The Mother Of Adaptive Moving Averages was created by John Ehlers (Rocket Science For Traders pgs 182-183) and this is definitely my favorite Ehlers moving average script. This works as a trend indicator and a typical moving average. When the mama is above the fama then the stock is in an uptrend and vice versa. Of course it is also good when the price is above...
Moving average adapting to the strength of the trend, this is made possible by using the square of the vertical-horizontal filter as a smoothing factor. Alerts are included with two different types of conditions available to the user.
Length : Period of the moving average
Src : Input data for the indicator
Alerts : Types of conditions to be used...
The Moving Average Adaptive Q (MAAQ) was authored by Perry Kaufman in the Stocks and Commodities Magazine 06/1995
This is similar to his Kaufman Adaptive Moving Average with a few changes. This is a pretty close moving average which I like quite a bit. Try it and let me know what you think.
Send me a message and let me know what other indicators you would like to see!
Hi, this script comes from the idea that Ricardo Santos' Minkovski Distance Function is transferred to the period as a factor.
Minkowski distance is used as a percentage factor with the help of Relative Strength Index function.
Minkowski Distance Function Script :
And thus an...
This is a deviation scaled moving average original designed by John Ehlers. It is a new adaptive moving average that has the ability to rapidly adapt to volatility in price movement with minimal lag. Because it is so smooth and adapts to the volatility of the market it is by far a really great tool for spotting trend changes
MTF ready adaptive MA using Ehler's IQ IFM ( In Phase - Quadrature Instantaneous Frequency Measurement ).
Ehler's formula is a method of quantitatively measuring the length of a market cycle. In this case it is used to calculate the "optimal" adaptive EMA.
Theoretically the length generated by Ehler's formula could be used in many indicators and it's been placed...
.. chameleon 🎵
Uses Kaufmann's Efficiency Ratio to generate adaptive inputs for Ehler's MAMA/FAMA. Alphas from the Hilbert transform are then used in place for the KAMA calculation.
Original MAMA/FAMA by everget : link
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"You don’t put sunscreen when there is no sun, you don’t use an umbrella when there is no rain, you don’t use a kite when there is no wind, so why would you use a trend following strategy when there is no trend ?"
This is how i start my 4th paper "A New Technical Indicator For Optimal Markets Detection" where i present two new technical...
The correlation oscillator is a technical indicator that measure the linear relationship between the market closing price and a simple increasing line, the indicator is in a (-1,1) range and rise when price is up-trending and fall when price is down-trending. Another characteristic of the indicator is its inherent smoothing which provide a noise...
The Dynamically Adjustable Moving Average (AMA) is an adaptive moving average proposed by Jacinta Chan Phooi M’ng (1) originally provided to forecast Asian Tiger's futures markets. AMA adjust to market condition in order to avoid whipsaw trades as well as entering the trending market earlier. This moving average showed better results than...
@ChartArt got my attention to this idea.
This type of moving average was originally developed by Michael R. Bryant (Adaptrade Software newsletter, April 2014). Mr. Bryant suggested a new approach, so called Variable Efficiency Ratio (VER), to obtain adaptive behaviour for the moving average. This approach is based on Perry Kaufman' idea with Efficiency Ratio...
The biggest challenge for any trader is identifying turning points in price movements. You never know if you’ll end up getting whipsawed out of a trade. Here’s one way to avoid those whipsaws.
Use cross sections of between AMA and KAMA.
Sell: Cross(KAMA, AMA)
Creator of KAMA: Perry Kaufman
Creator of AMA: Vitali Apirine
Coded by: Twitter @borserman
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...