Predicting Market Trends: A Stock Prices Forecasting with Artificial Neural Network

Abstract

Machine learning plays a crucial role in predicting stock prices, as it aids investors in making well-informed decisions amidst the vast array of stocks traded on the stock exchange. The unpredictability of stock price behaviour, influenced by numerous factors, adds complexity to this process. Consequently, numerous studies have explored the use of machine learning for stock price forecasting. However, it is also difficult to predict the behaviour of stock prices due to the uncertainty associated with them. Hence, this study focuses on employing an Artificial Neural Network model as a machine learning algorithm for forecasting stock prices. The model utilizes the daily stock prices of Apple Inc. and Microsoft Corp. gathered from Yahoo Finance. The performance of the model proposed is evaluated using the Root Mean Square Error (RMSE) and Absolute Error (AE) to assess its effectiveness in analyzing the data.