This module uses fundamental data of 17 Education to approximate its Piotroski F score. 17 Education F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of 17 Education 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 17 Education financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Check out 17 Education Altman Z Score, 17 Education Correlation, 17 Education Valuation, as well as analyze 17 Education Alpha and Beta and 17 Education Hype Analysis.
17 Education
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
Stock Based Compensation To Revenue
Capex To Depreciation
Pb Ratio
Ev To Sales
Free Cash Flow Per Share
Roic
Inventory Turnover
Net Income Per Share
Days Of Inventory On Hand
Sales General And Administrative To Revenue
Research And Ddevelopement To Revenue
Capex To Revenue
Cash Per Share
Pocfratio
Capex To Operating Cash Flow
Pfcf Ratio
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
Debt To Equity
Capex Per Share
Graham Net Net
Revenue Per Share
Interest Debt Per Share
Debt To Assets
Enterprise Value Over E B I T D A
Price Earnings Ratio
Operating Cycle
Price Book Value Ratio
Price Earnings To Growth Ratio
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
Net Income Per E B T
Cash Ratio
Cash Conversion Cycle
Operating Cash Flow Sales Ratio
Days Of Inventory Outstanding
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
Investments
Change In Cash
Depreciation
Capital Expenditures
Total Cash From Operating Activities
Change To Account Receivables
Net Income
Total Cash From Financing Activities
End Period Cash Flow
Change To Liabilities
Sale Purchase Of Stock
Stock Based Compensation
Free Cash Flow
Change In Working Capital
Begin Period Cash Flow
Total Cashflows From Investing Activities
Other Cashflows From Financing Activities
Other Non Cash Items
Change To Operating Activities
Change To Netincome
Other Cashflows From Investing Activities
Total Assets
Other Current Liab
Total Current Liabilities
Accounts Payable
Cash
Other Assets
Other Current Assets
Total Liab
Common Stock
Property Plant Equipment
Short Long Term Debt Total
Total Stockholder Equity
Other Liab
Net Tangible Assets
Property Plant And Equipment Net
Current Deferred Revenue
Net Debt
Retained Earnings
Non Current Assets Total
Non Currrent Assets Other
Cash And Short Term Investments
Net Receivables
Common Stock Total Equity
Common Stock Shares Outstanding
Short Term Investments
Liabilities And Stockholders Equity
Non Current Liabilities Total
Capital Lease Obligations
Inventory
Other Stockholder Equity
Net Invested Capital
Property Plant And Equipment Gross
Total Current Assets
Accumulated Other Comprehensive Income
Capital Stock
Net Working Capital
Short Term Debt
Net Interest Income
Interest Expense
Selling General Administrative
Total Revenue
Gross Profit
Operating Income
Net Income From Continuing Ops
Ebit
Research Development
Cost Of Revenue
Total Operating Expenses
Income Before Tax
Total Other Income Expense Net
Interest Income
Depreciation And Amortization
Selling And Marketing Expenses
Other Operating Expenses
Ebitda
Reconciled Depreciation
Net Income Applicable To Common Shares
Income Tax Expense
Probability Of Bankruptcy
At this time, 17 Education's Net Debt To EBITDA is relatively stable compared to the past year. As of 02/01/2025, Debt To Equity is likely to grow to 0.04, while Net Debt is likely to drop (349.7 M). At this time, 17 Education's Shareholders Equity Per Share is relatively stable compared to the past year. As of 02/01/2025, Debt To Equity is likely to grow to 0.04, while Free Cash Flow Yield is likely to drop (0.04).
At this time, it appears that 17 Education's Piotroski F Score is Healthy. 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 17 Education is to make sure 17 Education is not a subject of accounting manipulations and runs a healthy internal audit department. So, if 17 Education'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 17 Education'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 17 Education's different financial indicators related to revenue, expenses, operating profit, and net earnings helps investors identify and prioritize their investing strategies towards 17 Education 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.
Pretax Profit Margin
(1.72)
At this time, 17 Education's Pretax Profit Margin is relatively stable compared to the past year.
17 Education Current Valuation Drivers
We derive many important indicators used in calculating different scores of 17 Education from analyzing 17 Education's financial statements. These drivers represent accounts that assess 17 Education's ability to generate profits relative to its revenue, operating costs, and shareholders' equity. Below are some of 17 Education's important valuation drivers and their relationship over time.
The Macroaxis Fundamental Analysis modules help investors analyze 17 Education Technology's financials across various querterly and yearly statements, indicators and fundamental ratios. We help investors to determine the real value of 17 Education using virtually all public information available. We use both quantitative as well as qualitative analysis to arrive at the intrinsic value of 17 Education Technology 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 17 Education 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 17 Education will appreciate offsetting losses from the drop in the long position's value.
The ability to find closely correlated positions to 17 Education could be a great tool in your tax-loss harvesting strategies, allowing investors a quick way to find a similar-enough asset to replace 17 Education 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 17 Education - 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 17 Education Technology to buy it.
The correlation of 17 Education 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 17 Education moves, either up or down, the other security will move in the same direction. Alternatively, perfect negative correlation means that if 17 Education Technology 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 17 Education 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.
When running 17 Education's price analysis, check to measure 17 Education'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 17 Education is operating at the current time. Most of 17 Education's value examination focuses on studying past and present price action to predict the probability of 17 Education's future price movements. You can analyze the entity against its peers and the financial market as a whole to determine factors that move 17 Education's price. Additionally, you may evaluate how the addition of 17 Education to your portfolios can decrease your overall portfolio volatility.