Moelis Beneish M-Score Historical Data
The historical data trend for Moelis'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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Moelis 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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-2.02 |
-2.91 |
-4.36 |
-2.03 |
-2.54 |
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Moelis 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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-2.03 |
-2.66 |
-3.17 |
-3.08 |
-2.54 |
Competitive Comparison
For the Capital Markets subindustry, Moelis'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.
Moelis Beneish M-Score Distribution
For the Capital Markets industry and Financial Services sector, Moelis's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Moelis's Beneish M-Score falls into.
Moelis 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 Moelis 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 * 1.302 | + | 0.528 * 2.2747 | + | 0.404 * 0.9615 | + | 0.892 * 0.8675 | + | 0.115 * 1.0764 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.4645 | + | 4.679 * -0.16476 | - | 0.327 * 1.1122 |
| = | -2.54 |
* 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 $63.6 Mil.
Revenue was 214.878 + 272.179 + 179.871 + 187.82 = $854.7 Mil.
Gross Profit was 36.393 + 29.948 + 34.077 + 39.581 = $140.0 Mil.
Total Current Assets was $250.9 Mil.
Total Assets was $1,179.8 Mil.
Property, Plant and Equipment(Net PPE) was $235.8 Mil.
Depreciation, Depletion and Amortization(DDA) was $8.3 Mil.
Selling, General, & Admin. Expense(SGA) was $107.4 Mil.
Total Current Liabilities was $601.6 Mil.
Long-Term Debt & Capital Lease Obligation was $215.7 Mil.
Net Income was -5.66 + -10.732 + -11.974 + 3.666 = $-24.7 Mil.
Non Operating Income was 5.145 + 9.943 + -5.629 + 1.746 = $11.2 Mil.
Cash Flow from Operations was 99.337 + 140.123 + 71.155 + -152.143 = $158.5 Mil.
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Total Receivables was $56.3 Mil.
Revenue was 207.183 + 233.506 + 242.52 + 302.088 = $985.3 Mil.
Gross Profit was 66.154 + 73.069 + 102.428 + 125.451 = $367.1 Mil.
Total Current Assets was $263.9 Mil.
Total Assets was $1,216.9 Mil.
Property, Plant and Equipment(Net PPE) was $209.5 Mil.
Depreciation, Depletion and Amortization(DDA) was $8.0 Mil.
Selling, General, & Admin. Expense(SGA) was $84.5 Mil.
Total Current Liabilities was $565.2 Mil.
Long-Term Debt & Capital Lease Obligation was $192.8 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) |
| = | (63.635 / 854.748) | / | (56.339 / 985.297) |
| = | 0.074449 | / | 0.05718 |
| | = | 1.302 |
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) |
| = | (367.102 / 985.297) | / | (139.999 / 854.748) |
| = | 0.37258 | / | 0.16379 |
| | = | 2.2747 |
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 - (250.85 + 235.801) / 1179.759) | / | (1 - (263.878 + 209.493) / 1216.869) |
| = | 0.5875 | / | 0.610993 |
| | = | 0.9615 |
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 |
| = | 854.748 | / | 985.297 |
| | = | 0.8675 |
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)) |
| = | (7.975 / (7.975 + 209.493)) | / | (8.317 / (8.317 + 235.801)) |
| = | 0.036672 | / | 0.03407 |
| | = | 1.0764 |
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) |
| = | (107.382 / 854.748) | / | (84.524 / 985.297) |
| = | 0.12563 | / | 0.085785 |
| | = | 1.4645 |
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) |
| = | ((215.684 + 601.613) / 1179.759) | / | ((192.762 + 565.169) / 1216.869) |
| = | 0.692766 | / | 0.622853 |
| | = | 1.1122 |
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 |
| = | (-24.7 - 11.205 | - | 158.472) | / | 1179.759 |
| | = | -0.16476 |
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.
Moelis has a M-score of -2.54 suggests that the company is unlikely to be a manipulator.
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