Experimental NAND Perceptron based upon Python template that aims to predict NAND Gate Outputs. A Perceptron is one of the foundational building blocks of nearly all advanced Neural Network layers and models for Algo trading and Machine Learning.
The goal behind this script was threefold:
To prove and demonstrate that an ACTUAL working neural net can be...
This is a potential solution to dealing with the inherent lag in most filters especially with instruments such as BTC and the effects of long periods of low volatility followed by massive volatility spikes as well as whipsaws/barts etc.
We can try and solve these issues in a number of ways, adaptive lengths, dynamic weighting etc. This filter uses a non linear...
NOTE: Experimental. Pinescript implementation of Decimal to Binary and Binary to Decimal that is intended for use in the development of a neural network proof of concept.
Intended for use in as subcomponent in the development of a more complex/highly experimental prototype.
Protection/logic for edge cases above 11111111/255 (8bits) is NOT implemented.
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...
Calculates VWAP from a fixed point in time as well as standard deviations.
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BTC - 3BMEXEDyWJ58eXUEALYPadbn1wwWKmf6sA
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...