naive level forecasting of multiple zigzag's based on this principle:
a few functions to generate pseudo random values.
EXPERIMENTAL: Function to generate a normally distributed pseudo random value. if you find that something doesn't add up, please leave a message bellow.
Important ! The indicator is for experimental purpose only, it must not be used as a decisional tool but only as a visual one (like Zig-Zag, Fractal etc). The information this indicator display is uncertain and subject to drastic changes over time. If you have further question feel free to pm me. Introduction Most of the filters you will find are causal,...
This type of moving average was originally developed by Alex Orekhov at his home. This WMA uses previous prices as weights for the new ones. At the moment, this is a highly experimental approach, so don't use it in real trading. The weighting scheme is presented on the chart.
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 an experiment. This is a RSI based on candle high / low instead of close. If the candle is up / green then the high is used. If the candle is down / red then the low is used. Feel free to ask if you have any question.
This is not really a RSI not either a CVD. This is more like an experiment. It's a RSI calculation applied on the CVD script i made () instead of a classic RSI based on candle close. If you have any questions, feel free to ask.
This is an experimental study using z scores of multiple sampling periods to analyze price trends. Z score measures the number of standard deviations price is from its mean. In this study, z scores are calculated over a Fibonacci sequence of sampling periods from 3 to 4181. The scores are then averaged with equal weighting, resulting in a display of long term...
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...
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...
Measures price distance from extremes. Ranging closer to 0 means topping/bottoming (this can stay in this state for a long time), (price near extreme). Can be used to peak trend reversals(will need to keep doing tests with it) EXPERIMENTAL --> Use at your own risk.
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...
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 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...
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,...
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...