The following moving average adapt to the average number of highest high/lowest low made over a specific period, thus adapting to trend strength. Interesting results can be obtained when using the moving average in a MA crossover system or as a trailing support/resistance. Settings Length : Period of the indicator, with higher values returning smoother...

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RedK Slow Smooth Average (RSS_WMA) is based on simple, multi-WMA passes to generate a moving average that sacrifices low-lag and fast responsiveness for the sake of smoothness. This smoothness enables an increased trader ability to visualize and track longer-term trends and removes the noise of smaller, relatively insignificant price...

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So far the most widely used moving average with an adjustable weighting function is the Arnaud Legoux moving average (ALMA), who uses a Gaussian function as weighting function. Adjustable weighting functions are useful since they allow us to control characteristics of the moving average such as lag and smoothness. The following moving average has a simple...

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Hello All, High-Low Index is a breadth indicator based on Record High Percent (RHP). RHP is based on new 52-week highs and new 52-week lows. RHP => 100 * (new highs) / (new highs + new lows). High-Low Index is a 10-day Simple Moving Average of the RHP, which makes it a smoothed version of RHP. You can find many articles about High-Low Index on the...

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Introduction The non-signal version of the absolute strength indicator from fxcodebase.com requested by ernie76 . This indicator originally from mt4 aim to estimate the bullish/bearish force of the market by using various methods. The Indicator Two lines are plotted, a bull line (blue) representing the bullish/buying force and a bear one (red) representing...

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Introduction Back when i started using pine i made a script called periodic channel who aimed to rescale an average correlated sine wave to the price...don't worked very well. So i tried to fix problems induced by the indicator without much success, i had to redo it from scratch while abandoning the idea of rescaling correlated smooth functions to the price, at...

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Cycles represent relatively smooth fluctuations with mean 0 and of varying period and amplitude, their estimation using technical indicators has always been a major task. In the additive model of price, the cycle is a component : Price = Trend + Cycle + Noise Based on this model we can deduce that : Cycle = Price - Trend - Noise The indicators specialized...

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Hello Friend, This is a very simple script for fun to demonstrate the new ability to change the colors of attributes pertaining to the plotbar() and plotcandle() functions using series inputs. For Heiken Ashi lovers, this script does several things. It gives you both bars and hollow candles with Heikin Ashi values - something TV does not currently support. It...

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Today we'll link time series forecasting with signal processing in order to provide an original and funny trend forecasting method, the post share lot of information, if you just want to see how to use the indicator then go to the section "Using The Indicator". Time series forecasting is an area dealing with the prediction of future values of a series by using a...

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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...

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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!

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Introduction This indicator can have a wide variety of usages, and since it is based on exponential averaging then the whole indicator can be made adaptive, thus ending up with a really promising tool. This indicator who can both smooth price and act as a trailing stop depending on user preferences, i tried to make it as reactive, stable and efficient as...

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Introduction Using conditions in filters is a way to make them adapt to those, i already used this methodology in one of my proposed indicators ARMA which gave a really promising adaptive filter, ARMA tried to have a flat response when dealing with ranging market while following the price when the market where trending or exhibiting volatile movements, the...

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Introduction The ability the Kaufman adaptive moving average (KAMA) has to be flat during ranging markets and close to the price during trending markets is what make this moving average one of the most useful in technical analysis. KAMA is calculated by using exponential averaging using the efficiency ratio (ER) as smoothing variable where 1 > ER > 0 . An...

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Mean Reversion and Momentum Interpretation: - Divergence means trend reversal - Parallel movement means trend continuation Squares above serve as a confirming signal

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Old indicator ! But its a simple trick to have a zero-lag smoothing effect, i think i did it because the smoothing was kinda asymmetrical with the detrended line. So even if the result appear quite good take into account that the detrended line isn't always correlated with the price.

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Introduction People often ask me what is my best indicators, i can't really respond to this question with a straight answer but i would say you to check this indicator. The Autonomous Recursive Moving Average (ARMA) is an adaptive moving average that try to minimize the sum of squares thanks to a ternary operator, this choice can seem surprising since most of...

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In general gaussian related indicators are built by using the gaussian function in one way or another, for example a gaussian filter is built by using a truncated gaussian function as filter kernel (kernel refer to the set weights) and has many great properties, note that i say truncated because the gaussian function is not supposed to be finite. In general the...

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