Stock Market Price Prediction Using Machine Learning

Forecasting stock market returns is challenging due to market dynamics. This study employs Artificial Neural Network and Random Forest algorithms to predict closing prices for five diverse companies. Utilizing financial data, new variables were created as model inputs. Evaluation using RMSE and MAPE metrics shows promising performance, highlighting the efficacy of these models in predicting stock prices . Keywords— Stock market prediction, Artificial Neural Network, Random Forest, Financial data, Closing price forecast, RMSE, MAPE, Computational capabilities, Nonlinear dynamics.