What Linear Regression Channels are? Introduction to LinReg Indi
Linear Regression Channels
A brief info of what Linear Regression Channels are and introduction to Linear Regression Channel / Curve / Slope Indicator Study and one example where Linear Regression Channels are involved with other indicators Pick a Pivot
Brief Info
Linear Regression Channels are useful measure for technical and quantitative analysis in financial markets that help identifying trends and trend direction. The use of standard deviation gives traders ideas as to when prices are becoming overbought or oversold relative to the long term trend
The basis of a linear regression channel
Linear Regression Line – is a line drawn according to the least-squares statistical technique which produces a best-fit line that cuts through the middle of price action, a line that best fits all the data points of interest. The resulting fitted model can be used to summarize the data, to predict unobserved values from the same system. Linear Regression Line then present basis for the channel calculations
The linear regression channel
2. Upper Channel Line – A line that runs parallel to the Linear Regression Line and is usually one to two standard deviations above the Linear Regression Line.
3. Lower Channel Line – This line runs parallel to the Linear Regression Line and is usually one to two standard deviations below the Linear Regression Line.
Unlike Fibonacci Channels and Andrew’s Pitchfork, Linear Regression Channels are calculated using statistical methods, both for the regression line (as expressed above) and deviation channels. Upper and Lower channel lines are presenting the idea of bell curve method, also known as a normal distribution and are calculated using standard deviation function.
A standard deviation include 68% of the data points, two standard deviations include approximately 95% of the data points and any data point that appears outside two standard deviations is very rare.
It is often assumed that the data points will move back toward the average, or regress and channels would allow us to see when a security is overbought or oversold and ready to revert to the mean
please note : Over time, the price will move up and down, and the linear regression channel will experience changes as old prices fall off and new prices appear
█ Linear Regression Study Features
Linear Regression Channel
- Linear regression line as basis
- Customizable multiple channels based on Standard Deviation
- ALERTs for the channel levels
Linear Regression Curve
- Linear regression curve as basis
- Optional : Bands based on Standard Deviation or Volatility (ATR). Bands are applied with fixed levels 1, 2 and 3 times StdDev or ATR away from the curve
Linear Regression Slope
- Optional : Up/Down slope arrows for a used defined period
█ Volume / Volatility Add-Ons
High Volatile Bar Indication
Volume Spike Bar Indication
Volume Weighted Colored Bars
A brief info of what Linear Regression Channels are and introduction to Linear Regression Channel / Curve / Slope Indicator Study and one example where Linear Regression Channels are involved with other indicators Pick a Pivot
Brief Info
Linear Regression Channels are useful measure for technical and quantitative analysis in financial markets that help identifying trends and trend direction. The use of standard deviation gives traders ideas as to when prices are becoming overbought or oversold relative to the long term trend
The basis of a linear regression channel
Linear Regression Line – is a line drawn according to the least-squares statistical technique which produces a best-fit line that cuts through the middle of price action, a line that best fits all the data points of interest. The resulting fitted model can be used to summarize the data, to predict unobserved values from the same system. Linear Regression Line then present basis for the channel calculations
The linear regression channel
2. Upper Channel Line – A line that runs parallel to the Linear Regression Line and is usually one to two standard deviations above the Linear Regression Line.
3. Lower Channel Line – This line runs parallel to the Linear Regression Line and is usually one to two standard deviations below the Linear Regression Line.
Unlike Fibonacci Channels and Andrew’s Pitchfork, Linear Regression Channels are calculated using statistical methods, both for the regression line (as expressed above) and deviation channels. Upper and Lower channel lines are presenting the idea of bell curve method, also known as a normal distribution and are calculated using standard deviation function.
A standard deviation include 68% of the data points, two standard deviations include approximately 95% of the data points and any data point that appears outside two standard deviations is very rare.
It is often assumed that the data points will move back toward the average, or regress and channels would allow us to see when a security is overbought or oversold and ready to revert to the mean
please note : Over time, the price will move up and down, and the linear regression channel will experience changes as old prices fall off and new prices appear
█ Linear Regression Study Features
Linear Regression Channel
- Linear regression line as basis
- Customizable multiple channels based on Standard Deviation
- ALERTs for the channel levels
Linear Regression Curve
- Linear regression curve as basis
- Optional : Bands based on Standard Deviation or Volatility (ATR). Bands are applied with fixed levels 1, 2 and 3 times StdDev or ATR away from the curve
Linear Regression Slope
- Optional : Up/Down slope arrows for a used defined period
█ Volume / Volatility Add-Ons
High Volatile Bar Indication
Volume Spike Bar Indication
Volume Weighted Colored Bars
