| CHIAX Fund | | | USD 6.38 0.01 0.16% |
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
Trending Equities to better understand how to build diversified portfolios, which includes a position in Credit Suisse Floating. Also, note that the market value of any mutual fund could be tightly coupled with the direction of predictive economic indicators such as
signals in nation.
Credit Suisse Floating Mutual Fund Z Score Analysis
Credit Suisse'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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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.
In accordance with the company's disclosures, Credit Suisse Floating has a Z Score of 0.0. This indicator is about the same for the Credit Suisse (New York, NY) average (which is currently at 0.0) family and about the same as
Bank Loan (which currently averages 0.0) category. This indicator is about the same for all United States funds average (which is currently at 0.0).
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Fund Asset Allocation for Credit Suisse
The fund invests most of its assets under management in various types of exotic instruments, with the rest of asset invested in stocks, cash and bonds. Asset allocation divides Credit Suisse's investment portfolio among different asset categories to balance risk and reward by investing in a diversified mix of instruments that align with the investor's goals, risk tolerance, and time horizon. Mutual funds, which pool money from multiple investors to buy a diversified portfolio of securities, use asset allocation strategies to manage the risk and return of their portfolios.
Mutual funds allocate their assets by investing in a diversified portfolio of securities, such as stocks, bonds, cryptocurrencies and cash. The specific mix of these securities is determined by the fund's investment objective and strategy. For example, a stock mutual fund may invest primarily in equities, while a bond mutual fund may invest mainly in fixed-income securities. The fund's manager, responsible for making investment decisions, will buy and sell securities in the fund's portfolio as market conditions and the fund's objectives change.
Credit Fundamentals
About Credit Suisse Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Credit Suisse Floating's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Credit Suisse using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of Credit Suisse Floating based on its fundamental data. In general, a quantitative approach, as applied to this mutual fund, 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.
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 Credit Suisse 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, Credit Suisse's short interest history, or implied volatility extrapolated from Credit Suisse options trading.
Pair Trading with Credit Suisse
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 Credit Suisse 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 Credit Suisse will appreciate offsetting losses from the drop in the long position's value.The ability to find closely correlated positions to Credit Suisse could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Credit Suisse 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 Credit Suisse - 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 Credit Suisse Floating to buy it.
The correlation of Credit Suisse 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 Credit Suisse moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Credit Suisse Floating 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 Credit Suisse 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, which includes a position in Credit Suisse Floating. Also, note that the market value of any mutual fund could be tightly coupled with the direction of predictive economic indicators such as
signals in nation.
Note that the Credit Suisse Floating information on this page should be used as a complementary analysis to other Credit Suisse's statistical models used to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the
Price Exposure Probability module to analyze equity upside and downside potential for a given time horizon across multiple markets.