IShares MSCI Piotroski F Score

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This module uses fundamental data of IShares MSCI to approximate its Piotroski F score. IShares MSCI F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of IShares MSCI Global Impact ETF. 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 IShares MSCI financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Additionally take a look at IShares MSCI Altman Z Score, IShares MSCI Correlation, Portfolio Optimization as well as analyze IShares MSCI Alpha and Beta and IShares MSCI 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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Change in 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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Current Ratio Change
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Long Term Debt Over Assets Change
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Change In Outstending Shares
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9
Change in Gross Margin
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Current Sentiment - SDG

IShares MSCI Global Investor Sentiment

Macroaxis portfolio users are evenly split in their outlook on investing in IShares MSCI Global Impact ETF. What is your judgment towards investing in IShares MSCI Global Impact ETF? Are you bullish or bearish?
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About IShares MSCI F Score

What is IShares MSCI 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.