Developing a Stock Prediction System Using Grammatical Evolution

Stocks represent a popular investment model in contemporary markets. However, investing in stocks carries inherent risks, potentially leading to losses when purchased at high prices but sold at significantly lower values. Technical analysis is employed to examine historical stock price behavior in order to predict future price movements. The Grammatical Evolution method has been selected to address this issue, utilizing historical stock price data as input. By constructing a comprehensive grammar in Backus-Naur Form notation, Grammatical Evolution facilitates the exploration of numerous potential predictive models, allowing for a wide range of forecasting possibilities.