ArcelorMittal shows Mean Deviation of 1.98 and Risk Adjusted Performance of 0.01. In respect to Fundamental Indicators, Macroaxis technical analysis interface gives you tools to check existing technical drivers of ArcelorMittal as well as the relationship between them. In plain English you can use this information to find out if the firm will indeed mirror its model of historical prices and volume momentum or the prices will eventually revert. We found nineteen technical drivers for ArcelorMittal which can be compared to its rivals. Please confirm ArcelorMittalMean Deviation, Information Ratio as well as the relationship between Information Ratio and Downside Variance to decide if ArcelorMittal is priced correctly providing market reflects its regular price of 31.33 per share. Given that ArcelorMittal has Jensen Alpha of 0.0, we suggest you validate ArcelorMittal prevailing market performance to make sure the company can sustain itself at future point.
Incorrect Input. Please change your parameters or increase the time horizon required for running this function. The output start index for this execution was zero with a total number of output elements of zero. The Average True Range was developed by J. Welles Wilder in 1970s. It is one of components of the Welles Wilder Directional Movement indicators. The ATR is a measure of ArcelorMittal volatility. High ATR values indicate high volatility, and low values indicate low volatility. View also all equity analysis or get more info about average true range volatility indicators indicator.
ArcelorMittal Trend Analysis
Use this graph to draw trend lines for ArcelorMittal. You can use it to identify possible trend reversals for ArcelorMittal 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 ArcelorMittal price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.
ArcelorMittal Best Fit Change Line
The following chart estimates an ordinary least squares regression model for ArcelorMittal applied against its price change over selected period. The best fit line has a slop of 0.06 % which may indicate that the price for ArcelorMittal will continue to decline. It has 34 observation points and a regression sum of squares at 3.35, which is the sum of squared deviations for the predicted ArcelorMittal price change compared to its average price change.
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