Abstract:
Abstract – This study investigates the use of machine learning techniques, such as deep neural networks (DNNs) and regression algorithms, for forecasting stock market price of certain stocks in the transportation sector in the Colombo stock exchange. We assess these models' performance using historical stock price data. Our findings will illustrate the benefits and drawbacks of various models and show how machine learning algorithms may be used to forecast stock values. For investors, traders, and financial institutions attempting to make wise choices in the dynamic and ever-changing world of the stock market, this research has significant ramifications. . However, it is important to note that no model or algorithm can predict the future with complete accuracy. There are always risks involved in investing, and it is up to each individual to weigh these risks against potential rewards. Overall, this research highlights the importance of staying informed and educated about the stock market in order to make wise choices and minimize potential losses.
