iPath Series Piotroski F Score

iPath Series B SP GSCI Crude Oil -- USA Etf  

USD 56.28  0.0035  0.0062%

This module uses fundamental data of iPath Series to approximate its Piotroski F score. IPath Series F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of iPath Series B SP GSCI Crude Oil. These three categories are profitability, efficiency, and funding. Some research analysists 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 iPath Series financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Additionally take a look at iPath Series Altman Z Score, iPath Series Correlation, Portfolio Optimization as well as analyze iPath Series Alpha and Beta and iPath Series Hype Analysis
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Analyze Piotroski F Score
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Piotroski F Score -- Inapplicable
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Current Return On Assets
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Cash Flow Return on Assets
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Current Quality of Earnings (accrual)
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Asset Turnover Growth
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Long Term Debt Over Assets Change
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Current Sentiment - OILB

iPath Series B Investor Sentiment
Macroaxis portfolio users are evenly split in their perspective on investing in iPath Series B SP GSCI Crude Oil. What is your take regarding investing in iPath Series B SP GSCI Crude Oil? Are you bullish or bearish?
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About iPath Series F Score

What is iPath Series 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.

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