Bangladeshi Stock Price Prediction and Analysis with Potent Machine Learning Approaches Sajib Das, Md. Shohel Arman (B ) , Syeda Sumbul Hossain, Md. Sanzidul Islam, Farhan Anan Himu, and Asif Khan Shakir Department of Software Engineering, Daffodil International University, Dhaka, Bangladesh sshuvo27@gmail.com Abstract. Stock price forecasting, is one of the most significant financial com- plexities, since data are not reliable and noisy, impacting many factors. This article offers a machine learning model for the stock price prediction using Support Vec- tor Machine-Regression (SVR) with two different kernels which are Radial Basis Function (RBF) and linear kernel. This study shows the Prediction and accuracy comparison between Support Vector Regression (SVR) and Linear Regression (LR) and also the accuracy comparison for different kernels of Support vector Regression (SVR). The model has used sum squared error (SSE) to determine the accuracy of each algorithm; which has shown significant improvement than the other studies. This analysis is conducted on the price data of about five years of Grameenphone listed on Dhaka Stock Exchange (DSE). The highest accuracy was found with Linear Regression model in every case with the highest accuracy of about 97.07% followed by SVR (Linear) model and SVR (radial basis function) model with the highest accuracy rate of about 97.06% and 96.82%. In some cases the accuracy of SVR (radial basis function) was higher than SVR (linear). But it was the Linear Regression which had the highest accuracy of all in every case. Keywords: Machine learning · Stock price prediction · Support vector regression · Linear regression 1 Introduction The stock market refers to the selection and exchange of stocks in which common shares of public companies are bought, exchanged and issued. The shares of the company are all shares in which the company’s ownership is split. In proportion to the number of shares in total, a single share of the stock represents fractional ownership. The prices of stocks shift with market forces every day. This means that share prices are changing due to demand and supply. If more people would like to purchase a stock (demand) than sell it (supply), the price will increase. On the other hand, if more people wanted to sell a stock than purchase it, there would be more supply than demand, and the price would fall [1]. In other words the more a stock has been transacted the more is valuable. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020 Published by Springer Nature Switzerland AG 2020. All Rights Reserved T. Bhuiyan et al. (Eds.): ICONCS 2020, LNICST 325, pp. 230–240, 2020. https://doi.org/10.1007/978-3-030-52856-0_18