Gerdau Beneish M-Score Historical Data
The historical data trend for Gerdau'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.
Gerdau Beneish M-Score Chart
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Gerdau Annual Data
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Trend |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
Dec23 |
| Beneish M-Score |
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-2.49 |
-2.17 |
-2.16 |
-2.49 |
-2.56 |
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Gerdau 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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-2.49 |
-2.34 |
-2.44 |
-2.42 |
-2.56 |
Competitive Comparison of Gerdau's Beneish M-Score
For the Steel subindustry, Gerdau'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.
Gerdau's Beneish M-Score Distribution in the Steel Industry
For the Steel industry and Basic Materials sector, Gerdau's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Gerdau's Beneish M-Score falls into.
Gerdau 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 Gerdau 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 * 1.1859 | + | 0.528 * 1.3913 | + | 0.404 * 1.0072 | + | 0.892 * 0.8603 | + | 0.115 * 1.0853 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 1.2122 | + | 4.679 * -0.059166 | - | 0.327 * 0.885 |
| = | -2.49 |
* 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 $1,403 Mil.
Revenue was 3003.289 + 3455.01 + 3763.185 + 3623.297 = $13,845 Mil.
Gross Profit was 333.231 + 565.467 + 675.431 + 696.67 = $2,271 Mil.
Total Current Assets was $5,959 Mil.
Total Assets was $15,283 Mil.
Property, Plant and Equipment(Net PPE) was $4,911 Mil.
Depreciation, Depletion and Amortization(DDA) was $613 Mil.
Selling, General, & Admin. Expense(SGA) was $444 Mil.
Total Current Liabilities was $2,303 Mil.
Long-Term Debt & Capital Lease Obligation was $2,046 Mil.
Net Income was 117.953 + 320.285 + 440.058 + 615.505 = $1,494 Mil.
Non Operating Income was 27.676 + -3.347 + 14.152 + 107.565 = $146 Mil.
Cash Flow from Operations was 737.439 + 474.798 + 662.76 + 377.008 = $2,252 Mil.
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Total Receivables was $1,375 Mil.
Revenue was 3424.724 + 4033.342 + 4550.279 + 4085.381 = $16,094 Mil.
Gross Profit was 558.254 + 903.55 + 1169.628 + 1041.114 = $3,673 Mil.
Total Current Assets was $5,959 Mil.
Total Assets was $14,069 Mil.
Property, Plant and Equipment(Net PPE) was $4,077 Mil.
Depreciation, Depletion and Amortization(DDA) was $559 Mil.
Selling, General, & Admin. Expense(SGA) was $426 Mil.
Total Current Liabilities was $2,567 Mil.
Long-Term Debt & Capital Lease Obligation was $1,957 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) |
| = | (1402.572 / 13844.781) | / | (1374.855 / 16093.726) |
| = | 0.101307 | / | 0.085428 |
| | = | 1.1859 |
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) |
| = | (3672.546 / 16093.726) | / | (2270.799 / 13844.781) |
| = | 0.228197 | / | 0.164018 |
| | = | 1.3913 |
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 - (5959.006 + 4911.054) / 15283.306) | / | (1 - (5959.016 + 4076.64) / 14069.213) |
| = | 0.288763 | / | 0.286694 |
| | = | 1.0072 |
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 |
| = | 13844.781 | / | 16093.726 |
| | = | 0.8603 |
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)) |
| = | (558.59 / (558.59 + 4076.64)) | / | (613.447 / (613.447 + 4911.054)) |
| = | 0.12051 | / | 0.111041 |
| | = | 1.0853 |
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) |
| = | (444.269 / 13844.781) | / | (426.037 / 16093.726) |
| = | 0.032089 | / | 0.026472 |
| | = | 1.2122 |
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) |
| = | ((2046.028 + 2303.076) / 15283.306) | / | ((1957.113 + 2566.55) / 14069.213) |
| = | 0.284566 | / | 0.321529 |
| | = | 0.885 |
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 |
| = | (1493.801 - 146.046 | - | 2252.005) | / | 15283.306 |
| | = | -0.059166 |
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.
Gerdau has a M-score of -2.49 suggests that the company is unlikely to be a manipulator.
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