Professional Introduction

The Computational Finance major was officially approved for enrollment in 2024 by the Department of Management Science and Engineering, School of Computer Science and Artificial Intelligence, Beijing Technology and Business University. It belongs to the first-level discipline of Management Science and Engineering in the field of management. It is an emerging interdisciplinary major formed by related disciplines such as financial mathematics, management science, and computer science. It is an interdisciplinary major that studies the use of computers to solve financial and management problems such as quantitative trading, programmatic trading, high-frequency trading, and risk management. This major mainly integrates management science, financial mathematics, big data, artificial intelligence, and computer technology to cultivate economic and management innovative talents with computational financial investment thinking and the ability to capture financial market information and changing trends, who systematically master the basic theories of economic management, big data analysis methods, and management skills, and have an innovative spirit, practical ability, and an international perspective.

Training Objectives

This major aims to cultivate high-end compound talents in computational finance to meet the needs of the new era. It closely combines the advantageous resources of our university in financial mathematics, management science, and computer science, focusing on cultivating students' ability to use advanced information technology to solve complex problems in the financial field. Through undergraduate study, students can systematically master relevant knowledge of management science, big data methods, computer theory, artificial intelligence technology, finance, mathematics, and statistics. They can use big data and artificial intelligence technology to solve practical problems in related fields such as financial quantitative trading, the development of financial information systems, financial system modeling and analysis, and risk management, becoming new innovative talents who can adapt to technological progress and the development of the financial industry.

Features and Advantages

With the rapid development of big data and artificial intelligence, the financial industry has entered the stage of computational finance, which is deeply integrated with the Internet, big data, and artificial intelligence. This major is closely combined with advanced technologies such as big data, "Internet +", and artificial intelligence. It takes mathematical knowledge as the foundation, computer technology as the tool, and financial problems as the research object, aiming to cultivate innovative high-end compound management talents for the country who can systematically master the basic theories of economic management, skillfully use mathematical modeling and computer technology for financial data analysis and modeling, financial system development, financial quantitative trading, and financial risk management.

Faculty

The faculty of this major is strong. The professional backgrounds of the teachers cover multiple disciplinary fields such as computer science, management science, mathematics, finance, and systems science, showing an obvious feature of interdisciplinary integration. At present, the teaching team has 31 full-time teachers, including 11 professors. 90% of the teachers have a doctoral degree, and 39% have an overseas background. In the past five years, the team members have undertaken more than 20 national and provincial-level research projects and published more than 200 high-level academic papers in the fields of management science, artificial intelligence, and finance.

Core Courses

Mathematics and Statistics: Mathematical Analysis, Advanced Algebra, Probability Theory and Mathematical Statistics, Discrete Mathematics, Management Statistics, Operations Research, Stochastic Processes in Finance.

Economics and Management: Microeconomics, Macroeconomics, Accounting, Finance, Investment, Econometrics, Financial Mathematics, Principles of Management.

Big Data and Artificial Intelligence: Advanced Python Programming, Algorithms and Data Structures, Database Principles and Applications, Computational Methods, Programming Languages, Computer Networks and Applications, Machine Learning, Introduction to Artificial Intelligence, Financial Modeling and Simulation, Big Data Analysis and Management, Development of Quantitative Strategies and Programmatic Trading.

Practical Teaching

The practical teaching of the Computational Finance major mainly consists of two parts: in-class practice and out-of-class practice. In-class practice refers to laboratory simulation experiments, and out-of-class practice refers to professional internships.

1. Laboratory Simulation Experiments: These include experiments related to modeling and simulation in computational finance, management decision-making models and methods, commercial data analysis and application, enterprise management practice, and the application of project management software. Through simulation, students can have a clear and intuitive understanding of computational finance knowledge, which not only cultivates their practical skills but also deepens their understanding of management basic theories and practical work.

2. Concentrated Practical Teaching: In addition to the experiments distributed in various courses, concentrated practical teaching links such as professional internships, graduation internships, and graduation theses are set up. The major has established cooperative relationships with many enterprises and local government departments. Students can conduct internships in these units to improve their management practice and social adaptability.

Employment and Further Studies

The employment prospects for this major are broad. Graduates can apply for postgraduate studies in majors such as Management Science and Engineering, Big Data Technology and Engineering, Finance, Financial Engineering, Industrial Engineering and Management, and Artificial Intelligence. They can also apply for postgraduate studies in majors such as Management, Data Science, and Accounting in overseas prestigious universities. In addition, they can work in various financial or non-financial institutions, engaging in tasks such as the design and implementation of artificial intelligence algorithms, the design and calculation of fintech products, big data analysis and calculation, financial system development, and quantitative trading.