Predicting VN - Index Value by KNN Algorithm of Machine Learning Tran Kim Toai* VSB-Technical University of Ostrava 17, Listopadu 15/2172, 708 33 Ostrava-Poruba Czech Repulic, tran.kim.toai.st@vsb.cz; Faculty of Economics, No 1 Vo Van Ngan Street, Linh Chieu Ward, Ho Chi Minh University of Technology and Education Vietnam *toaitk@hcmute.edu.vn Bui Tien Thinh Faculty of Economics, No 1 Vo Van Ngan Street, Linh Chieu Ward, Ho Chi Minh University of Technology and Education Vietnam *thinhbt@hcmute.edu.vn Phan-Anh-Huy Nguyen Faculty of Economics HCMC University of Technology and Education Ho Chi Minh city, Vietnam huynpa@hcmute.edu.vn Roman Senkerik Faculty of Applied Informatics, Tomas Bata University in Zlin, T. G. Masaryka 5555, 760 01, Zlin Czech Republic senkerik@utb.cz Abstract—The world has entered the stage of rapid development of technology, especially the fourth industrial revolution with outstanding changes and developments in information technology. Artificial Intelligence (AI) is one of the most mentioned names in this period. AI is part of computer science, developing technology in the direction of automation, self-learning. As a result, it takes a solid knowledge to be able to operate any AI system. There have been many applications of artificial intelligence in the fields of science, technology and economics - finance. From previous decades, the application of algorithms to predict values and variables in economics has been implemented and improved over many different stages. This paper aims to predict VNINDEX value by the application of KNN algorithm machine learning to assess the changes of price indexes and stock variables in general and the VNIndex stock exchange in particular. Research result shows that the outcome of a buy - or - sell decision at the point of view. With a predict signal value of 1, investors should execute buy and sell orders that are advised when predict signal yields -1. Overall, the result indicates that 51% of the stock market price are correctly predicted by the KNN algorithm machine learning. Keywords—machine learning, forecasting, KNN I. INTRODUCTION The world has entered the stage of rapid development of technology, especially the fourth industrial revolution with development of Artificial Intelligence (AI). One of the current trends of technology development is AI – integrated applications that are the foundation of the 4.0 technology revolution. Machine Learning is a part of AI, born from the ability to recognize existing patterns and from theories on computers that can be learned by themselves without programming. Currently, almost every industry that is operating with large amounts of data recognizes the importance of machine learning. There have been many applications of artificial intelligence in the fields of science, technology and economics - finance. From previous decades, the application of algorithms to predict values and variables in economics has been implemented and improved over many different stages. However, there is no paper utilized machine learning to improve the VNindex forecasting. To solve this problem, this study aims to predict vn - index value by the application of machine learning to assess the changes of price indexes and stock variables of VN - Index stock exchange. The purpose of the research is to analyze, evaluate and apply KNN algorithm in predicting VN - Index and stock prices. The authors will attempt to find out the advantages and disadvantages of the algorithm. Through the research, the authors hope to contribute to increasing the accuracy of forecasting the upward-and-downward trend of stock prices, short-term risk prevention, increasing profits. Advances in Economics, Business and Management Research, volume 191 Proceedings of the 3rd Annual International Conference on Public and Business Administration (AICoBPA 2020) Copyright © 2021 The Authors. Published by Atlantis Press International B.V. This is an open access article distributed under the CC BY-NC 4.0 license -http://creativecommons.org/licenses/by-nc/4.0/. 228