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...
EXPERIMENTAL: WARNING: highly curve fitted results, if you dont know whats going on stay away.
This study is an experiment built off the framework of my Dual Volume Divergence Index indicator. It is designed to gauge polarity over multiple lookback periods of your choice by expressing the data as a two color grid. Positive Volume Divergence and Negative Volume Divergence are calculated, and their relative values are used to gauge polarity. The order of the...
Experimental. In regular scenario divergence calculation follows these procedure Pivots on price are considered as primary source They are compared with pivots on oscillators Trend bias of price is used This is an experimental version where Pivots on oscillators are considered as primary source They are compared with pivots on price Trend...
EXPERIMENTAL: Double EMA RSI Strategy. Optional: N max orders per day, %equity trade size, Time session constraints, TP, SL, Trailing.
EXPERIMENTAL: Using keltner channels with automatic multiplier finding, offsets and show_last cutoffs to generate a forecast area. video showing why its named keltner worms :p.. streamable.com
This is an experimental study designed to analyze trend intensity using two Donchian Channels. The DCTI curve is calculated by comparing the differences between Donchian highs and lows over a major an minor period, and expressing them as a positive and negative percentage. The curve is then smoothed with an exponential moving average to provide a signal...
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...
EXPERIMENTAL: Swing Charts with a personal touch(has slight modifications) :p
This is a follow on from this script Allows a further breakdown and examination of Sigma spikes by hour of the day or hour of the day & day of the week. For simplicity it MUST be used on H1 chart.
This study is an experiment designed to identify market phases using changes in an approximate Hurst Exponent. The exponent in this script is approximated using a simplified Rescaled Range method. First, deviations are calculated for the specified period, then the specified period divided by 2, 4, 8, and 16. Next, sums are taken of the deviations of each period,...
EXPERIMENTAL: Adaptation from stop hunt levels: Uses timeframe and atr to set ranges.
This is an experimental study designed to identify underlying price activity using a series of Laguerre Filters. Two different modes are included within this script: -Ribbon Mode - A ribbon of 18 Laguerre Filters with separate Gamma values is calculated. -Band Mode - An average of the 18 filters generates the basis line. Then, Golden Mean ATR over the specified...
EXPERIMENTAL: candle version for a RSI script i did for JR.
RSI modified with Jurik's ma as a center point of difference. -added optional calculation to simulate rsi with x length at certain timeframes. -added optional barcolor.
EXPERIMENTAL: Request for IvanLabrie. Method for reading Neo Wave's. note: some issues arent possible to work around/fix due to limitations in pinescript.
This study is an experimental regression curve built around fractal and ATR calculations. First, Williams Fractals are calculated, and used as anchoring points. Next, high anchor points are connected to negative sloping lines, and low anchor points to positive sloping lines. The slope is a specified percentage of the current ATR over the sampling period. The...
Description: A Function that returns a linear regression channel using (X,Y) vector points. Inputs: _X: Array containing x data points.¹ _Y: Array containing y data points.¹ Note: ¹: _X and _Y size must match. Outputs: _predictions: Array with adjusted _Y values at _X. _max_dev: Max deviation from the mean. _min_dev:...