VelocityShares Piotroski F Score

DGAZ -- USA Etf  

USD 19.50  0.60  2.99%

This module uses fundamental data of VelocityShares to approximate its Piotroski F score. VelocityShares F Score is determined by combining nine binary scores representing 3 distinct fundamental categories of VelocityShares 3x Inv Natural Gas ETN. 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 VelocityShares financial position does not get reflected in the current market share price suggesting a possibility of arbitrage. Additionally see VelocityShares Altman Z Score, VelocityShares Correlation, Portfolio Optimization as well as analyze VelocityShares Alpha and Beta and VelocityShares 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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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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Change In Outstending Shares
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Change in Gross Margin
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Current Sentiment - DGAZ

VelocityShares 3x Inv Investor Sentiment

Most of Macroaxis users are currently bullish on VelocityShares 3x Inv Natural Gas ETN. What is your outlook on investing in VelocityShares 3x Inv Natural Gas ETN? Are you bullish or bearish?
Bullish
Bearish
98% Bullish
2% Bearish
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About VelocityShares F Score

What is VelocityShares 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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