Core Courses

MFTZ01 Introduction to Python Programming for Finance (3 credits)

This course aims to teach the fundamentals of Python programming and its applications in the financial domain. The course content includes basic syntax and data structures in Python programming, acquiring and processing financial data, fundamental statistical analysis, as well as constructing and evaluating simple financial models. Students will learn how to use Python for data analysis and visualization, handle common financial datasets, and implement basic financial algorithms. Through practical projects and case studies, students will be able to apply their knowledge to solve real-world financial problems.

MFTZ02 Machine Learning for Fintech (3 credits)

This course aims to introduce the basic theories of machine learning and its practical applications in the financial industry. The course content covers supervised learning, unsupervised learning, reinforcement learning, deep learning, etc. Students will learn how to apply these machine learning and deep learning techniques for financial data analysis, risk management, portfolio optimization, and trading. The course will also explore the application of machine learning in credit scoring, fraud detection, market forecasting, and reinforcement learning in dynamic trading strategies and portfolio management. Through practical case studies and projects, students will be able to understand and implement specific machine learning solutions in finance.

MFTZ03 Blockchain for Finance (3 credits)

"Blockchain for Finance" is a course designed to explore the transformative impact of blockchain technology on the financial industry. The course provides students with a comprehensive overview of blockchain’s role in redefining traditional financial systems, with a focus on enhancing security, transparency, and efficiency. The curriculum covers foundational cryptography, core principles of blockchain, smart contracts, and decentralized finance (DeFi). Through case studies and practical examples, the course investigates blockchain's applications in banking, payments, asset management, digital currencies, and virtual banks, demonstrating its capacity to drive innovation.

MFTZ04 Financial Data Analysis and Econometrics (3 credits)

Financial data analysis has become increasingly important in the big data era, as it helps individual and institutional investors better understand market trends and manage risks and opportunities. The main objective of this course is to equip students with the fundamental theories and methods of modern financial econometrics, enabling them to construct econometric models based on real-world economic and financial issues and conduct empirical research. Students are required to thoroughly master classical linear regression models, univariate analysis models, multivariate analysis models, generalized autoregressive conditional heteroskedasticity models, and Markov switching models. Students will also moderately understand generalized linear regression models, instrumental variables estimation, and panel data methods; and develop familiarity with cutting-edge developments in financial econometrics.

MFTZ05 FinTech Regulations and Compliance (3 credits)

This course focuses on regulatory and compliance issues in the field of fintech, comprehensively introducing relevant legal frameworks, regulatory requirements, and compliance strategies. The content covers the analysis of global and regional fintech regulatory environments, delves into the major regulatory challenges faced by fintech firms, and explores core topics such as data privacy and protection, Anti-Money Laundering (AML), Combating the Financing of Terrorism (CFT), data governance and ethical issues related to AI applications, and fintech crime monitoring. Students will learn how to build and maintain compliance in a rapidly evolving fintech industry. Additionally, the course examines the impact of emerging technologies such as blockchain and smart contracts on regulation and compliance. Through case studies and project execution, students will gain practical skills to navigate complex regulatory environments.

MFTZ06 Advanced Corporate Finance (3 credits)

Corporate Finance is one of the core areas of financial research, forming the theoretical foundation of finance and underpinning real-world financial phenomena. This course is designed to equip students with a robust theoretical framework for understanding and analyzing key financial issues encountered by modern corporations. Through the study of corporate finance, students will gain insights into the underlying logic driving changes in the financial environment and develop the skills necessary to apply advanced tools and decision-making methodologies to corporate financial challenges. The major topics include advanced valuation techniques, financial forecasting, capital structure and financing decisions, financial derivatives and risk management, short- and long-term financial management, and the impact of modern corporate governance on financial issues.

