Ciena Beneish M-Score Historical Data
The historical data trend for Ciena'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.
Ciena Beneish M-Score Chart
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Ciena Annual Data
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Trend |
Oct14 |
Oct15 |
Oct16 |
Oct17 |
Oct18 |
Oct19 |
Oct20 |
Oct21 |
Oct22 |
Oct23 |
| Beneish M-Score |
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-2.60 |
-2.63 |
-2.31 |
-2.11 |
-2.25 |
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Ciena Quarterly Data
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Apr19 |
Jul19 |
Oct19 |
Jan20 |
Apr20 |
Jul20 |
Oct20 |
Jan21 |
Apr21 |
Jul21 |
Oct21 |
Jan22 |
Apr22 |
Jul22 |
Oct22 |
Jan23 |
Apr23 |
Jul23 |
Oct23 |
Jan24 |
| Beneish M-Score |
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-1.72 |
-1.81 |
-2.11 |
-2.25 |
-2.91 |
Competitive Comparison of Ciena's Beneish M-Score
For the Communication Equipment subindustry, Ciena'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.
Ciena's Beneish M-Score Distribution in the Hardware Industry
For the Hardware industry and Technology sector, Ciena's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Ciena's Beneish M-Score falls into.
Ciena 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 Ciena 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 * 0.769 | + | 0.528 * 0.9812 | + | 0.404 * 1.0692 | + | 0.892 * 1.0872 | + | 0.115 * 0.9724 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9565 | + | 4.679 * -0.076577 | - | 0.327 * 0.9388 |
| = | -2.93 |
* 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 (Jan24) TTM: | Last Year (Jan23) TTM: |
Total Receivables was €953 Mil.
Revenue was 952.617 + 1069.624 + 965.369 + 1032.981 = €4,021 Mil.
Gross Profit was 428.671 + 460.508 + 405.843 + 444.767 = €1,740 Mil.
Total Current Assets was €3,313 Mil.
Total Assets was €5,135 Mil.
Property, Plant and Equipment(Net PPE) was €290 Mil.
Depreciation, Depletion and Amortization(DDA) was €131 Mil.
Selling, General, & Admin. Expense(SGA) was €658 Mil.
Total Current Liabilities was €772 Mil.
Long-Term Debt & Capital Lease Obligation was €1,446 Mil.
Net Income was 45.484 + 86.365 + 26.879 + 52.58 = €211 Mil.
Non Operating Income was -8.719 + -17.455 + -6.22 + -9.918 = €-42 Mil.
Cash Flow from Operations was 244.258 + 185.112 + 7.854 + 209.588 = €647 Mil.
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Total Receivables was €1,140 Mil.
Revenue was 980.451 + 985.575 + 853.225 + 878.984 = €3,698 Mil.
Gross Profit was 423.118 + 440.101 + 334.986 + 372.049 = €1,570 Mil.
Total Current Assets was €3,492 Mil.
Total Assets was €5,264 Mil.
Property, Plant and Equipment(Net PPE) was €304 Mil.
Depreciation, Depletion and Amortization(DDA) was €132 Mil.
Selling, General, & Admin. Expense(SGA) was €632 Mil.
Total Current Liabilities was €945 Mil.
Long-Term Debt & Capital Lease Obligation was €1,478 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) |
| = | (952.628 / 4020.591) | / | (1139.526 / 3698.235) |
| = | 0.236937 | / | 0.308127 |
| | = | 0.769 |
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) |
| = | (1570.254 / 3698.235) | / | (1739.789 / 4020.591) |
| = | 0.424596 | / | 0.43272 |
| | = | 0.9812 |
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 - (3312.83 + 290.121) / 5134.567) | / | (1 - (3491.664 + 303.849) / 5264.077) |
| = | 0.298295 | / | 0.278978 |
| | = | 1.0692 |
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 |
| = | 4020.591 | / | 3698.235 |
| | = | 1.0872 |
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)) |
| = | (131.898 / (131.898 + 303.849)) | / | (131.127 / (131.127 + 290.121)) |
| = | 0.302694 | / | 0.311282 |
| | = | 0.9724 |
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) |
| = | (657.701 / 4020.591) | / | (632.496 / 3698.235) |
| = | 0.163583 | / | 0.171026 |
| | = | 0.9565 |
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) |
| = | ((1446.342 + 772.319) / 5134.567) | / | ((1478.118 + 944.899) / 5264.077) |
| = | 0.432103 | / | 0.460293 |
| | = | 0.9388 |
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 |
| = | (211.308 - -42.312 | - | 646.812) | / | 5134.567 |
| | = | -0.076577 |
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.
Ciena has a M-score of -2.93 suggests that the company is unlikely to be a manipulator.
Ciena (FRA:CIE1) Business Description
Traded in Other Exchanges
Address
7035 Ridge Road, Hanover, MD, USA, 21076
Ciena Corp is a network and technology company. It provides network hardware, software, and services that support the transport, switching, aggregation, service delivery, and management of video, data, and voice traffic on communications networks. It serves various industries such as communication services providers, web-scale providers, cable operators, government, and large enterprises world-wide. The business activities function through Networking Platforms; Platform Software and Services; Blue Planet Automation Software, and Global Services segments. Geographically, its presence is seen in the markets of the United States, Canada, the Caribbean, Latin America, Europe, the Middle East, Africa, the Asia Pacific, Japan, and India. The maximum revenue is generated from Americas.
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