This is version 2 of my ANN strategy. This version will not repaint, but requires some settings configuration.
The reason why the old version repainted, is because it used the daily OHLC/4 which kept changing, causing lower timeframes ro repaint.
You can now specify which timeframes to use. The bigger timeframe is set in the settings (e.g. 1 day). You set the...
Hi all, this script was created as a result of ANN training in all time frames of bitcoin data.
Trained data is built on Chris Moody's Sling Shot system.
CM Sling Shot System :
This system automatically generates the ANN output for all time periods.
Therefore, it has multi-time-frame ...
I found a very high correlation in a research-based Artificial Neural Networks.(ANN)
Trained only on daily bars with blockchain data and Bitcoin closing price.
NOTE: It does not repaint strictly during the weekly time frame. (TF = 1W)
Use only for Bitcoin .
Blockchain data can be repainted in the daily time zone according to the description time.
This is a different approach from my original ANN strategy.
This version does 2 ANN predictions and only when they are both in the same direction, a trade will be opened.
When either of them switches, the trade is closed.
This is an implementation of an Artificial Neural Network (ANN) in pine. I made this as part of a bigger project and should be considered more as a proof of concept than a fully working indicator.
It was trained by a different program, using 3 years of bitcoin history. It's a 4 layer ANN that takes the percentual difference of the last few days as input. It was...
NOTE : Deep learning was conducted in a narrow sample set for testing purposes. So this script is Experimental .
This system is based on the following article and is inspired by an external program:
None of the artificial neural networks in Tradingview work and are not based...
Experimental and incomplete.
Script is open to development and will be developed.
This is just version 1.0
This script is trained according to the open, close, high and low values of the bars.
It is tried to predict the future values of opening, closing, high and low values.
A few simple codes were used to correlate expectation...
Hello Traders, I want to share this modified experimental script I´m testing for 1 minute charts... It´s completely based on Sirof´s ANN (Artificial Neural Networks script, Murari´s modification), all the credits are for them (I just tested and switched minor modifications to the code for scalping and alert functions since I have not studied and comprehend the ANN...
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...
Hello, this script consists of training candlesticks with Artificial Neural Networks (ANN).
In addition to the first series, candlesticks' bodies and wicks were also introduced as training inputs.
The inputs are individually trained to find the relationship between the subsequent historical value of all candlestick values 1.(High,Low,Close,Open)
In this script, I tried to fit deep learning series to 1 command system up to the maximum point.
After selecting the ticker, select the instrument from the menu and the system will automatically turn on the appropriate ann system.
Listed instruments with alternative tickers and error rates:
WTI : West Texas Intermediate (WTICOUSD , USOIL , CL1! ) Average...
This is a fractal version of my deep learning script for SPY
In addition, buy and sell conditions may appear in bar colors in green and red.
You can choose from the menu if you wish.
Fractal codes do not belong to me.
So I didn't put any license.
You can use it as you want, you can change and modify.
Hi, this is the MACD version of the ANN BTC Multi Timeframe Script.
The MACD Periods were approximated to the Golden Cross values.
MACD Lengths :
Signal Length = 25
Fast Length = 50
Slow Length = 200
This script aims to establish artificial neural networks with gold data.(4H)
Learning cycles: 329818
Training error: 0.012767 ( Slightly above average but negligible.)
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 300
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
This script was created by training 20 selected macroeconomic data to construct artificial neural networks on the S&P 500 index.
No technical analysis data were used.
The average error rate is 0.01.
In this respect, there is a strong relationship between the index and macroeconomic data.
Although it affects the whole world,I personally recommend using it under...
Logic is correct.
But I prefer to say experimental because the sample set is narrow. (300 columns)
6 inputs : Volume Change , Bollinger Low Band chg. , Bollinger Mid Band chg., Bollinger Up Band chg. , RSI change , MACD histogram change.
1 output : Future bar change (Historical)
Training timeframe : 15 mins (Analysis TF > 4 hours (My...