Computer Sciences Corp Stock Z Score

Altman Z Score is one of the simplest fundamental models to determine how likely your company is to fail. The module uses available fundamental data of a given equity to approximate the Altman Z score. Altman Z Score is determined by evaluating five fundamental price points available from the company's current public disclosure documents. 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.
  

Computer Sciences Corp Company Z Score Analysis

Computer Sciences' Z-Score is a simple linear, multi-factor model that measures the financial health and economic stability of a company. The score is used to predict the probability of a firm going into bankruptcy within next 24 months or two fiscal years from the day stated on the accounting statements used to calculate it. The model uses five fundamental business ratios that are weighted according to algorithm of Professor Edward Altman who developed it in the late 1960s at New York University..

Z Score

 = 

Sum Of

5 Factors

More About Z Score | All Equity Analysis

Current Computer Sciences Z Score

    
  3.4  
Most of Computer Sciences' fundamental indicators, such as Z Score, 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.

First Factor

 = 

1.2 * (

Working Capital

/

Total Assets )

Second Factor

 = 

1.4 * (

Retained Earnings

/

Total Assets )

Thrid Factor

 = 

3.3 * (

EBITAD

/

Total Assets )

Fouth Factor

 = 

0.6 * (

Market Value of Equity

/

Total Liabilities )

Fifth Factor

 = 

0.99 * (

Revenue

/

Total Assets )

To calculate a Z-Score, one would need to know a company's current working capital, its total assets and liabilities, and the amount of its latest earnings as well as earnings before interest and tax. Z-Scores can be used to compare the odds of bankruptcy of companies in a similar line of business or firms operating in the same industry. Companies with Z-Scores above 3.1 are generally considered to be stable and healthy with a low probability of bankruptcy. Scores that fall between 1.8 and 3.1 lie in a so-called 'grey area,' with scores of less than 1 indicating the highest probability of distress. Z Score is a used widely measure by financial auditors, accountants, money managers, loan processors, wealth advisers, and day traders. In the last 25 years, many financial models that utilize z-scores proved it to be successful as a predictor of corporate bankruptcy.
Competition
In accordance with the company's disclosures, Computer Sciences Corp has a Z Score of 3.4. This is 32.41% lower than that of the sector and 66.17% lower than that of the Z Score industry. The z score for all United States stocks is 61.01% higher than that of the company.

Computer Z Score 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 Z Score 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 z score 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 Citigroup could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Citigroup 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 Citigroup - 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 Citigroup to buy it.
The correlation of Citigroup 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 Citigroup moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Citigroup 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 Citigroup 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 Sign In To Macroaxis module to sign in to explore Macroaxis' wealth optimization platform and fintech modules.

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.
Price Exposure Probability
Analyze equity upside and downside potential for a given time horizon across multiple markets
Correlation Analysis
Reduce portfolio risk simply by holding instruments which are not perfectly correlated
ETFs
Find actively traded Exchange Traded Funds (ETF) from around the world
Portfolio Backtesting
Avoid under-diversification and over-optimization by backtesting your portfolios
Premium Stories
Follow Macroaxis premium stories from verified contributors across different equity types, categories and coverage scope
Insider Screener
Find insiders across different sectors to evaluate their impact on performance
Price Transformation
Use Price Transformation models to analyze the depth of different equity instruments across global markets
Risk-Return Analysis
View associations between returns expected from investment and the risk you assume
Instant Ratings
Determine any equity ratings based on digital recommendations. Macroaxis instant equity ratings are based on combination of fundamental analysis and risk-adjusted market performance