Linear Regression gives us some abilities to calculate the trend and if we combine it with volume then we may get very good results. Because if there is no volume support at up/downtrends then the trend may have a reversal soon. we also need to check the trend in different periods. With all this info, I developed Volume-Supported Linear...
Multi-timeframe Strategy based on Logistic Regression algorithm
This strategy uses a classic machine learning algorithm that came from statistics - Logistic Regression (LR).
The first and most important thing about logistic regression is that it is not a 'Regression' but a 'Classification' algorithm. The name itself is somewhat misleading....
Introducing the Moving Regression Prediction Bands indicator.
Here I aimed to combine the principles of traditional band indicators (such as Bollinger Bands), regression channel and outlier detection methods. Its upper and lower bands define an interval in which the current price was expected to fall with a prescribed probability, as predicted by the...
Introducing the Pivot Regression Oscillator. This oscillator uses a similar formula to the Stochastic Oscillator. However, instead of comparing the closing price to the lowest price of a period, it compares the distance between current price and the current pivot point. By basing our oscillator on pivot levels, we incorporate a much more relevant and...
Introducing the Delta-RSI Oscillator.
This oscillator is a time derivative of the RSI, plotted as a histogram and serving as a momentum indicator. The derivative is calculated explicitly by means of local polynomial regression. It is designed to provide minimum false and premature buy/sell signals compared to many traditional momentum indicators such as...
Moving Regression is a generalization of moving average and polynomial regression.
The procedure approximates a specified number of prior data points with a polynomial function of a user-defined degree. Then, polynomial interpolation of the last data point is used to construct a Moving Regression time series.
Moving Regression allows one to smooth...
Due to public demand
Linear Regression Formula
Scraped Calculation With Alerts
Here is the Linear Regression Script For traders Who love rich 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...
A function that returns a polynomial regression and deviation information for a data set.
_X: Array containing x data points.
_Y: Array containing y data points.
_predictions: Array with adjusted _Y values.
_max_dev: Max deviation from the mean.
_min_dev: Min deviation from the mean.
Fit a quadratic polynomial (parabola) to the last length data points by minimizing the sum of squares between the data and the fitted results. The script can extrapolate the results in the future and can also display the R-squared of the model. Note that this script is subject to some limitations (more in the "Notes" section).
Length : Number of...
This script is a combination of different logarithmic regression fits on weekly BTC data. It is meant to be used only on the weekly timeframe and on the BLX chart for bitcoin. The "fair value" line is still subjective, as it is only a regression and does not take into account other metrics.
Here is another amazing script for you guys
++ Linear Regression Enthusiasts
Please Use this Indicator If you understand the risk posed by linear regression; ill explain some below
++ Raw Formulae for the linear regression
--I understand that tradingview explanation on how the linreg function works is not clear to...
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...
This is an experimental study designed to calculate polynomial regression for any order polynomial that TV is able to support.
This study aims to educate users on polynomial curve fitting, and the derivation process of Least Squares Moving Averages (LSMAs).
I also designed this study with the intent of showcasing some of the capabilities and potential applications...
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...
This is version 1 of the Linear Regression Slope. In ideal world the Linear regression slope values will remain same for any time period length. because the equation is y = mx+b, where m is the slope. All I did here is m = y/x
The Main Purpose of this indicator is to see, if the Trend is accelerating or decelerating.
The first Blue bar will caution when a...
A Function that returns a linear regression channel using (X,Y) vector points.
_X: Array containing x data points.¹
_Y: Array containing y data points.¹
¹: _X and _Y size must match.
_predictions: Array with adjusted _Y values at _X.
_max_dev: Max deviation from the mean.
This is my first public release of indicator code and my PSv4.0 version of "Linear Regression Channel", as it is more commonly known. It replicates TV's built-in "Linear Regression" without the distraction of heavy red/blue fill bleeding into other indicators. We can't fill() line.new() at this time in Pine Script anyways. I entitled it Linear Regression Trend...