Matson Beneish M-Score Historical Data
The historical data trend for Matson'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.
Matson Beneish M-Score Chart
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Matson Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-3.01 |
-2.92 |
-2.33 |
-2.35 |
-2.31 |
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Matson 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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-2.35 |
-2.26 |
-2.05 |
-2.52 |
-2.31 |
Competitive Comparison of Matson's Beneish M-Score
For the Marine Shipping subindustry, Matson'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.
Matson's Beneish M-Score Distribution in the Transportation Industry
For the Transportation industry and Industrials sector, Matson's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Matson's Beneish M-Score falls into.
Matson 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 Matson 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 * 1.3026 | + | 0.528 * 1.7491 | + | 0.404 * 1.093 | + | 0.892 * 0.7125 | + | 0.115 * 1.0323 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.5233 | + | 4.679 * -0.051693 | - | 0.327 * 0.8807 |
| = | -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 $424 Mil.
Revenue was 788.9 + 827.5 + 773.4 + 704.8 = $3,095 Mil.
Gross Profit was 144.5 + 203.4 + 168.7 + 107.3 = $624 Mil.
Total Current Assets was $602 Mil.
Total Assets was $4,295 Mil.
Property, Plant and Equipment(Net PPE) was $2,380 Mil.
Depreciation, Depletion and Amortization(DDA) was $286 Mil.
Selling, General, & Admin. Expense(SGA) was $283 Mil.
Total Current Liabilities was $562 Mil.
Long-Term Debt & Capital Lease Obligation was $549 Mil.
Net Income was 62.4 + 119.9 + 80.8 + 34 = $297 Mil.
Non Operating Income was 5.7 + 2.5 + 0.4 + 0 = $9 Mil.
Cash Flow from Operations was 111.4 + 152.6 + 149.8 + 96.7 = $511 Mil.
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Total Receivables was $457 Mil.
Revenue was 801.6 + 1114.8 + 1261.1 + 1165.5 = $4,343 Mil.
Gross Profit was 160.6 + 376.4 + 532.7 + 461.8 = $1,532 Mil.
Total Current Assets was $760 Mil.
Total Assets was $4,330 Mil.
Property, Plant and Equipment(Net PPE) was $2,359 Mil.
Depreciation, Depletion and Amortization(DDA) was $294 Mil.
Selling, General, & Admin. Expense(SGA) was $261 Mil.
Total Current Liabilities was $582 Mil.
Long-Term Debt & Capital Lease Obligation was $690 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) |
| = | (423.9 / 3094.6) | / | (456.7 / 4343) |
| = | 0.136981 | / | 0.105158 |
| | = | 1.3026 |
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) |
| = | (1531.5 / 4343) | / | (623.9 / 3094.6) |
| = | 0.352636 | / | 0.201609 |
| | = | 1.7491 |
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 - (602.3 + 2379.5) / 4294.6) | / | (1 - (759.6 + 2359.4) / 4330) |
| = | 0.305686 | / | 0.279677 |
| | = | 1.093 |
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 |
| = | 3094.6 | / | 4343 |
| | = | 0.7125 |
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)) |
| = | (294.3 / (294.3 + 2359.4)) | / | (286.4 / (286.4 + 2379.5)) |
| = | 0.110902 | / | 0.107431 |
| | = | 1.0323 |
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) |
| = | (283.3 / 3094.6) | / | (261 / 4343) |
| = | 0.091547 | / | 0.060097 |
| | = | 1.5233 |
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) |
| = | ((548.6 + 562.3) / 4294.6) | / | ((690.2 + 581.6) / 4330) |
| = | 0.258674 | / | 0.293718 |
| | = | 0.8807 |
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 |
| = | (297.1 - 8.6 | - | 510.5) | / | 4294.6 |
| | = | -0.051693 |
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.
Matson has a M-score of -2.31 suggests that the company is unlikely to be a manipulator.
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