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CARTERA NARANJA (Spain) Technical Analysis

ES0
ES0116405004 -- Spain Fund  

EUR 9.68  0.00  0.00%

As of the 8th of April CARTERA NARANJA shows Coefficient Of Variation of (563.19) and Mean Deviation of 1.93. Macroaxis technical analysis interface gives you tools to check possible technical drivers of CARTERA NARANJA 2080 as well as the relationship between them. Put another way, you can use this information to find out if the entity will indeed mirror its model of historical prices and volume momentum or the prices will eventually revert. We found nineteen technical drivers for CARTERA NARANJA 2080, which can be compared to its rivals. Please confirm CARTERA NARANJA 2080 Jensen Alpha, Maximum Drawdown and the relationship between Information Ratio and Treynor Ratio to decide if CARTERA NARANJA 2080 is priced adequately providing market reflects its regular price of 9.68 per share.
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CARTERA NARANJA 2080 Technical Analysis

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CARTERA NARANJA 2080 Trend Analysis

Use this graph to draw trend lines for CARTERA NARANJA 2080. You can use it to identify possible trend reversals for CARTERA NARANJA as well as other signals and approximate when it will take place. Remember, you need at least two touches of the trend line with actual CARTERA NARANJA price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.

CARTERA NARANJA Best Fit Change Line

The following chart estimates an ordinary least squares regression model for CARTERA NARANJA 2080 applied against its price change over selected period. The best fit line has a slop of   0.09  which may suggest that CARTERA NARANJA 2080 market price will keep on failing further. It has 22 observation points and a regression sum of squares at 1.96, which is the sum of squared deviations for the predicted CARTERA NARANJA price change compared to its average price change.

CARTERA NARANJA April 8, 2020 Technical Indicators

Continue to Investing Opportunities. Please also try Pattern Recognition module to use different pattern recognition models to time the market across multiple global exchanges.
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