Introduction
Indicator Strips linear regression arbitrarily smooths the price data is the regression result, if projected regression line, and then randomly creates band standard deviations above and below the regression line. First, data based on the selected price, smoothed, using the period and type of moving average. If you prefer not to use any smoothing, the chosen period 1. Then, the data obtained are used to form a regression line that ends in each bar, using the period of regression. Values in each bar may optionally be predicted value determined by the design of the regression line at X bar forward, where X is the projection period (if X = 0, then no prediction will not happen). Then, above and below the regression line can be held strip of standard deviations, based on a specified number of standard deviations and significance of standard deviation, calculated from data in the range of the period of regression.
In its most basic form, without smoothing (Moving Average of period 1) and without the forecast (the forecast period 0), the indicator provides a simple end point of linear regression line, which ensures the end of each bar with a period of regression. This alone provides a good replacement of the rolling average, and in fact identical to the type of moving average of least squares.
Period smoothing (MA), allows you to pre-smooth the data before performing any regression analysis or prediction. For predictive value of a linear regression line, ending at each point, and designed more for X number of bars, where X is the projection period. This is a designed value is then used as a value indicator for this bar.
The bands that performed, using the standard deviation, which varies in time. Standard deviations are calculated in the same way as an indicator for the "linear regression" (see number 23). The standard deviation factor of the options multiplied by the value of standard deviation to determine how far the band will be conducted from the main line.
Oscillator Linear regression is the number of standard deviations the current price of the line of linear regression. A value of 2 means that the price is currently located at 2 standard deviations above the linear regression (using a given period of regression, ending at the bar). Value - 1.5 means that the price is now at a 1.5 standard deviations below the regression line. This function is added as an additional option "Oscillator linear regression to indicator bands of linear regression. Recommended that the oscillator linear regression was built in a separate window below the price chart. Oscillator Linear regression shows how far the current price deviated from the regression trend line in units of standard deviation, or how far the price deviated from the basic trend established by regression analysis (using the term).
The above graph shows the daily candle "Intel Corporation" (INTC). Prognostic line linear regression (LRF) is depicted in black, the upper band of 2 standard deviations, shown in blue, and the lower band shows a red color.
Formula
Smoothed price = Moving Average (Price, Z), where Z - period moving average
(Note: If smoothing is not required (only the price), the period moving average should be set to 1. In this case, the smoothed price is the same as the price.)
The band regression = regression (smoothed price, X) + Slope * Y, where
Z - period moving average
X - the period of regression
Y - the forecast period (if not necessarily equal to 0)
Slope - slope of the regression line
The upper band = band regression + standard deviation (smoothed price, X) * N, where
N - standard deviation (s)
X - the period of regression
Lower band = band regression - standard deviation (smoothed price, X) * N, where
N - standard deviation (s)
X - the period of regression
Oscillator Linear Regression = (Price - Stripe regression / standard deviation (smoothed price, X), where X - the period of regression
The use of graphics programs
. Price - Price data used in calculating the (opening, closing ...).
. Type MA - type smoothing (moving average), which will be applied to regression (simple, exponential ...).
. Period MA - period smoothing (moving average), which is used to regression.
. The period of regression - number of bars that are used in calculating the regression line.
. The forecast period - the mean regression line may optionally be predictive of the future number of bars specified by user. If the prediction is 0, no prediction will not happen. If the forecast period greater than 0, the linear regression line is projected forward to determine the value of the regression for the bar.
. The band regression - Average strip is determined calculating the regression line, using the current bar and previous X-1 bars (X is a period of regression), and the design of the line next to the bar Y (Y is the forecast period), and then by the end point line as the values.
. The top band - band of the standard deviation, held above the regression line. Uses the number of standard deviations below. The standard deviation is calculated over the period of regression.
. Bottom line - the standard deviation band, held below the regression line. Uses the number of standard deviations below. The standard deviation is calculated over the period of regression.
. Standard Deviation (s) - How many standard deviations from the mean regression lines used for the upper and lower bands.
. Oscillator Linear Regression - Oscillator linear regression represents the number of standard deviations the current price of the line of linear regression.
Practical applications
To better understand the practical application of linear regression ?????, below the existing comments trederov who uses this tool in their daily practice.
Trader Stephen Kessler
I really like the bands of linear regression, because they are superimposed on the graph. I use the value of projection 0 (no prediction), the regression between 100 and MA between 1 (no pre-smoothing) at 1 -, 2 -, 3 - and 5-minute charts S & P, to display the likely levels of support and resistance, along with reference points, the usual recent maximum and minimum levels of recovery and Fibonacci. On the lateral market, as shown above, at 1-minute schedule can be very useful for the band, conducted by 2 standard deviations.
Trader Chad Payne
You can create a convenient indicator, which actually shows you how many standard deviations (from the linear regression line) are the current prices. This indicator will be positive when the price is above the regression line and negative when prices are lower. In the following chart shows the parameters set by the indicator and an example of this indicator, which was built in the form of the histogram below the price chart.
The indicator is installed without smoothing (the period of AI = 1), no forecast (the forecast period = 0), and the period of regression = 13.
Significance of -2.3 tells you that prices are currently at 2.3 standard deviations below the regression line (which begins 13 bars ago, and ends at this bar).
Here is an another example of use of the linear regression.
This is a daily schedule of MSFT. For the indicator is used between 13 and 1.5 standard deviations. I also added to the schedule indicator "Paint Bar". Parameters used for the indicator "Paint Bar" shown there. LRFU and LRFL - is respectively the upper and lower bands of linear regression.
As you can see the bars are displayed in black when they closed above the upper band, and blue, when they closed below the lower band.
