The use of support vector machine and Naive Bayes algorithms and its combination with risk measure and fuzzy theory in the selection of stock portfolio Danial Mohammadi 1 , Emran Mohammadi 1 , Naeim Shokri 2 , Nima Heidari 3 Received: 21/10/2023 Accepted: 22/12/2023 Extended Abstract Introduction Choosing the right investment portfolio makes people earn more profit by investing in the right fields. Therefore, studying ways to determine the optimal stock portfolio is of great importance and necessity. In recent decades, special attention has been paid to the issue of stock portfolio in financial engineering. Many researchers researched this issue and proposed models to optimize the investment portfolio, in which they tried to improve the previous models. On the other hand, considering that the uncertainty in the future economic conditions plays a key role in financial decisions, especially the issues of stock portfolio selection, stock portfolio optimization techniques should be studied along with risk measurement and contingency planning techniques. Both in the part of classification by machine learning algorithms to separate data and in the part of selecting the optimal basket and portfolio, the research gap can be checked. In the data classification part, methods such as random or random classification have been used so far, in this study artificial intelligence method has been used, and more importantly in the part of selecting and optimizing the capital portfolio. In this study, it is tried to use the ability of neural network (machine learning) to create a relationship between different variables, portfolio using machine learning methods (support vector machine and simple Bayes) as well as value at risk and value at conditional risk and it should be combined with the fuzzy theory, which 1. Department of Financial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran. 2. Department of Economic Development and Planning, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran. (Corresponding Author). n.shokri@modares.ac.ir 3. Department of Industrial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran. How to cite this paper: Mohammadi, D., Mohammadi, E., Shokri, N., & Heidari, N. (2023). The use of support vector machine and Naive Bayes algorithms and its combination with risk measure and fuzzy theory in the selection of stock portfolio. Advances in Finance and Investment, 4(4), 177-206. [In Persian] https://doi.org/10.30495/afi.2023.1995691.1257 Journal of Advances in Finance and Investment Volume 4, Issue 4, 2023 pp. 177-206. Paper type: Research paper