This module uses fundamental data of Decision Diagnostics to approximate its Piotroski F score. Decision Diagnostics F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Decision Diagnostics. 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 Decision Diagnostics financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Decision Diagnostics Altman Z Score, Decision Diagnostics Correlation, Decision Diagnostics Valuation, as well as analyze Decision Diagnostics Alpha and Beta and Decision Diagnostics Hype Analysis.
At this time, Decision Diagnostics' Long Term Debt is very stable compared to the past year. As of the 26th of November 2024, Debt To Equity is likely to grow to 5.72, while Short and Long Term Debt is likely to drop about 1.9 M. At this time, Decision Diagnostics' Debt To Equity is very stable compared to the past year.
At this time, it appears that Decision Diagnostics' Piotroski F Score is Frail. 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..
The critical factor to consider when applying the Piotroski F Score to Decision Diagnostics is to make sure Decision is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Decision Diagnostics' 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 Decision Diagnostics' financial numbers are properly reported.
One of the toughest challenges investors face today is learning how to quickly synthesize historical financial statements and information provided by the company, SEC reporting, and various external parties in order to project the various growth rates. Understanding the correlation between Decision Diagnostics' different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Decision Diagnostics in a much-optimized way.
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.
Book Value Per Share
0.001982
At this time, Decision Diagnostics' Book Value Per Share is very stable compared to the past year.
Decision Diagnostics Current Valuation Drivers
We derive many important indicators used in calculating different scores of Decision Diagnostics from analyzing Decision Diagnostics' financial statements. These drivers represent accounts that assess Decision Diagnostics' ability to generate profits relative to its revenue, operating costs, and shareholders' equity. Below are some of Decision Diagnostics' important valuation drivers and their relationship over time.
The Macroaxis Fundamental Analysis modules help investors analyze Decision Diagnostics's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Decision Diagnostics using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Decision Diagnostics based on its fundamental data. In general, a quantitative approach, as applied to this company, focuses on analyzing financial statements comparatively, whereas a qaualitative method uses data that is important to a company's growth but cannot be measured and presented in a numerical way.
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 Decision Diagnostics 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 Decision Diagnostics will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Decision Diagnostics could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Decision Diagnostics 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 Decision Diagnostics - 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 Decision Diagnostics to buy it.
The correlation of Decision Diagnostics 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 Decision Diagnostics moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Decision Diagnostics 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 Decision Diagnostics 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.
When determining whether Decision Diagnostics offers a strong return on investment in its stock, a comprehensive analysis is essential. The process typically begins with a thorough review of Decision Diagnostics' financial statements, including income statements, balance sheets, and cash flow statements, to assess its financial health. Key financial ratios are used to gauge profitability, efficiency, and growth potential of Decision Diagnostics Stock. Outlined below are crucial reports that will aid in making a well-informed decision on Decision Diagnostics Stock:
To learn how to invest in Decision Stock, please use our How to Invest in Decision Diagnostics guide.You can also try the Bonds Directory module to find actively traded corporate debentures issued by US companies.
Is Health Care Technology space expected to grow? Or is there an opportunity to expand the business' product line in the future? Factors like these will boost the valuation of Decision Diagnostics. If investors know Decision will grow in the future, the company's valuation will be higher. The financial industry is built on trying to define current growth potential and future valuation accurately. All the valuation information about Decision Diagnostics listed above have to be considered, but the key to understanding future value is determining which factors weigh more heavily than others.
Earnings Share
(0.02)
Revenue Per Share
0.006
Quarterly Revenue Growth
(0)
Return On Assets
(0.21)
Return On Equity
(81.61)
The market value of Decision Diagnostics is measured differently than its book value, which is the value of Decision that is recorded on the company's balance sheet. Investors also form their own opinion of Decision Diagnostics' value that differs from its market value or its book value, called intrinsic value, which is Decision Diagnostics' true underlying value. Investors use various methods to calculate intrinsic value and buy a stock when its market value falls below its intrinsic value. Because Decision Diagnostics' market value can be influenced by many factors that don't directly affect Decision Diagnostics' underlying business (such as a pandemic or basic market pessimism), market value can vary widely from intrinsic value.
Please note, there is a significant difference between Decision Diagnostics' value and its price as these two are different measures arrived at by different means. Investors typically determine if Decision Diagnostics is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, Decision Diagnostics' price is the amount at which it trades on the open market and represents the number that a seller and buyer find agreeable to each party.