This is an experimental study aimed to find historical patterns of current trend movement.
▶ Derive zigzag pivots based on Length and Source
▶ Based on the Loopback Pivot settings devise a pattern string based on predetermined language which correlates all the pivots within the given range.
▶ Preserve pattern in an array along with bar index
Experimental attemt of applying Logistic Map Equation for some of widly used indicators.
With this study "Awesome Oscillator (AO)", "Rate of Change (ROC)", "Relative Strength Index (RSI)", "Stochastic (STOCH)" and a custom interpretation of Logistic Map Equation is presented
Calculations with Logistic Map Equation makes sense when the calculated results...
zigzag indicator with all the zigzag methods that im aware of(that matter atleast), theres something for all tastes there :P
this will be the basis for zigzag tools i make in the future.
note: some zigzags REPAINT.
This study is an experiment utilizing the Ehlers Gaussian Filter technique combined with lag reduction techniques and true range to analyze trend activity.
Gaussian filters, as Ehlers explains it, are simply exponential moving averages applied multiple times.
First, beta and alpha are calculated based on the sampling period and number of poles specified. The...
For long time I thought that if it's possible to make a script that has own memory and criterias in Pine. it would learn and find patterns as images according to given criterias. after we have arrays of strings, lines, labels I tried and made this experimental script. The script works only for Long positions.
Now lets look at how it...
Italian physicist Galileo Galilei is usually credited with being the first to measure speed by considering the distance covered and the time it takes. Galileo defined speed as the distance covered during a period of time. In equation form, that is v = Δd / Δt where v is speed, Δd is change in distance, and Δt is change in time. The Greek symbol for delta, a...
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...
WARNING: this strategy repaints after reloading and results are heavily curve fitted, use at your own discretion.
UPDATE: (AleksanderThor) add option for a 2nd target, to use you need to activate pyramiding with a setting of 1 manually (not possible to change programatically) .
Bull and Bear power based on linear regression (this is a non lagging oscillator, the parameter are for the lookup window for the donchian extremes)
this indicator can also be used for convergence/divergence.
(accidentjev2) added multi timeframe support (indicator may repaint values)
This is an experimental study designed using data from Bollinger Bands to determine price squeeze ranges and active levels of support and resistance.
First, a set of Bollinger Bands using a Coefficient of Variation weighted moving average as the basis is calculated.
Then, the relative percentage of current bandwidth to maximum bandwidth over the specified sampling...
This is an experimental study designed to identify the underlying trend bias and volatility of an instrument over any custom interval TradingView supports.
First, reset points are established at points where the opening price of the interval changes.
Next, Volume Weighted Average Price (VWAP) is calculated. It is the cumulative sum of typical price times volume...
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 study geared toward identifying price trends using Quadratic regression.
Quadratic regression is the process of finding the equation of a parabola that best fits the set of data being analyzed.
In this study, first a quadratic regression curve is calculated, then the slope of the curve is calculated and plotted.
Custom bar colors are included. The...