Albemarle Beneish M-Score Historical Data
The historical data trend for Albemarle'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.
Albemarle Beneish M-Score Chart
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Albemarle Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.61 |
-2.72 |
-2.25 |
-1.44 |
-1.05 |
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Albemarle 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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-1.44 |
-1.15 |
-1.47 |
-1.62 |
-1.05 |
Competitive Comparison of Albemarle's Beneish M-Score
For the Specialty Chemicals subindustry, Albemarle'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.
Albemarle's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Albemarle's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Albemarle's Beneish M-Score falls into.
Albemarle 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 Albemarle 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 * 0.9643 | + | 0.528 * 3.4062 | + | 0.404 * 0.9106 | + | 0.892 * 1.3138 | + | 0.115 * 0.9525 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.3353 | + | 4.679 * 0.003614 | - | 0.327 * 1.008 |
| = | -1.05 |
* 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 $1,835 Mil.
Revenue was 2356.165 + 2310.596 + 2370.19 + 2580.252 = $9,617 Mil.
Gross Profit was -704.052 + 54.934 + 558.487 + 1276.54 = $1,186 Mil.
Total Current Assets was $5,217 Mil.
Total Assets was $18,271 Mil.
Property, Plant and Equipment(Net PPE) was $9,633 Mil.
Depreciation, Depletion and Amortization(DDA) was $430 Mil.
Selling, General, & Admin. Expense(SGA) was $919 Mil.
Total Current Liabilities was $3,560 Mil.
Long-Term Debt & Capital Lease Obligation was $3,655 Mil.
Net Income was -617.68 + 302.533 + 650.043 + 1238.58 = $1,573 Mil.
Non Operating Income was 34.491 + 11.182 + 53.954 + 82.492 = $182 Mil.
Cash Flow from Operations was -98.219 + 628.853 + 73.707 + 720.98 = $1,325 Mil.
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Total Receivables was $1,449 Mil.
Revenue was 2620.978 + 2091.805 + 1479.593 + 1127.728 = $7,320 Mil.
Gross Profit was 1001.319 + 1043.814 + 580.424 + 449.03 = $3,075 Mil.
Total Current Assets was $5,187 Mil.
Total Assets was $15,457 Mil.
Property, Plant and Equipment(Net PPE) was $7,091 Mil.
Depreciation, Depletion and Amortization(DDA) was $301 Mil.
Selling, General, & Admin. Expense(SGA) was $524 Mil.
Total Current Liabilities was $2,741 Mil.
Long-Term Debt & Capital Lease Obligation was $3,314 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) |
| = | (1835.21 / 9617.203) | / | (1448.584 / 7320.104) |
| = | 0.190826 | / | 0.197891 |
| | = | 0.9643 |
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) |
| = | (3074.587 / 7320.104) | / | (1185.909 / 9617.203) |
| = | 0.42002 | / | 0.123311 |
| | = | 3.4062 |
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 - (5216.919 + 9632.609) / 18270.652) | / | (1 - (5186.917 + 7091.17) / 15456.522) |
| = | 0.187247 | / | 0.205637 |
| | = | 0.9106 |
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 |
| = | 9617.203 | / | 7320.104 |
| | = | 1.3138 |
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)) |
| = | (300.841 / (300.841 + 7091.17)) | / | (429.944 / (429.944 + 9632.609)) |
| = | 0.040698 | / | 0.042727 |
| | = | 0.9525 |
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) |
| = | (919.493 / 9617.203) | / | (524.145 / 7320.104) |
| = | 0.095609 | / | 0.071603 |
| | = | 1.3353 |
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) |
| = | ((3654.683 + 3560.462) / 18270.652) | / | ((3314.241 + 2741.015) / 15456.522) |
| = | 0.394904 | / | 0.391761 |
| | = | 1.008 |
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 |
| = | (1573.476 - 182.119 | - | 1325.321) | / | 18270.652 |
| | = | 0.003614 |
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.
Albemarle has a M-score of -1.05 signals that the company is likely to be a manipulator.
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