This script is inspired from "Vitali Apirine (Stocks & Commodities V.36:5: Adaptive Moving Averages)" and a correction to Dynamic Volume Adaptive Moving Average (MZ DVAMA) . I have used slope filtering in order to adapt trends more precisely for better trades.
Slope adaption makes it better for adaptive moving average to detect trend health;...
This indicator is a functional enhancement to “Ehlers Deviation Scaled Moving Average (EDSMA / DSMA)”. I’ve used Volume Breakout and Volatility for dynamic length adaption and further Slope too for trend evaluation.
EDSMA was originally developed by John F. Ehlers (Stocks & Commodities V. 36:8: The Deviation-Scaled Moving Average).
This indicator is inspired from "Vitali Apirine (Stocks & Commodities V.36:5: Adaptive Moving Averages)" but I have used Volume filtering to in order to adapt trends more precisely for better trades.
Volume adaption makes it better for adaptive moving average to detect trend health; making it easier to make decisions based on market strong...
This indicator uses “Chikou” cross concept of Ichimoku cloud indicator and enhances usage of High/Low data with Volume Breakout and Volatility based dynamic adaption.
I’ve been working on making Moving Averages more adaptive based on Volume Breakout and Volatility but as we know Mas work better on close values. I wanted to create a study...
This study uses Adaptive Moving Average with 1 year of length to plot on all time history Index Calculated by Tradingview . All previous $BTC bear runs bottomed on this curve which makes it important enough. Use this only on " "
AMA length is 1 year
Minor length is 50
Major length is 100
.. 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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This is an experimental adaptive trend following study inspired by Giorgos Siligardos's Reverse Engineering RSI and Tushar S. Chande's Variable Moving Average.
In this study, reverse engineered RSI levels are calculated and used to generate a volatility index for VMA calculation.
First, price levels are calculated for when RSI will equal 70 and 30. The...
This is a follow up to my previous publication of Adaptive HMA+ few months ago, as a mean to provide some kind of initial backtesting tools. Which can be use to explore many possible strategies, optimise its settings to better conform user's pair/tf, and hopefully able to help tweaking your general strategy.
If you haven't read the study or use the indicator,...
The Kaufman Adaptive Moving Average was created by Perry Kaufman and this is a variation of that original formula created by John Ehlers. I have included a side by side with an original script (blue line) done by @HPotter that shows that Ehlers version is slightly more reactive compared to the original version. I have included strong buy and sell signals in...
The Adaptive Stochastic Indicator V1 was created by John Ehlers (Rocket Science For Traders pgs 233-234) and this indicator uses the same calculations to find a cycle period that is then used for both the creation of the stochastic indicator but also for the smoothing to create a double smoothed stochastic indicator. Because it is calculated this way, this...
One challenging issue for beginner traders is to differentiate market conditions, whether or not the current market is giving best possibility to stack profits, as earliest, in shortest time possible, or not.
On intraday, we've seen some big actions by big banks are somewhat can be defined --or circling around-- by HMA 200 . I've been thinking on to make the...
This is an experimental study designed to filter out minor price action for a clearer view of trends.
Inspired by the QQE's volatility filter, this filter applies the process directly to price rather than to a smoothed RSI.
First, a smooth average price range is calculated for the basis of the filter and multiplied by a specified amount.
Next, the filter is...
Another one to add to Ehlers collection.
The MESA Adaptive Moving Average (MAMA) adapts to price movement based on the rate of change of phase as measured by the Hilbert Transform Discriminator. This method features a fast attack average and a slow decay average so that composite average rapidly ratchets behind price changes and holds the average value until the...
Lines are the most widely used figures in technical analysis, this is due to the linear trends that some securities posses (daily log SP500 for example), support and resistances are also responsible for the uses of lines, basically linear support and resistances are made with the assumption that the line connecting two local maximas or minimas will...
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...