil.
Non Operating Income was 2.524 + 3.117 + 1.736 + 8.673 = $16 Mil.
Cash Flow from Operations was 216.001 + 96.278 + 211.469 + 16.48 = $540 Mil.
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Total Receivables was $598 Mil.
Revenue was 730.165 + 745.843 + 697.964 + 610.782 = $2,785 Mil.
Gross Profit was 145.151 + 143.032 + 123.987 + 110.2 = $522 Mil.
Total Current Assets was $1,212 Mil.
Total Assets was $5,555 Mil.
Property, Plant and Equipment(Net PPE) was $3,788 Mil.
Depreciation, Depletion and Amortization(DDA) was $201 Mil.
Selling, General, & Admin. Expense(SGA) was $303 Mil.
Total Current Liabilities was $642 Mil.
Long-Term Debt & Capital Lease Obligation was $1,218 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) |
| = | (578.716 / 3091.64) | / | (597.962 / 2784.754) |
| = | 0.187187 | / | 0.214727 |
| | = | 0.8717 |
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) |
| = | (522.37 / 2784.754) | / | (700.062 / 3091.64) |
| = | 0.187582 | / | 0.226437 |
| | = | 0.8284 |
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 - (1135.161 + 4013.321) / 5722.197) | / | (1 - (1211.759 + 3787.969) / 5554.924) |
| = | 0.100261 | / | 0.099947 |
| | = | 1.0031 |
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 |
| = | 3091.64 | / | 2784.754 |
| | = | 1.1102 |
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)) |
| = | (201.443 / (201.443 + 3787.969)) | / | (211.156 / (211.156 + 4013.321)) |
| = | 0.050494 | / | 0.049984 |
| | = | 1.0102 |
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) |
| = | (335.213 / 3091.64) | / | (302.692 / 2784.754) |
| = | 0.108426 | / | 0.108696 |
| | = | 0.9975 |
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) |
| = | ((1147.338 + 675.795) / 5722.197) | / | ((1218.466 + 642.197) / 5554.924) |
| = | 0.318607 | / | 0.334957 |
| | = | 0.9512 |
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 |
| = | (222.935 - 16.05 | - | 540.228) | / | 5722.197 |
| | = | -0.058254 |
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.
Kirby has a M-score of -2.84 suggests that the company is unlikely to be a manipulator.
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