Due to popular request, this is an envelope implementation of my non-repainting Nadaraya-Watson indicator using the Rational Quadratic Kernel. For more information on this implementation, please refer to the original indicator located here: What is an Envelope? In technical analysis, an "envelope" typically refers to a pair of upper and lower bounds that...
Due to public demand Linear Regression Formula Scraped Calculation With Alerts Here is the Linear Regression Script For traders Who love rich features Features ++ Multi time frame -> Source Regression from a different Chart ++ Customized Colors -> This includes the pine lines ++ Smoothing -> Allow Filtered Regression; Note: Using 1 Defaults to the original...
This is an experimental study which calculates a linear regression channel over a specified period or interval using custom moving average types for its calculations. Linear regression is a linear approach to modeling the relationship between a dependent variable and one or more independent variables. In linear regression, the relationships are modeled using...
The tool plots a linear regression line using the entire history of an instrument on chart. There are may be issues on intraday timeframes less then 1h. On daily, weekly and monthly charts it works without problem. If an instrument has a lot of data points, you may not see the line (this is TV feature): To fix that you need to scroll your chart to the left...
Regression trends are typically used to determine when a price is unusually far from its baseline. The script calculates the linear regression of volume and price to determine the trend direction and strength. This can be used to determine the volume support for upward/downward trends. As a special feature, this indicator allows you to choose from three (as of...
This is a study geared toward identifying price trends using Quadratic regression. Quadratic regression is the process of finding the equation of a parabola that best fits the set of data being analyzed. In this study, first a quadratic regression curve is calculated, then the slope of the curve is calculated and plotted. Custom bar colors are included. The...
Calculates a log-log regression from arrays. Due to line limits, for sets greater than the limit, only every nth value is plotted in order to cover the entire set.
A quadratic regression is the process of finding the equation that best fits a set of data.This form of regression is mainly used for smoothing data shaped like a parabola. Because we can use short/midterm/longterm periods we can say that we use a Quadratic Least Squares Moving Average or a Moving Quadratic Regression. Like the Linear Regression (LSMA) a...
Calculates an exponential regression from arrays. Due to line limits, for sets greater than the limit, only every nth value is plotted in order to cover the entire set.
Original implementation idea of bands by: Traders issue: Stocks & Commodities V. 14:9 (375-379): Standard Error Bands by Jon Andersen Standard Error Bands are quite different than Bollinger's. First, they are bands constructed around a linear regression curve. Second, the bands are based on two standard errors above and below this regression line. The...
This indicator was originally developed by Paul Kirshenbaum, a mathematician with a Ph.D. in economics from New York University. It uses the standard error of linear regression lines of the closing price to determine band width. This has the effect of measuring volatility around the current trend, rather than measuring volatility for changes in trend. Good luck!
This indicator was originally developed by Donald Dorsey (Stocks & Commodities, V.13:9 (September, 1995): "Refining the Relative Volatility Index"). Inertia is based on Relative Volatility Index (RVI) smoothed using linear regression. In physics, inertia is the tendency of an object to resist to acceleration. Dorsey chose this name because he believes that trend...
Price Estimator with aggregated linear regresion --------------------------------------------------------------------------- How it works: It uses 6 linear regression from time past to get an estimated point in future time, and using transparency, those areas that are move "visited" by those 6 different regressions and maybe more probable to be visited by the...