MFTZ07 Investment Analysis (3 credits)

This course explores the impact and application of fintech to portfolio management, with a focus on how to leverage artificial intelligence and other advanced technologies to optimize investment decision-making and wealth management processes. The course covers the fundamentals of portfolio management, the core concepts of fintech, and the application of artificial intelligence in big data processing and automation. Students will learn how to improve the efficiency of asset allocation, risk management, and performance measurement through fintech tools. Through case studies and practical projects, students will acquire the skills to leverage fintech to achieve efficient asset management in a rapidly changing market environment.

MFTZ08 Cybersecurity and Privacy for Fintech (3 credits)

This course delves into the fundamental theories of financial cybersecurity and their practical applications in the fintech domain. The course content includes the design of secure architectures for financial systems, data encryption techniques, identity verification processes, access control strategies, as well as the identification and defense against cybersecurity threats. Additionally, we will discuss regulatory compliance requirements, privacy protection measures, and response and recovery strategies for security incidents. Students will learn to analyze security risks in financial systems and design and implement comprehensive security solutions to ensure the confidentiality, integrity, and availability of financial data. Through case studies and practical projects, students will acquire critical skills for addressing real-world financial security challenges.

Elective Courses

MFTE01 Quantitative Trading (3 credits)

Quantitative trading has become critical in data-driven and automated financial markets nowadays. This course aims to familiarize students with the fundamental principles and practical applications of quantitative trading, helping students to develop and execute trading strategies using mathematical models, statistical analysis and computer algorithms. The curriculum covers backtesting using historical data, risk management, market microstructure, and the application of cutting-edge machine learning techniques in quantitative trading. Students will learn to predict market trends and price movements with quantitative methods, applying theories to real-world trading scenarios. Furthermore, the course introduces mainstream quant trading platforms and tools, using case studies to help students understand the development and evaluation process of quantitative trading strategies. Additionally, the course cultivates students with a deep understanding of regulatory frameworks and ethical issues in quantitative trading, ensuring compliance with relevant laws and professional standards in practice.

MFTE02 Financial Technology Entrepreneurship (3 credits)

This course explores the theory and practice of entrepreneurship in the field of FinTech, providing students with the knowledge and skills to launch and manage a FinTech startup. Students will learn the essentials of FinTech innovation, entrepreneurial strategies, venture financing, and regulatory challenges. In addition, students will learn how to identify opportunities in the FinTech industry, develop competitive business solutions, and build sustainable businesses. Through real-life projects and case studies, students will learn how to tackle the knowledge, skills and challenges of FinTech entrepreneurship, develop effective marketing strategies and financing plans, and drive business growth.

MFTE03 Special Topic I (Finance) (3 credits)

In the era of digital transformation and technological innovation, financial technology (FinTech) has become a central force driving revolutionary changes in the financial industry. FinTech not only significantly enhances transaction efficiency and security but also pioneers innovative models of financial services. This course focuses on cutting-edge applications in FinTech, covering electronic payment systems, digital currencies, and artificial intelligence applications in finance. It systematically introduces foundational knowledge and technical frameworks of electronic payments, including payment gateways, encryption technologies, payment protocols, and industry standards. The course further examines the concepts, real-world applications, and regulatory challenges of digital currencies, alongside analyzing how artificial intelligence enables automated decision-making and risk management in financial practices. Specifically, through case studies and analyses of academic papers, the course explores the transformative impacts of these technologies on financial institutions and businesses, equipping students with insights into current FinTech trends and guiding master's students in selecting thesis topics. Group presentations and discussions will empower students to apply theoretical knowledge to practical challenges and formulate innovative solutions.

MFTE04 Financial Derivatives (3 credits)

Upon completion of this course, students will acquire a comprehensive understanding of the definition, characteristics, and diverse applications of derivatives within financial markets. They will develop proficiency in the operational principles of various derivatives, including futures, options, forwards, and swaps, and be capable of designing and executing risk management strategies tailored to specific practical requirements. Additionally, students will gain the ability to utilize derivatives effectively for speculation and arbitrage, while assessing potential risks and returns across different market conditions. Through the integration of practical case studies and market analysis, students will be equipped to make informed decisions within complex financial environments, thereby enhancing their professional expertise and market insight.

