Mobile health Network Solutions Company Z Score Analysis
Mobile Health's 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..
| First Factor | = | 1.2 * ( | Working Capital | / | Total Assets ) |
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| Second Factor | = | 1.4 * ( | Retained Earnings | / | Total Assets ) |
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| Thrid Factor | = | 3.3 * ( | EBITAD | / | Total Assets ) |
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| Fouth Factor | = | 0.6 * ( | Market Value of Equity | / | Total Liabilities ) |
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| Fifth Factor | = | 0.99 * ( | Revenue | / | Total Assets ) |
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Mobile Z Score Driver Correlations
Understanding the fundamental principles of building solid financial models for Mobile Health is extremely important. It helps to project a fair market value of Mobile Stock properly, considering its historical
fundamentals such as Z Score. Since Mobile Health's main accounts across its financial reports are all linked and dependent on each other, it is essential to analyze all possible correlations between related accounts. However, instead of reviewing all of Mobile Health's historical
financial statements, investors can examine the correlated drivers to determine its overall health. This can be effectively done using a conventional correlation matrix of Mobile Health's interrelated accounts and indicators.
Click cells to compare fundamentals
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.
Based on the company's disclosures, Mobile health Network Solutions has a Z Score of 0.0. This is 100.0% lower than that of the Health Care Providers & Services sector and 100.0% lower than that of the
Health Care industry. The z score for all United States stocks is 100.0% higher than that of the company.
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Mobile Fundamentals
About Mobile Health Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Mobile health Network Solutions's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Mobile Health using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of Mobile health Network Solutions 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.
Pair Trading with Mobile Health
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 Mobile Health 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 Mobile Health will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Mobile Health could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Mobile Health 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 Mobile Health - 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 Mobile health Network Solutions to buy it.
The correlation of Mobile Health 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 Mobile Health moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Mobile health Network 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 Mobile Health 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.
Additional Tools for Mobile Stock Analysis
When running Mobile Health's price analysis, check to
measure Mobile Health'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 Mobile Health is operating at the current time. Most of Mobile Health's value examination focuses on studying past and present price action to
predict the probability of Mobile Health's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Mobile Health's price. Additionally, you may evaluate how the addition of Mobile Health to your portfolios can decrease your overall portfolio volatility.