This module uses fundamental data of Real Estate to approximate its Piotroski F score. Real Estate F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Real Estate E Commerce. 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 Real Estate financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Your Equity Center to better understand how to build diversified portfolios, which includes a position in Real Estate E Commerce. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in estimate.
Real
Piotroski F Score
Price To Sales Ratio
Ptb Ratio
Days Sales Outstanding
Book Value Per Share
Free Cash Flow Yield
Operating Cash Flow Per Share
Pb Ratio
Ev To Sales
Free Cash Flow Per Share
Roic
Net Income Per Share
Payables Turnover
Sales General And Administrative To Revenue
Cash Per Share
Pocfratio
Interest Coverage
Pfcf Ratio
Days Payables Outstanding
Income Quality
Roe
Ev To Operating Cash Flow
Pe Ratio
Return On Tangible Assets
Ev To Free Cash Flow
Earnings Yield
Net Debt To E B I T D A
Current Ratio
Tangible Book Value Per Share
Receivables Turnover
Graham Number
Shareholders Equity Per Share
Graham Net Net
Revenue Per Share
Interest Debt Per Share
Enterprise Value Over E B I T D A
Price Earnings Ratio
Operating Cycle
Price Book Value Ratio
Days Of Payables Outstanding
Price To Operating Cash Flows Ratio
Price To Free Cash Flows Ratio
Pretax Profit Margin
Operating Profit Margin
Effective Tax Rate
Company Equity Multiplier
Return On Capital Employed
Ebit Per Revenue
Quick Ratio
Net Income Per E B T
Cash Ratio
Cash Conversion Cycle
Operating Cash Flow Sales Ratio
Days Of Sales Outstanding
Price To Book Ratio
Price Cash Flow Ratio
Enterprise Value Multiple
Price Sales Ratio
Return On Assets
Asset Turnover
Net Profit Margin
Gross Profit Margin
Price Fair Value
Return On Equity
Change In Cash
Free Cash Flow
Change In Working Capital
Begin Period Cash Flow
Other Cashflows From Financing Activities
Other Non Cash Items
Dividends Paid
Total Cash From Operating Activities
Issuance Of Capital Stock
Net Income
Total Cash From Financing Activities
End Period Cash Flow
Total Assets
Other Current Liab
Total Current Liabilities
Total Stockholder Equity
Net Debt
Accounts Payable
Cash
Cash And Short Term Investments
Net Receivables
Common Stock Shares Outstanding
Short Term Investments
Liabilities And Stockholders Equity
Total Liab
Total Current Assets
Net Working Capital
Tax Provision
Net Interest Income
Depreciation And Amortization
Interest Expense
Selling General Administrative
Total Revenue
Gross Profit
Other Operating Expenses
Operating Income
Net Income From Continuing Ops
Ebit
Ebitda
Cost Of Revenue
Total Operating Expenses
Income Before Tax
Total Other Income Expense Net
Income Tax Expense
Probability Of Bankruptcy
At this time, Real Estate's Debt To Equity is very stable compared to the past year. As of the 30th of November 2024, Debt To Assets is likely to grow to 0.01, while Net Debt is likely to drop (3.6 M). At this time, Real Estate's Earnings Yield is very stable compared to the past year. As of the 30th of November 2024, Current Ratio is likely to grow to 2.61, while Price To Sales Ratio is likely to drop 9.19.
At this time, it appears that Real Estate'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..
The critical factor to consider when applying the Piotroski F Score to Real Estate is to make sure Real is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Real Estate'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 Real Estate'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 Real Estate's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Real Estate 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.
Book Value Per Share
15.43
At this time, Real Estate's Book Value Per Share is very stable compared to the past year.
About Real Estate Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Real Estate E Commerce's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Real Estate using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Real Estate E Commerce 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.
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 Real Estate 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 Real Estate will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to Real Estate could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace Real Estate 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 Real Estate - 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 Real Estate E Commerce to buy it.
The correlation of Real Estate 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 Real Estate moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if Real Estate E 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 Real Estate 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.
Real Estate financial ratios help investors to determine whether Real 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 Real with respect to the benefits of owning Real Estate security.