The weights of this moving average are powers of the weights of the standard weighted moving average WMA . Remember: When parameter Power = 0, you will get SMA . When parameter Power = 1, you will get WMA . Good luck!
A derivation of the Kalman Filter. Lower Gain values create smoother results.The ratio Smoothing/Lag is similar to any Low Lagging Filters. The Gain parameter can be decimal numbers. Kalman Smoothing With Gain = 20 For any questions/suggestions feel free to contact me
A One Dimensional Kalman Filter, the particularity of Kalman Filtering is the constant recalculation of the Error between the measurements and the estimate.This version is modified to allow more/less filtering using an alternative calculation of the error measurement. Camparison of the Kalman filter Red with a moving average Black of both period 50 Can...
This indicator was originally developed by Marc Chaikin.
This indicator was originally described by Joseph E. Granville in his book "Granville's New Key To Stock Market Profits" (1963).
Moving Average 3.0 (3rd Generation) script. This indicator was originally developed and described by Dr. Manfred G. Dürschner in his paper "Gleitende Durchschnitte 3.0".
Ehlers Stochastic script. This indicator was originally developed by John F. Ehlers (Stocks & Commodities V. 32:1: Predictive And Successful Indicators).
Ehlers Super Smoother Filter script. This indicator was originally developed by John F. Ehlers (see his book `Cybernetic Analysis for Stocks and Futures`, Chapter 13: `Super Smoothers`).
Ehlers Leading Indicator script. This indicator was originally developed by John F. Ehlers (see his book `Cybernetic Analysis for Stocks and Futures`, Chapter 16: `Leading Indicators`).
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...
Applying a window to the filter weights provides sometimes extra control over the characteristics of the filter.In this script an hamming window is applied to the volume before being used as a weight.In general this process smooth the frequency response of a filter. Lets compare the classic vwma with hamming windowed vwma Something i noticed is that windowed...
Single Exponential Smoothing ( ema ) does not excel in following the data when there is a trend. This situation can be improved by the introduction of a second equation with a second constant gamma . The gamma constant cant be lower than 0 and cant be greater than 1, higher values of gamma create less lag while preserving smoothness.Higher values of length ...
Holt Exponential Moving Average indicator script. This indicator was originally developed by Charles C. Holt (International Journal of Forecasting 20(1):5-10, March 2004: Forecasting seasonals and trends by exponentially weighted moving averages).
A least squares filter using the Auto line as source, practical for noise removal without higher phase shift. Its possible to create another parameter for the auto-line length, just add a parameter Period or whatever you want. r = round(close/round)*round dev = stdev(close,Period) Hope you enjoy :)