Computer Sciences Corp Stock Piotroski F Score
This module uses fundamental data of Computer Sciences to approximate its Piotroski F score. Computer Sciences F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Computer Sciences Corp. These three categories are profitability, efficiency, and funding. Some research analysts and sophisticated value traders use Piotroski F Score to find opportunities outside of the conventional market and financial statement analysis.They believe that some of the new information about Computer Sciences financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. 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 |
At this time, it appears that Computer Sciences' Piotroski F Score is Unavailable. Although some professional money managers and academia have recently criticized Piotroski F-Score model, we still consider it an effective method of predicting the state of the financial strength of any organization that is not predisposed to accounting gimmicks and manipulations. Using this score on the criteria to originate an efficient long-term portfolio can help investors filter out the purely speculative stocks or equities playing fundamental games by manipulating their earnings..
0.0
Piotroski F Score - Unavailable
| Current Return On Assets | N/A |
| Change in Return on Assets | N/A |
| Cash Flow Return on Assets | N/A |
| Current Quality of Earnings (accrual) | N/A |
| Asset Turnover Growth | N/A |
| Current Ratio Change | N/A |
| Long Term Debt Over Assets Change | N/A |
| Change In Outstending Shares | N/A |
| Change in Gross Margin | N/A |
Computer Sciences Piotroski F Score Drivers
The critical factor to consider when applying the Piotroski F Score to Computer Sciences is to make sure Computer is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Computer Sciences' auditors report directly to the board (not management), the managers will be reluctant to manipulate simply due to the fear of punishment. On the other hand, the auditors will be free to investigate the ledgers properly because they know that the board has their back. Below are the main accounts that are used in the Piotroski F Score model. By analyzing the historical trends of the mains drivers, investors can determine if Computer Sciences' financial numbers are properly reported.
About Computer Sciences Piotroski F Score
F-Score is one of many stock grading techniques developed by Joseph Piotroski, a professor of accounting at the Stanford University Graduate School of Business. It was published in 2002 under the paper titled Value Investing: The Use of Historical Financial Statement Information to Separate Winners from Losers. Piotroski F Score is based on binary analysis strategy in which stocks are given one point for passing 9 very simple fundamental tests, and zero point otherwise. According to Mr. Piotroski's analysis, his F-Score binary model can help to predict the performance of low price-to-book stocks.Some investors attempt to determine whether the market's mood is bullish or bearish by monitoring changes in market sentiment. Unlike more traditional methods such as technical analysis, investor sentiment usually refers to the aggregate attitude towards Computer Sciences in the overall investment community. So, suppose investors can accurately measure the market's sentiment. In that case, they can use it for their benefit. For example, some tools to gauge market sentiment could be utilized using contrarian indexes, Computer Sciences' short interest history, or implied volatility extrapolated from Computer Sciences options trading.
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 Newell Brands could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Newell Brands 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 Newell Brands - 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 Newell Brands to buy it.
The correlation of Newell Brands 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 Newell Brands moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Newell Brands 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 Newell Brands 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.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 Economic Indicators module to top statistical indicators that provide insights into how an economy is performing.
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.
| USA ETFs Find actively traded Exchange Traded Funds (ETF) in USA | |
| Positions Ratings Determine portfolio positions ratings based on digital equity recommendations. Macroaxis instant position ratings are based on combination of fundamental analysis and risk-adjusted market performance | |
| Transaction History View history of all your transactions and understand their impact on performance | |
| Portfolio Diagnostics Use generated alerts and portfolio events aggregator to diagnose current holdings | |
| Options Analysis Analyze and evaluate options and option chains as a potential hedge for your portfolios |