Indicator Strips linear regression arbitrarily smooths the price data is the regression result, if projected regression line, and then randomly creates band standard deviations above and below the regression line. First, data based on the selected price, smoothed, using the period and type of moving average. If you prefer not to use any smoothing, the chosen period 1. Then, the data obtained are used to form a regression line that ends in each bar, using the period of regression. Values in each bar may optionally be predicted value determined by the design of the regression line at X bar forward, where X is the projection period (if X = 0, then no prediction will not happen). Then, above and below the regression line can be held strip of standard deviations, based on a specified number of standard deviations and significance of standard deviation, calculated from data in the range of the period of regression.
In its most basic form, without smoothing (Moving Average of period 1) and without the forecast (the forecast period 0), the indicator provides a simple end point of linear regression line, which ensures the end of each bar with a period of regression. This alone provides a good replacement of the rolling average, and in fact identical to the type of moving average of least squares.
Period smoothing (MA), allows you to pre-smooth the data before performing any regression analysis or prediction. For predictive value of a linear regression line, ending at each point, and designed more for X number of bars, where X is the projection period. This is a designed value is then used as a value indicator for this bar.
The bands that performed, using the standard deviation, which varies in time. Standard deviations are calculated in the same way as an indicator for the "linear regression" (see number 23). The standard deviation factor of the options multiplied by the value of standard deviation to determine how far the band will be conducted from the main line.
Oscillator Linear regression is the number of standard deviations the current price of the line of linear regression. A value of 2 means that the price is currently located at 2 standard deviations above the linear regression (using a given period of regression, ending at the bar). Value - 1.5 means that the price is now at a 1.5 standard deviations below the regression line. This function is added as an additional option "Oscillator linear regression to indicator bands of linear regression. Recommended that the oscillator linear regression was built in a separate window below the price chart. Oscillator Linear regression shows how far the current price deviated from the regression trend line in units of standard deviation, or how far the price deviated from the basic trend established by regression analysis (using the term).
The above graph shows the daily candle "Intel Corporation" (INTC). Prognostic line linear regression (LRF) is depicted in black, the upper band of 2 standard deviations, shown in blue, and the lower band shows a red color.Formula
Smoothed price = Moving Average (Price, Z), where Z - period moving average
(Note: If smoothing is not required (only the price), the period moving average should be set to 1. In this case, the smoothed price is the same as the price.)
The band regression = regression (smoothed price, X) + Slope * Y, where
Z - period moving average
X - the period of regression
Y - the forecast period (if not necessarily equal to 0)
Slope - slope of the regression line
The upper band = band regression + standard deviation (smoothed price, X) * N, where
N - standard deviation (s)
X - the period of regression
Lower band = band regression - standard deviation (smoothed price, X) * N, where
N - standard deviation (s)
X - the period of regression
Oscillator Linear Regression = (Price - Stripe regression / standard deviation (smoothed price, X), where X - the period of regression
The use of graphics programs
. Price - Price data used in calculating the (opening, closing ...).
. Type MA - type smoothing (moving average), which will be applied to regression (simple, exponential ...).
. Period MA - period smoothing (moving average), which is used to regression.
. The period of regression - number of bars that are used in calculating the regression line.
. The forecast period - the mean regression line may optionally be predictive of the future number of bars specified by user. If the prediction is 0, no prediction will not happen. If the forecast period greater than 0, the linear regression line is projected forward to determine the value of the regression for the bar.
. The band regression - Average strip is determined calculating the regression line, using the current bar and previous X-1 bars (X is a period of regression), and the design of the line next to the bar Y (Y is the forecast period), and then by the end point line as the values.
. The top band - band of the standard deviation, held above the regression line. Uses the number of standard deviations below. The standard deviation is calculated over the period of regression.
. Bottom line - the standard deviation band, held below the regression line. Uses the number of standard deviations below. The standard deviation is calculated over the period of regression.
. Standard Deviation (s) - How many standard deviations from the mean regression lines used for the upper and lower bands.
. Oscillator Linear Regression - Oscillator linear regression represents the number of standard deviations the current price of the line of linear regression.
Practical applications
To better understand the practical application of linear regression ?????, below the existing comments trederov who uses this tool in their daily practice.
Trader Stephen Kessler
I really like the bands of linear regression, because they are superimposed on the graph. I use the value of projection 0 (no prediction), the regression between 100 and MA between 1 (no pre-smoothing) at 1 -, 2 -, 3 - and 5-minute charts S & P, to display the likely levels of support and resistance, along with reference points, the usual recent maximum and minimum levels of recovery and Fibonacci. On the lateral market, as shown above, at 1-minute schedule can be very useful for the band, conducted by 2 standard deviations.Trader Chad Payne
You can create a convenient indicator, which actually shows you how many standard deviations (from the linear regression line) are the current prices. This indicator will be positive when the price is above the regression line and negative when prices are lower. In the following chart shows the parameters set by the indicator and an example of this indicator, which was built in the form of the histogram below the price chart.
The indicator is installed without smoothing (the period of AI = 1), no forecast (the forecast period = 0), and the period of regression = 13.
Significance of -2.3 tells you that prices are currently at 2.3 standard deviations below the regression line (which begins 13 bars ago, and ends at this bar).Here is an another example of use of the linear regression.
This is a daily schedule of MSFT. For the indicator is used between 13 and 1.5 standard deviations. I also added to the schedule indicator "Paint Bar". Parameters used for the indicator "Paint Bar" shown there. LRFU and LRFL - is respectively the upper and lower bands of linear regression.As you can see the bars are displayed in black when they closed above the upper band, and blue, when they closed below the lower band.
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