This module uses fundamental data of Fobi AI to approximate its Piotroski F score. Fobi AI F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of Fobi AI. 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 Fobi AI financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out Investing Opportunities to better understand how to build diversified portfolios, which includes a position in Fobi AI. Also, note that the market value of any company could be closely tied with the direction of predictive economic indicators such as signals in gross domestic product.
Fobi
Piotroski F Score
Market Cap
Enterprise Value
Price To Sales Ratio
Ptb Ratio
Days Sales Outstanding
Book Value Per Share
Free Cash Flow Yield
Operating Cash Flow Per Share
Average Payables
Stock Based Compensation To Revenue
Capex To Depreciation
Pb Ratio
Ev To Sales
Free Cash Flow Per Share
Roic
Net Income Per Share
Payables Turnover
Sales General And Administrative To Revenue
Research And Ddevelopement To Revenue
Capex To Revenue
Cash Per Share
Pocfratio
Interest Coverage
Capex To Operating Cash Flow
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
Intangibles To Total Assets
Net Debt To E B I T D A
Current Ratio
Tangible Book Value Per Share
Receivables Turnover
Graham Number
Shareholders Equity Per Share
Debt To Equity
Capex Per Share
Graham Net Net
Average Receivables
Revenue Per Share
Interest Debt Per Share
Debt To Assets
Enterprise Value Over E B I T D A
Short Term Coverage Ratios
Price Earnings Ratio
Operating Cycle
Price Book Value Ratio
Price Earnings To Growth Ratio
Days Of Payables Outstanding
Price To Operating Cash Flows Ratio
Price To Free Cash Flows Ratio
Pretax Profit Margin
Ebt Per Ebit
Operating Profit Margin
Effective Tax Rate
Company Equity Multiplier
Total Debt To Capitalization
Return On Capital Employed
Debt Equity Ratio
Ebit Per Revenue
Quick Ratio
Dividend Paid And Capex Coverage Ratio
Cash Ratio
Cash Conversion Cycle
Operating Cash Flow Sales Ratio
Days Of Sales Outstanding
Free Cash Flow Operating Cash Flow Ratio
Cash Flow Coverage Ratios
Price To Book Ratio
Fixed Asset Turnover
Capital Expenditure Coverage Ratio
Price Cash Flow Ratio
Enterprise Value Multiple
Debt Ratio
Cash Flow To Debt Ratio
Price Sales Ratio
Return On Assets
Asset Turnover
Net Profit Margin
Gross Profit Margin
Price Fair Value
Return On Equity
Change In Cash
Net Borrowings
Free Cash Flow
Change In Working Capital
Begin Period Cash Flow
Total Cashflows From Investing Activities
Other Cashflows From Financing Activities
Depreciation
Capital Expenditures
Total Cash From Operating Activities
Change To Account Receivables
Change To Operating Activities
Net Income
Total Cash From Financing Activities
End Period Cash Flow
Change To Netincome
Change To Liabilities
Investments
Stock Based Compensation
Other Non Cash Items
Issuance Of Capital Stock
Total Assets
Other Current Liab
Total Current Liabilities
Total Stockholder Equity
Net Tangible Assets
Retained Earnings
Accounts Payable
Cash
Non Current Assets Total
Net Receivables
Common Stock Shares Outstanding
Non Current Liabilities Total
Total Liab
Net Invested Capital
Total Current Assets
Net Working Capital
Common Stock
Property Plant Equipment
Other Stockholder Equity
Short Long Term Debt
Capital Stock
Property Plant And Equipment Net
Capital Lease Obligations
Property Plant And Equipment Gross
Good Will
Short Term Investments
Intangible Assets
Interest Expense
Selling General Administrative
Total Revenue
Operating Income
Net Income From Continuing Ops
Ebit
Total Operating Expenses
Income Before Tax
Total Other Income Expense Net
Net Income Applicable To Common Shares
Research Development
Reconciled Depreciation
Net Interest Income
Interest Income
Gross Profit
Ebitda
Cost Of Revenue
Tax Provision
Probability Of Bankruptcy
At this time, Fobi AI's Net Debt To EBITDA is fairly stable compared to the past year. Debt To Equity is likely to climb to 6.38 in 2024, whereas Long Term Debt is likely to drop slightly above 234.4 K in 2024. At this time, Fobi AI's Average Payables is fairly stable compared to the past year. Capex To Depreciation is likely to climb to 504.84 in 2024, despite the fact that PTB Ratio is likely to grow to (11.48).
At this time, it appears that Fobi AI'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 Fobi AI is to make sure Fobi is not a subject of accounting manipulations and runs a healthy internal audit department. So, if Fobi AI'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 Fobi AI'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 Fobi AI's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards Fobi AI 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
(0.0236)
At this time, Fobi AI's Book Value Per Share is fairly stable compared to the past year.
About Fobi AI Fundamental Analysis
The Macroaxis Fundamental Analysis modules help investors analyze Fobi AI's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of Fobi AI using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of Fobi AI 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.
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.
When running Fobi AI's price analysis, check to measure Fobi AI'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 Fobi AI is operating at the current time. Most of Fobi AI's value examination focuses on studying past and present price action to predict the probability of Fobi AI's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move Fobi AI's price. Additionally, you may evaluate how the addition of Fobi AI to your portfolios can decrease your overall portfolio volatility.