DATA MODUL Market Capitalization vs. EBITDA
| DAM Stock | EUR 27.20 0.80 3.03% |
For DATA MODUL profitability analysis, we use financial ratios and fundamental drivers that measure the ability of DATA MODUL to generate income relative to revenue, assets, operating costs, and current equity. These fundamental indicators attest to how well DATA MODUL utilizes its assets to generate profit and value for its shareholders. The profitability module also shows relationships between DATA MODUL's most relevant fundamental drivers. It provides multiple suggestions of what could affect the performance of DATA MODUL over time as well as its relative position and ranking within its peers.
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DATA MODUL EBITDA vs. Market Capitalization Fundamental Analysis
Comparative valuation techniques use various fundamental indicators to help in determining DATA MODUL's current stock value. Our valuation model uses many indicators to compare DATA MODUL value to that of its competitors to determine the firm's financial worth. DATA MODUL is rated # 5 in market capitalization category among its peers. It is rated below average in ebitda category among its peers totaling about 0.08 of EBITDA per Market Capitalization. The ratio of Market Capitalization to EBITDA for DATA MODUL is roughly 12.36 . The reason why the comparable model can be used in almost all circumstances is due to the vast number of multiples that can be utilized, such as the price-to-earnings (P/E), price-to-book (P/B), price-to-sales (P/S), price-to-cash flow (P/CF), and many others. The P/E ratio is the most commonly used of these ratios because it focuses on the DATA MODUL's earnings, one of the primary drivers of an investment's value.DATA Market Capitalization vs. Competition
DATA MODUL is rated # 5 in market capitalization category among its peers. Market capitalization of Other industry is currently estimated at about 46.69 Billion. DATA MODUL adds roughly 218.62 Million in market capitalization claiming only tiny portion of all equities under Other industry.
DATA EBITDA vs. Market Capitalization
Market Capitalization is the total market value of a company's equity. It is one of many ways to value a company and is calculated by multiplying the price of the stock by the number of shares issued. If a firm has one type of stock its market capitalization will be the current market share price multiplied by the number of shares. However, if a company has multiple types of equities then the market cap will be the total of the market caps of the different types of shares.
DATA MODUL |
| = | 218.62 M |
In most publications or references market cap is broken down into the mega-cap, large-cap, mid-cap, small-cap, micro-cap, and nano-cap. Market Cap is a measurement of business as total market value of all of the outstanding shares at a given time, and can be used to compare different companies based on their size.
EBITDA stands for earnings before interest, taxes, depreciation, and amortization. It is a measure of a company operating cash flow based on data from the company income statement and is a very good way to compare companies within industries or across different sectors. However, unlike Operating Cash Flow, EBITDA does not include the effects of changes in working capital.
DATA MODUL |
| = | 17.69 M |
In a nutshell, EBITDA is calculated by adding back each of the excluded items to the post-tax profit, and can be used to compare companies with very different capital structures.
DATA EBITDA Comparison
DATA MODUL is currently under evaluation in ebitda category among its peers.
DATA Profitability Driver Comparison
Profitability drivers are factors that can directly affect your investment outlook on DATA MODUL. Investors often realize that things won't turn out the way they predict. There are maybe way too many unforeseen events and contingencies during the holding period of DATA MODUL position where the market behavior may be hard to predict, tax policy changes, gold or oil price hikes, calamities change, and many others. The question is, are you prepared for these unexpected events? Although some of these situations are obviously beyond your control, you can still follow the important profit indicators to know where you should focus on when things like this occur. Below are some of the DATA MODUL's important profitability drivers and their relationship over time.
Use DATA MODUL in pair-trading
One of the main advantages of trading using pair correlations is that every trade hedges away some risk. Because there are two separate transactions required, even if DATA MODUL position performs unexpectedly, the other equity can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in DATA MODUL will appreciate offsetting losses from the drop in the long position's value.DATA MODUL Pair Trading
DATA MODUL Pair Trading Analysis
The ability to find closely correlated positions to DATA MODUL could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace DATA MODUL when you sell it. If you don't do this, your portfolio allocation will be skewed against your target asset allocation. So, investors can't just sell and buy back DATA MODUL - that would be a violation of the tax code under the "wash sale" rule, and this is why you need to find a similar enough asset and use the proceeds from selling DATA MODUL to buy it.
The correlation of DATA MODUL is a statistical measure of how it moves in relation to other instruments. This measure is expressed in what is known as the correlation coefficient, which ranges between -1 and +1. A perfect positive correlation (i.e., a correlation coefficient of +1) implies that as DATA MODUL moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if DATA MODUL moves in either direction, the perfectly negatively correlated security will move in the opposite direction. If the correlation is 0, the equities are not correlated; they are entirely random. A correlation greater than 0.8 is generally described as strong, whereas a correlation less than 0.5 is generally considered weak.
Correlation analysis and pair trading evaluation for DATA MODUL can also be used as hedging techniques within a particular sector or industry or even over random equities to generate a better risk-adjusted return on your portfolios.Use Investing Themes to Complement your DATA MODUL position
In addition to having DATA MODUL in your portfolios, you can quickly add positions using our predefined set of ideas and optimize them against your very unique investing style. A single investing idea is a collection of funds, stocks, ETFs, or cryptocurrencies that are programmatically selected from a pull of investment themes. After you determine your investment opportunity, you can then find an optimal portfolio that will maximize potential returns on the chosen idea or minimize its exposure to market volatility.Did You Try This Idea?
Run Large Cap ETFs Thematic Idea Now
Large Cap ETFs
ETF themes focus on helping investors to gain exposure to a broad range of assets, diversify, and lower overall costs. The Large Cap ETFs theme has 714 constituents at this time.
You can either use a buy-and-hold strategy to lock in the entire theme or actively trade it to take advantage of the short-term price volatility of individual constituents. Macroaxis can help you discover thousands of investment opportunities in different asset classes. In addition, you can partner with us for reliable portfolio optimization as you plan to utilize Large Cap ETFs Theme or any other thematic opportunities.
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Additional Tools for DATA Stock Analysis
When running DATA MODUL's price analysis, check to measure DATA MODUL's market volatility, profitability, liquidity, solvency, efficiency, growth potential, financial leverage, and other vital indicators. We have many different tools that can be utilized to determine how healthy DATA MODUL is operating at the current time. Most of DATA MODUL's value examination focuses on studying past and present price action to predict the probability of DATA MODUL's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move DATA MODUL's price. Additionally, you may evaluate how the addition of DATA MODUL to your portfolios can decrease your overall portfolio volatility.