Innospec Beneish M-Score Historical Data
The historical data trend for Innospec'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.
Innospec Beneish M-Score Chart
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Innospec Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.56 |
-2.87 |
-2.32 |
-2.30 |
-2.57 |
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Innospec 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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-2.30 |
-2.54 |
-2.82 |
-2.89 |
-2.57 |
Competitive Comparison of Innospec's Beneish M-Score
For the Specialty Chemicals subindustry, Innospec'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.
Innospec's Beneish M-Score Distribution in the Chemicals Industry
For the Chemicals industry and Basic Materials sector, Innospec's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Innospec's Beneish M-Score falls into.
Innospec 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 Innospec 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 * 1.0835 | + | 0.528 * 0.985 | + | 0.404 * 1.0269 | + | 0.892 * 0.9924 | + | 0.115 * 1.1749 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.0833 | + | 4.679 * -0.046093 | - | 0.327 * 0.866 |
| = | -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 (Dec23) TTM: | Last Year (Dec22) TTM: |
Total Receivables was $360 Mil.
Revenue was 494.7 + 464.1 + 480.4 + 509.6 = $1,949 Mil.
Gross Profit was 155.7 + 137.2 + 150.4 + 147.8 = $591 Mil.
Total Current Assets was $886 Mil.
Total Assets was $1,707 Mil.
Property, Plant and Equipment(Net PPE) was $313 Mil.
Depreciation, Depletion and Amortization(DDA) was $39 Mil.
Selling, General, & Admin. Expense(SGA) was $388 Mil.
Total Current Liabilities was $372 Mil.
Long-Term Debt & Capital Lease Obligation was $32 Mil.
Net Income was 37.8 + 39.2 + 28.9 + 33.2 = $139 Mil.
Non Operating Income was -0.7 + 4.8 + 2.7 + 3.7 = $11 Mil.
Cash Flow from Operations was 72.4 + 58.1 + 55 + 21.8 = $207 Mil.
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Total Receivables was $335 Mil.
Revenue was 510.7 + 513 + 467.6 + 472.4 = $1,964 Mil.
Gross Profit was 151.6 + 156 + 139.8 + 139.3 = $587 Mil.
Total Current Assets was $873 Mil.
Total Assets was $1,604 Mil.
Property, Plant and Equipment(Net PPE) was $266 Mil.
Depreciation, Depletion and Amortization(DDA) was $40 Mil.
Selling, General, & Admin. Expense(SGA) was $361 Mil.
Total Current Liabilities was $406 Mil.
Long-Term Debt & Capital Lease Obligation was $31 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) |
| = | (359.8 / 1948.8) | / | (334.6 / 1963.7) |
| = | 0.184626 | / | 0.170393 |
| | = | 1.0835 |
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) |
| = | (586.7 / 1963.7) | / | (591.1 / 1948.8) |
| = | 0.298773 | / | 0.303315 |
| | = | 0.985 |
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 - (885.7 + 313.4) / 1707.4) | / | (1 - (872.6 + 266.2) / 1603.7) |
| = | 0.297704 | / | 0.289892 |
| | = | 1.0269 |
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 |
| = | 1948.8 | / | 1963.7 |
| | = | 0.9924 |
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)) |
| = | (40.1 / (40.1 + 266.2)) | / | (39.3 / (39.3 + 313.4)) |
| = | 0.130917 | / | 0.111426 |
| | = | 1.1749 |
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) |
| = | (387.8 / 1948.8) | / | (360.7 / 1963.7) |
| = | 0.198994 | / | 0.183684 |
| | = | 1.0833 |
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) |
| = | ((31.6 + 371.5) / 1707.4) | / | ((31.4 + 405.8) / 1603.7) |
| = | 0.23609 | / | 0.27262 |
| | = | 0.866 |
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 |
| = | (139.1 - 10.5 | - | 207.3) | / | 1707.4 |
| | = | -0.046093 |
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.
Innospec has a M-score of -2.57 suggests that the company is unlikely to be a manipulator.
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