This toolkit provides filters and extra functionality for non-repainting Nadaraya-Watson estimator implementations made by @jdehorty. For the sake of ease I have nicknamed it "kreg". Filters include a smoothing formula and zero lag formula. The purpose of this script is to help traders test, experiment and develop different regression lines. Regression lines are...
Library "KernelFunctionsFilters" This library provides filters for non-repainting kernel functions for Nadaraya-Watson estimator implementations made by @jdehorty. Filters include a smoothing formula and zero lag formula. You can find examples in the code. For more information check out the original library KernelFunctions. rationalQuadratic(_src, _lookback,...
This indicator is based on the work of @jdehorty and his amazing Nadaraya-Watson Kernel Envelope, which you can see here: General Description The Nadaraya-Watson Oscillator (NWO) will give the same information as the Nadaraya-Watson Envelope, but as an oscillator off the main chart, by plotting the relationship between price and the Kernel and its bands....
█ OVERVIEW WaveTrend 3D (WT3D) is a novel implementation of the famous WaveTrend (WT) indicator and has been completely redesigned from the ground up to address some of the inherent shortcomings associated with the traditional WT algorithm. █ BACKGROUND The WaveTrend (WT) indicator has become a widely popular tool for traders in recent years. WT was first...
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...
// ENGLISH The problem of the wonderfuls Nadaraya-Watson indicators is that they repainting, @jdehorty made an aproximation of the Nadaraya-Watson Estimator using raational Quadratic Kernel so i used this indicator as inspiration i just added the Upper and lower band using ATR with this we get an aproximation of Nadaraya-Watson Envelope without repainting ...
Library "KernelFunctions" This library provides non-repainting kernel functions for Nadaraya-Watson estimator implementations. This allows for easy substitution/comparison of different kernel functions for one another in indicators. Furthermore, kernels can easily be combined with other kernels to create newer, more customized kernels. Compared to Moving...
This is a combination of the Lux Algo Nadaraya-Watson Estimator and Envelope. Please note the repainting issue. In addition, I've added a plot of the actual values of the current barstate of the Nadaraya-Watson windows as they are computed (lines 92-95). It only plots values for the current data at each time update. It is interesting to compare the trajectory...
What is Nadaraya–Watson Regression? Nadaraya–Watson Regression is a type of Kernel Regression, which is a non-parametric method for estimating the curve of best fit for a dataset. Unlike Linear Regression or Polynomial Regression, Kernel Regression does not assume any underlying distribution of the data. For estimation, it uses a kernel function, which is a...
STD-Filtered, Gaussian-Kernel-Weighted Moving Average is a moving average that weights price by using a Gaussian kernel function to calculate data points. This indicator also allows for filtering both source input price and output signal using a standard deviation filter. Purpose This purpose of this indicator is to take the concept of Kernel estimation and...
This indicator builds upon the previously posted Nadaraya-Watson Estimator. Here we have created an envelope indicator based on kernel smoothing with integrated alerts from crosses between the price and envelope extremities. Unlike the Nadaraya-Watson Estimator, this indicator follows a contrarian methodology. For more information on the Nadaraya-Watson Estimator...
Library "MathStatisticsKernelDensityEstimation" (KDE) Method for Kernel Density Estimation kde(observations, kernel, bandwidth, nsteps) Parameters: observations : float array, sample data. kernel : string, the kernel to use, default='gaussian', options='uniform', 'triangle', 'epanechnikov', 'quartic', 'triweight', 'gaussian', 'cosine', 'logistic',...
The following tool smooths the price data using the Nadaraya-Watson estimator, a simple Kernel regression method. We make use of the Gaussian kernel as a weighting function. Kernel smoothing allows the estimating of underlying trends in the price and has found certain applications in stock prices pattern detection. Note that results are subject to repainting,...
Returns a moving average allowing the user to control the amount of lag as well as the amplitude of its overshoots thanks to a parametric kernel. The indicator displays alternating extremities and aims to provide potential points where price might reverse. Due to user requests, we added the option to display the moving average as candles instead of a solid...
"In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable." from wikipedia.com KDE function with optional kernel: Uniform Triangle Epanechnikov Quartic Triweight Gaussian Cosinus Republishing due to change of function. deprecated script:
"In statistics, kernel density estimation (KDE) is a non-parametric way to estimate the probability density function of a random variable." from wikipedia.com
Introduction Who doesn't like smooth things? I'd like a smooth market price for christmas! But i can't get it, instead its so noisy...so you apply a filter to smooth it, such filters are called low-pass filters, they smooth and its great but they have lag, so nobody really use them, but they are pretty to look at. Its on a childish note that i will introduce...
This is a moving average with a customizable random kernel. You can shape your kernel by selecting your parameters in the settings window. This is not something that is immediately ready to mess with by just applying it on the chart, it is very useful for people who are researching indicators and developing new tools. To see the shape of your kernel you can plug...