Neuro Genetic Expert

This system accepts a comma-separated list of symbols and iterates through them, creating a neural network with training for each symbol. These neural networks take values ​​from price action, Bollinger Bands, MACD, and RSI indicators. The number of neurons for each of the three layers of each network can be configured, and genetic training for the indicator parameters can be set up at specific intervals. Confidence levels for the neurons can be adjusted, and market trend analysis filters can be selected. The system includes incremental lot sizes in case of favorable market activity and drawdown control to prevent the balance from falling below a predetermined level.

The main idea is to optimally adapt the sensitivity of the inputs to the market, so that given these genetically configured and selected inputs, decision-making and learning can take place under the most favorable conditions possible, iterating the adaptation and learning process successively.

External genetic optimization, internal neural learning, thus its evolution.