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)
The outputs are adapted to the current values with a simple forecast code. Once the OHLC value is found, the exponential moving averages of 5 and 20 periods are used.
Reminder : OHLC = (Open + High + Close + Low ) / 4
Script is designed for S&P 500 Indices,Funds,ETFs, especially S&P 500 Stocks,and for all liquid Stocks all around the World. NOTE: This script is only suitable for 1W time-frame for Stocks.
The average training error rates are less than 5 per thousand for each candlestick variable. (Average Error < 0.005 )
I've just finished it and haven't tested it in detail. So let's use it carefully as a supporter.
Hi, amazing work !
I'm currently trying to learn ANN as well, pretty sure it's a basic question...But how do you iterate your model to find the proper parameters in the activation function ? I guess you have used the gradient propagation method, but how is it possible on TV ?
I'm currently trying to learn ANN as well, pretty sure it's a basic question...But how do you iterate your model to find the proper parameters in the activation function ? I guess you have used the gradient propagation method, but how is it possible on TV ?
Thanks a lot,
Cheers.