Facebook shows Mean Deviation of 2.13. Facebook technical analysis allows you to utilize historical prices and volume patterns in order to determine a pattern that computes the direction of the firm future prices. 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 Facebook which can be compared to its rivals. Please confirm FacebookVariance, Maximum Drawdown and the relationship between Coefficient Of Variation and Jensen Alpha to decide if Facebook is priced favorably providing market reflects its regular price of 179.53 per share. Given that Facebook has Jensen Alpha of 0.66, we urge you verify Facebook prevailing market performance to make sure the company can sustain itself at future point.
The output start index for this execution was twelve with a total number of output elements of five. 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 Facebook 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.
Facebook Trend Analysis
Use this graph to draw trend lines for Facebook. You can use it to identify possible trend reversals for Facebook 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 Facebook price movement. To start drawing, click on the pencil icon on top-right. To remove the trend, use eraser icon.
Facebook Best Fit Change Line
The following chart estimates an ordinary least squares regression model for Facebook applied against its price change over selected period. The best fit line has a slop of 0.21 % which suggests that Facebook will keep on generating value for investors. It has 34 observation points and a regression sum of squares at 34.56, which is the sum of squared deviations for the predicted Facebook price change compared to its average price change.
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