This module uses fundamental data of Ming Shing to approximate its Piotroski F score. Ming Shing F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Ming Shing Group. 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 Ming Shing financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Ming Shing Altman Z Score, Ming Shing Correlation, Ming Shing Valuation, as well as analyze Ming Shing Alpha and Beta and Ming Shing Hype Analysis.
Ming
Piotroski F Score
Investments
Change In Cash
Free Cash Flow
Change In Working Capital
Begin Period Cash Flow
Depreciation
Other Non Cash Items
Total Cash From Operating Activities
Change To Account Receivables
Net Income
Total Cash From Financing Activities
End Period Cash Flow
Total Assets
Total Current Liabilities
Total Stockholder Equity
Property Plant And Equipment Net
Net Debt
Retained Earnings
Accounts Payable
Cash
Non Current Assets Total
Non Currrent Assets Other
Long Term Debt
Net Receivables
Non Current Liabilities Total
Capital Lease Obligations
Total Liab
Net Invested Capital
Property Plant And Equipment Gross
Short Long Term Debt
Total Current Assets
Net Working Capital
Tax Provision
Net Interest Income
Interest Expense
Selling General Administrative
Total Revenue
Gross Profit
Operating Income
Net Income From Continuing Ops
Cost Of Revenue
Total Operating Expenses
Reconciled Depreciation
Income Before Tax
Total Other Income Expense Net
Probability Of Bankruptcy
Net Debt is likely to drop to about 3.9 M in 2024. Long Term Debt is likely to drop to about 1.8 M in 2024.
At this time, it appears that Ming Shing'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..
The critical factor to consider when applying the Piotroski F Score to Ming Shing is to make sure Ming is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Ming Shing'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 Ming Shing's financial numbers are properly reported.
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 Ming Shing's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Ming Shing in a much-optimized way.
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.
Net Debt
3.93 Million
At this time, Ming Shing's Net Debt is fairly stable compared to the past year.
About Ming Shing Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Ming Shing Group's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Ming Shing using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Ming Shing Group 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.
Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.
When running Ming Shing's price analysis, check to measure Ming Shing'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 Ming Shing is operating at the current time. Most of Ming Shing's value examination focuses on studying past and present price action to predict the probability of Ming Shing's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Ming Shing's price. Additionally, you may evaluate how the addition of Ming Shing to your portfolios can decrease your overall portfolio volatility.