MFTE05 Database Management Systems (3 credits)

This course covers the fundamental theories of database management and its importance in practical applications. Topics include the design and implementation of relational and non-relational databases, the use of SQL language, and data modeling. The course will also explore database security management and big data processing technologies. Students will learn how to design efficient database structures, manage and optimize database performance, and ensure data security and integrity. Through real-world case studies and projects, students will acquire practical database management skills to solve real-life data management challenges.

MFTE06 Special Topic II (Technology) (3 credits)

This course provides an in-depth exploration of Natural Language Processing (NLP) applications in the FinTech sector, covering both the fundamental theories of NLP and their practical applications in finance. The curriculum encompasses core technologies including natural language understanding, sentiment analysis, text classification, and information extraction. We will focus on specific applications of NLP technologies in the financial industry, such as event detection, anomalous behavior identification, fraud prevention, and fake news detection. Additionally, the course will discuss how sentiment analysis and market emotion analysis can be utilized in stock trading, market monitoring, and regulatory compliance. Through a series of practical case studies and project work, students will master how to deploy and optimize NLP algorithms in FinTech environments to solve complex problems in the financial domain.

MFTE07 Financial Risk Management (3 credits)

Financial risk management plays a crucial role in ensuring the stability and sustainable development of the financial system. This course aims to cultivate students' awareness and identification abilities regarding various risks in financial markets, and their ability to effectively manage these risks. The course covers topics such as market risk, credit risk, liquidity risk, operational risk, the Basel Accords, etc. Students will learn risk quantification and analysis tools, understand the risk management framework of financial institutions and related regulatory policies, and develop and implement effective risk management strategies. Through case studies and relevant training, students will be able to understand and apply the knowledge learned, and enhance their ability to cope with financial risks.

MFTE08 Financial Accounting and Reports (3 credits)

Financial accounting information is widely utilized in risk assessment, capital market analysis, investment analysis, and other areas, serving as a critical informational foundation for financial decision-making by institutions and investors. The primary objective of this course is to enable students to learn and master the fundamental principles of financial accounting, the framework of financial reporting, and its application in analysis. Students are expected to understand the principles of double-entry accounting, the accounting cycle, and the informativeness of financial reports. They should also acquire analytical methods for assessing the quality of corporate assets, capital structure, earnings, and cash flows, as well as comprehend the synergistic effects between accounting and finance.

MFTE09 Financial Markets and Institutions (3 credits)

This course introduces the concepts, structure and innovative financing of financial markets and institutions with topics including financial institutions and financial markets, financial system, money, functions and behavior of interest rates, rational expectation theory, efficient market hypothesis, analysis of financial structure, financial crises in the advanced economies, financial crises in the emerging markets economies, analysis of financial regulations, central bank, money supply processes, tools and conducts of monetary policy, foreign exchange markets, international financial systems, quantity theory, IS curves, monetary policy and aggregate demand curve, analysis of aggregate supply and aggregate demand, monetary policy theory, expected role of monetary policy, and monetary policy transmission mechanism.

MFTE10 Behavioral Finance (3 credits)

Behavioral finance is a discipline that studies how psychological and cognitive biases of investors, market participants, and financial institutions influence financial markets and asset pricing in the decision-making process. This course aims to help students understand how human behavior and psychological processes are integrated with traditional financial theories to reveal financial market phenomena in the real world. Topics in the course typically include fundamental concepts and principles of behavioral finance, investor behavior and psychological biases, market anomalies and asset pricing, and the application of behavioral finance in corporate finance and investment management. By studying behavioral finance, students can gain a deeper understanding of the mechanisms of financial markets and how to apply the theories and methods of behavioral finance in practical investment and financial decision-making.