Morgan Stanley Etf 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 Investing Opportunities to better understand how to build diversified portfolios. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in metropolitan statistical area.
  

Morgan Stanley ETF Z Score Analysis

Morgan Stanley'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..

Z Score

 = 

Sum Of

5 Factors

More About Z Score | All Equity Analysis

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

According to the company's disclosures, Morgan Stanley has a Z Score of 0.0. This indicator is about the same for the Market Vectors average (which is currently at 0.0) family and about the same as Trading--Miscellaneous (which currently averages 0.0) category. This indicator is about the same for all United States etfs average (which is currently at 0.0).

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Morgan Fundamentals

Pair Trading with Morgan Stanley

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 Morgan Stanley 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 Morgan Stanley will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Dover could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Dover 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 Dover - 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 Dover to buy it.
The correlation of Dover 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 Dover moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Dover 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 Dover 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 Investing Opportunities to better understand how to build diversified portfolios. Also, note that the market value of any etf could be closely tied with the direction of predictive economic indicators such as signals in metropolitan statistical area.
You can also try the Portfolio Analyzer module to portfolio analysis module that provides access to portfolio diagnostics and optimization engine.

Other Tools for Morgan Etf

When running Morgan Stanley's price analysis, check to measure Morgan Stanley'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 Morgan Stanley is operating at the current time. Most of Morgan Stanley's value examination focuses on studying past and present price action to predict the probability of Morgan Stanley's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Morgan Stanley's price. Additionally, you may evaluate how the addition of Morgan Stanley to your portfolios can decrease your overall portfolio volatility.
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