Computer Sciences Corp Stock Return On Equity

Computer Sciences Corp fundamentals help investors to digest information that contributes to Computer Sciences' financial success or failures. It also enables traders to predict the movement of Computer Stock. The fundamental analysis module provides a way to measure Computer Sciences' intrinsic value by examining its available economic and financial indicators, including the cash flow records, the balance sheet account changes, the income statement patterns, and various microeconomic indicators and financial ratios related to Computer Sciences stock.
  
This module does not cover all equities due to inconsistencies in global equity categorizations. Continue to Equity Screeners to view more equity screening tools.

Computer Sciences Corp Company Return On Equity Analysis

Computer Sciences' Return on Equity or ROE tells company stockholders how effectually their money is being utilized or reinvested. It is a useful ratio when analyzing company profitability or the management effectiveness given the capital invested by the shareholders. ROE shows how efficiently a company utilizes investments to generate income.

Return On Equity

 = 

Net Income

Total Equity

More About Return On Equity | All Equity Analysis

Current Computer Sciences Return On Equity

    
  -76.21  
Most of Computer Sciences' fundamental indicators, such as Return On Equity, are part of a valuation analysis module that helps investors searching for stocks that are currently trading at higher or lower prices than their real value. If the real value is higher than the market price, Computer Sciences Corp is considered to be undervalued, and we provide a buy recommendation. Otherwise, we render a sell signal.
For most industries, Return on Equity between 10% and 30% are considered desirable to provide dividends to owners and have funds for the future growth of the company. Investors should be very careful using ROE as the only efficiency indicator because ROE can be high if a company is heavily leveraged.
Competition
Based on the latest financial disclosure, Computer Sciences Corp has a Return On Equity of -76.2087. This is 7956.57% lower than that of the sector and notably lower than that of the Return On Equity industry. The return on equity for all United States stocks is notably higher than that of the company.

Computer Return On Equity Peer Comparison

Stock peer comparison is one of the most widely used and accepted methods of equity analyses. It analyses Computer Sciences' direct or indirect competition against its Return On Equity to detect undervalued stocks with similar characteristics or determine the stocks which would be a good addition to a portfolio. Peer analysis of Computer Sciences could also be used in its relative valuation, which is a method of valuing Computer Sciences by comparing valuation metrics of similar companies.
Computer Sciences is currently under evaluation in return on equity category among related companies.

Computer Fundamentals

Pair Trading with Computer Sciences

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 Computer Sciences 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 Computer Sciences will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Helmerich could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Helmerich 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 Helmerich - 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 Helmerich and Payne to buy it.
The correlation of Helmerich 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 Helmerich moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Helmerich and Payne 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 Helmerich 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.
Pair CorrelationCorrelation Matching
Check out Trending Equities to better understand how to build diversified portfolios. Also, note that the market value of any company could be tightly coupled with the direction of predictive economic indicators such as signals in state.
You can also try the Stocks Directory module to find actively traded stocks across global markets.

Other Consideration for investing in Computer Stock

If you are still planning to invest in Computer Sciences Corp check if it may still be traded through OTC markets such as Pink Sheets or OTC Bulletin Board. You may also purchase it directly from the company, but this is not always possible and may require contacting the company directly. Please note that delisted stocks are often considered to be more risky investments, as they are no longer subject to the same regulatory and reporting requirements as listed stocks. Therefore, it is essential to carefully research the Computer Sciences' history and understand the potential risks before investing.
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