Macys secures Downside Deviation of 2.16, Mean Deviation of 1.26 and Risk Adjusted Performance of 0.01. In connection with Fundamental Indicators, Macroaxis technical analysis interface lets you check existing technical drivers of Macys as well as the relationship between them. Strictly speaking you can use this information to find out if the firm will indeed mirror its model of past prices or the prices will eventually revert. We found eighteen technical drivers for Macys which can be compared to its peers in the industry. Please verify MacysVariance as well as the relationship between Potential Upside and Kurtosis to decide if Macys is priced some-what accurately providing market reflects its recent price of 35.15 per share. Given that Macys has Treynor Ratio of 0.0, we recommend you check Macys last-minute market performance to make sure the company can sustain itself at future point.
null. 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 Macys 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.
Macys Trend Analysis
Use this graph to draw trend lines for Macys. You can use it to identify possible trend reversals for Macys 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 Macys price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.
Macys Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Macys applied against its price change over selected period. The best fit line has a slop of 0.04 % which may imply that the price for Macys will drop even more. It has 34 observation points and a regression sum of squares at 1.14, which is the sum of squared deviations for the predicted Macys price change compared to its average price change.
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