| EFUT Etf | | | 25.39 0.55 2.12% |
This module uses fundamental data of EFuture Information to approximate its Piotroski F score. EFuture Information F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of eFuture Information Technology. 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 EFuture Information financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out
EFuture Information Altman Z Score,
EFuture Information Correlation,
Portfolio Optimization, as well as analyze
EFuture Information Alpha and Beta and
EFuture Information Hype Analysis.
At this time, it appears that EFuture Information's Piotroski F Score is Inapplicable. 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..
0.0
Piotroski F Score - Inapplicable
| Change in Return on Assets | |
| Cash Flow Return on Assets | |
| Current Quality of Earnings (accrual) | |
| Long Term Debt Over Assets Change | |
| Change In Outstending Shares | |
EFuture Information Piotroski F Score Drivers
The critical factor to consider when applying the Piotroski F Score to EFuture Information is to make sure EFuture is not a subject of accounting manipulations and runs a healthy internal audit department. So, if EFuture Information's 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 EFuture Information's financial numbers are properly reported.
About EFuture Information Piotroski F Score
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.
About EFuture Information Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze eFuture Information Technology's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of EFuture Information using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of eFuture Information Technology based on its fundamental data. In general, a quantitative approach, as applied to this etf, 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.
Please read more on our
fundamental analysis page.
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 EFuture Information 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, EFuture Information's short interest history, or implied volatility extrapolated from EFuture Information options trading.
Pair Trading with EFuture Information
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 EFuture Information 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 EFuture Information will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to EFuture Information could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace EFuture Information 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 EFuture Information - 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 eFuture Information Technology to buy it.
The correlation of EFuture Information 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 EFuture Information moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if eFuture Information 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 EFuture Information 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.
The market value of eFuture Information is measured differently than its book value, which is the value of EFuture that is recorded on the company's balance sheet. Investors also form their own opinion of EFuture Information's value that differs from its market value or its book value, called intrinsic value, which is EFuture Information's 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 EFuture Information's market value can be influenced by many factors that don't directly affect EFuture Information's 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 EFuture Information's value and its price as these two are different measures arrived at by different means. Investors typically determine if EFuture Information is a good investment by looking at such factors as earnings, sales, fundamental and technical indicators, competition as well as analyst projections. However, EFuture Information's 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.