| SPEL Stock | | | 38.06 1.17 2.98% |
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
World Market Map to better understand how to build diversified portfolios, which includes a position in Synthetic Products Enterprises. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as
signals in board of governors.
Synthetic Products Enterprises Company Z Score Analysis
Synthetic Products' 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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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, Synthetic Products Enterprises has a Z Score of 0.0. This is 100.0% lower than that of the Basic Materials sector and 100.0% lower than that of the
Chemicals industry. The z score for all Pakistan stocks is 100.0% higher than that of the company.
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About Synthetic Products Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Synthetic Products Enterprises's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Synthetic Products using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of Synthetic Products Enterprises 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 Synthetic Products
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 Synthetic Products 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 Synthetic Products will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Synthetic Products could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Synthetic Products 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 Synthetic Products - 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 Synthetic Products Enterprises to buy it.
The correlation of Synthetic Products 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 Synthetic Products moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Synthetic Products 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 Synthetic Products 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.
Other Information on Investing in Synthetic Stock
Synthetic Products financial ratios help investors to determine whether Synthetic Stock is cheap or expensive when compared to a particular measure, such as profits or enterprise value. In other words, they help investors to determine the cost of investment in Synthetic with respect to the benefits of owning Synthetic Products security.