The estimation of a least squares moving average of any degree isn't an interesting goal, this is due to the fact that lsma of high degrees would highly overshoot as well as overfit the closing price, which wouldn't really appear smooth. However i proposed an estimate of an lsma of any degree using convolution and a new sine wave series, all the...
The last indicators i posted where about estimating the least squares moving average, the task of estimating a filter is a funny one because its always a challenge and it require to be really creative. After the last publication of the 1LC-LSMA, who estimate the lsma with 1 line of code and only 3 functions i felt like i could maybe make something...
It is possible to use a wide variety of filters for the estimation of a least squares moving average, one of the them being the Kaufman adaptive moving average (KAMA) which adapt to the market trend strength, by using KAMA in an lsma we therefore allow for an adaptive low lag filter which might provide a smarter way to remove noise while preserving...
An adaptive filtering technique allowing permanent re-evaluation of the filter parameters according to price volatility. The construction of this filter is based on the formula of moving ordinary least squares or lsma, the period parameter is estimated by dividing the true range with its highest. The filter will react faster during high volatility periods and...
The fast z-score is a modification of the classic z-score that allow for smoother and faster results by using two least squares moving averages, however oscillators of this kind can be hard to read and modifying its shape to allow a better interpretation can be an interesting thing to do.
I already talked about the fisher transform,...
Its a pretty old script and i have absolutely no idea how i did it, the code kinda look like the phase wrapping/unwrapping formula. This indicator is an oscillator, sometimes its reactivity is impressive so i think its a good idea to post it, feel free to experiment with it.
Quick script made by reusing some functions written for other projects. This is a variation on the least squares moving average, but with custom weights on the linear regression. This gives higher weights to recent values and values with high volume.
Behaves very similarly to my volume weighted Hull moving average, especially with the hull smoothing option turned on.
This is an experimental study that takes a moving average of price, then offsets the average by up to 11 consecutive Fibonacci numbers from 1 to 144.
Choose between Kaufman's Adaptive Moving Average, Hull Moving Average, Fractal Adaptive Moving Average, Geometric Moving Average, or Exponential Moving Average.
This is an experimental study inspired by Goichi Hosoda's Ichimoku Kinkō Hyō.
In this study, a McGinley Dynamic replaces the Tenkan-Sen and Kaufman's Adaptive Moving Average replaces the Kijun-Sen.
The cloud is calculated by taking the mean of the highest high and lowest low, adding a golden mean standard deviation above and below, and offsetting it over the...
I already estimated the least-squares moving average numerous times, one of the most elegant ways was by rescaling a linear function to the price by using the z-score, today i will propose a new smoother (FLSMA) based on the line rescaling approach and the inverse fisher transform of a scaled moving average error with the goal to provide an...
I already mentioned various problems associated with the lsma, one of them being overshoots, so here i propose to use an lsma using a developed and adaptive form of 1st order polynomial to provide several improvements to the lsma. This indicator will adapt to various coefficient of determinations while also using various recursions.
More In Depth...
This study is an experiment based off the concept used in my Dynamic Range Channel indicator.
Rather than using a McGinley Dynamic, a moving average of your choice is used in this calculation.
There are eight different moving average types to choose from in this script:
- Kaufman's Adaptive Moving Average
- Geometric Moving Average
- Hull Moving...
You can choose one of these MA types in params:
Simple Moving Average ( SMA )
Exponential Moving Average ( EMA )
Weighted Moving Average ( WMA )
Arnaud Legoux Moving Average ( ALMA )
Hull Moving Average ( HMA )
Volume-weighted Moving Average ( VWMA )
Least Square Moving Average ( LSMA )
Smoothed Moving Average ( SMMA )
Double Exponential Moving Average (...
The ability to reduce lag while keeping a good level of stability has been a major challenge for smoothing filters in technical analysis. Stability involve many parameters, one of them being overshoots. Overshoots are a common effect induced by low-lagging filters, they are defined as the ability of a signal output to exceed a target input. This...