Valeant Expected to Rise 5-8% on Wednesday Dec. 2
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Posted On: 12/01/2015 10:15:45 PM
Valeant Expected to Rise 5-8% on Wednesday Dec. 2
Based on Linear Regression (line of best fit), VRX is expected to rise another 5-8% on Wednesday.
VRX shares are now heavily Bullish.
In statistics, linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variables) denoted X. The case of one explanatory variable is called simple linear regression.
Most institutional High Frequency Trading platforms are built on it. Linear Regression gives statistical edge to traders.
“Slope” indicator, available at Stock Charts, is based on Linear Regression. Linear regression is the least squares estimator of a linear regression model with a single explanatory variable.
In other words, simple linear regression fits a straight line through the set of n points in such a way that makes the sum of squared residuals of the model (that is, vertical distances between the points of the data set and the fitted line) as small as possible.
Linear Regression has 95% prediction accuracy. Continue reading Technical Analysis in Stock Markets
Based on Linear Regression (line of best fit), VRX is expected to rise another 5-8% on Wednesday.
VRX shares are now heavily Bullish.
In statistics, linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variables) denoted X. The case of one explanatory variable is called simple linear regression.
Most institutional High Frequency Trading platforms are built on it. Linear Regression gives statistical edge to traders.
“Slope” indicator, available at Stock Charts, is based on Linear Regression. Linear regression is the least squares estimator of a linear regression model with a single explanatory variable.
In other words, simple linear regression fits a straight line through the set of n points in such a way that makes the sum of squared residuals of the model (that is, vertical distances between the points of the data set and the fitted line) as small as possible.
Linear Regression has 95% prediction accuracy. Continue reading Technical Analysis in Stock Markets
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