This sample is implemented by Perceptron, a branch of neural network. Maybe you will ask why not use convolutional NN, which is well-known recently. I think the basic concepts are the same. So, no matter what neural network we are using, our purpose is to make a tool to help us analyze market. And after a long time of practising, we drawed a conclusion that analyzing market is not so sensitive to technical skills. Perceptron is satisfied to help us do that. That’s the reason why we don’t use complicated neural network structure. In addition, for a beginner, the concept of perceptron is easy to understand. We just need to prepare these stuffs below for constructing a neural network:
- The number of layers and the number of neurons for every layer.
- What to input(raw data such as candlestick or indicator).
- The signal to end up training.
After preparing for the struture of neural network, it’s the time to program the EA. The process of developing an EA with AI is simple as well. Please do these things:
- Write two programs. One is for gathering historical data as input parameters and training. The other one is for calculating the new input parameter by the trained NN model to get signals(buy or sell).
- Run the first EA to train the NN model.
- Run the second EA to get signals.
Please check the source codes below as reference: