| CNET Stock | | | USD 1.66 0.07 4.40% |
This module uses fundamental data of ZW Data to approximate its Piotroski F score. ZW Data F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of ZW Data Action. 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 ZW Data financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out
ZW Data Altman Z Score,
ZW Data Correlation,
ZW Data Valuation, as well as analyze
ZW Data Alpha and Beta and
ZW Data Hype Analysis.
At this time, ZW Data's
Long Term Debt is comparatively stable compared to the past year.
Short and Long Term Debt is likely to gain to about 735.5
K in 2024, whereas
Short Term Debt is likely to drop slightly above 116.8
K in 2024. At this time, ZW Data's
PTB Ratio is comparatively stable compared to the past year.
PB Ratio is likely to gain to 4.01 in 2024, whereas
Days Sales Outstanding is likely to drop 9.57 in 2024.
At this time, it appears that ZW Data's Piotroski F Score is Poor. 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..
4.0
Piotroski F Score - Poor
| Change in Return on Assets | |
| Cash Flow Return on Assets | |
| Current Quality of Earnings (accrual) | |
| Long Term Debt Over Assets Change | Higher Leverage| Focus | |
| Change In Outstending Shares | |
ZW Data Piotroski F Score Drivers
The critical factor to consider when applying the Piotroski F Score to ZW Data is to make sure CNET is not a subject of accounting manipulations and runs a healthy internal audit department. So, if ZW Data'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 ZW Data's financial numbers are properly reported.
ZW Data Action F Score Driver Matrix
One of the toughest challenges investors face today is learning how to quickly synthesize historical
financial statements and information provided by the company, SEC reporting, and various external parties in order to project the various growth rates. Understanding the correlation between ZW Data's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards ZW Data in a much-optimized way.
Click cells to compare fundamentals
About ZW Data 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 ZW Data Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze ZW Data Action's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of ZW Data using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at
the intrinsic value of ZW Data Action 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.
Please read more on our
fundamental analysis page.
Build portfolios using Macroaxis predefined set of investing ideas. Many of Macroaxis investing ideas can easily outperform a given market. Ideas can also be optimized per your risk profile before portfolio origination is invoked. Macroaxis thematic optimization helps investors identify companies most likely to benefit from changes or shifts in various micro-economic or local macro-level trends. Originating optimal thematic portfolios involves aligning investors' personal views, ideas, and beliefs with their actual investments.
Additional Tools for CNET Stock Analysis
When running ZW Data's price analysis, check to
measure ZW Data'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 ZW Data is operating at the current time. Most of ZW Data's value examination focuses on studying past and present price action to
predict the probability of ZW Data's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move ZW Data's price. Additionally, you may evaluate how the addition of ZW Data to your portfolios can decrease your overall portfolio volatility.