Full-time

This course consists of a series of company visits to prestigious companies in various industries. During the visits, students will have opportunities to gain an in-depth understanding of the characteristics of host companies through participating in onsite tours as well as interacting with the companies’ executives. The objectives of company visits are to establish a link between theory taught in a classroom and actual practical concepts. After the visits, students will be able to combine theoretical knowledge with practical experiences and use this additional knowledge to conduct further industry or company analysis.

The course aims to broaden students’ perspective on many contemporary issues in Chinese financial development and enhance their analytical skills to effectively analyze these issues. Practitioner speakers will work with students on both classroom case presentations and projects. By offering students opportunity to integrate theories with existing finance practices, the course helps students gain practical insights in the latest trends of the financial industry in China.

(*This course is conducted mainly in Chinese in the form of workshops hosted by local financial industry executives.)

This course prepares students to engage in productive and original research in the broad area of finance under the instruction of leading professors.

Over the past several decades, the field of finance has developed a successful paradigm based on the notions that investors and managers were generally rational and the prices of securities were generally “efficient.” In recent years, however, anecdotal evidence as well as theoretical and empirical research has shown this paradigm to be insufficient to describe various features of actual financial markets.

In this course we will use psychology and more realistic settings to guide and develop alternative theories of financial markets. We will examine how the insights of behavioral finance complement the traditional paradigm and shed light on investors' trading patterns, the behavior of asset prices, corporate finance, and various Wall Street institutions and practices.

The objective of this course is to value real companies. We start with the foundations and theories of value and pricing, but we focus on real-world applications. This course is designed for potential investors, investment bankers, traders, business owners and managers who intend to understand the value of real companies. Throughout the semester, we seek to understand how to value small firms and large firms, young firms and matured firms, firms with simple or complex businesses and firms in distress. We will apply finance and accounting concepts taught in other courses to value real companies.

This course introduces basic techniques for modelling and analysing systems in the presence of uncertainty. It will cover probability preliminaries, Martingales, Brownian motions and applications in financial engineering.

This course overviews mergers and acquisitions (M&A) and other changes in corporate control. Topics include the process of M&A, leveraged buyouts, and other forms of corporate restructurings, along with related valuation techniques. In addition, we will discuss the parties involved in M&A and other changes in corporate control, their motives and roles, the causes of these changes in corporate control, and the effects of these changes on firm value and performance.

The Chinese economy has been growing at an unprecedented speed in the past three decades and it is already the world’s second-largest economy. Meanwhile, Chinese financial markets are also developing rapidly as the country’s leadership pushes forward its liberalization process and integration with the rest of the world. This course aims to provide an in-depth coverage of the Chinese financial system, with a focus on its distinct characteristics. The objective is to understand the role provided by the financial system in Chinese economic development, as well as the investment opportunities and risks presented by the system to the outside world.

The course covers financial topics most relevant to newly formed companies, with an emphasis on innovative startups that target large markets and raise outside capital. Includes topics on: (1) valuation, which is the course’s primary theme, underlying all of the topics covered, (2) evaluating business opportunities, which focuses on the underlying economic principles that differentiate large opportunities from small opportunities, (3) funding business opportunities, which covers both identifying a company’s needs and acquiring the capital to finance those needs, and (4) discussing how successful entrepreneurial ventures “exit.”

The course examines banks, insurance companies and investment funds. Topics include the role of intermediation, the part played by banks in the real economy, regulation and management of banks, valuation of financial institutions, the functions and conduct of insurance companies, behavior and management of mutual funds and hedge funds. The course also covers corporate credit analysis, credit scoring modelling as well as the various credit risk management practices.

The course covers quantitative portfolio management techniques and strategies with hands-on computing using Python. It is specially designed for students with a career endeavor in the quantitative asset management field or systematic trading strategies. Topics will include fundamental investment concepts, classical portfolio theories, state-of-the-art smart beta strategies formulation, factors modelling and risk optimization, active portfolio management and design, dynamic hedging etc. Programming and numerical algorithm will be a focus and students are expected to learn and apply Python to real practice problems encountered widely in the industry.

This course introduces the foundations of securities trading and discusses market microstructure and optimal trading strategies. It covers the nature of markets and prices, trading mechanism, market microstructure models, trading costs and optimal trading strategies and high frequency trading.

Financial decisions are made within a broader macroeconomic context. The course topics generally include: why people use financial markets, national income accounts, interest rate and central bank policy, banking, and international capital flows.

The course introduces credit risk modeling and credit derivatives evaluation and management. It covers structural models of default risk, intensity-based modelling, risk structures of interest rates; credit default swaps, CDOs and related products.

This course covers econometrics used in empirical finance. Topics include univariate and multivariate linear models, time series models, parametric and nonparametric models of volatility, risk management models. The course considers applied problems in financial data analysis and makes extensive use of computer-based applications to draw inferences.

This course provides students with an in-depth understanding of financial risks by building mathematical models in order to understand the nature of these risks and to manage them using relevant products and instruments. Topics include market risk such as interest rate risk, credit risk, foreign exchange risk at trade level and portfolio level. The course also covers Value at Risk, liquidity risk and an introduction to bank regulations.

This course emphasizes on the object-oriented analysis techniques, examines economic principles of information systems strategy, and highlights applications of economic and management principles to the unique environment of information services. Various key business activities will be discussed. This course will also explain the importance of business IS controls in contemporary IT governance.

This course combines theory and practice (with most case studies drawn from Chinese capital markets) to explain alternative assets and their investment management knowledge. The course will analyze how to conduct alternative asset allocation from the perspective of institutional investment managers (such as pension funds, endowment funds, family offices, etc.). Through this course, students will learn about the returns, risks, characteristics and investment strategies of classic alternative asset such as hedge funds, private equity funds, real estate and commodities. Meanwhile, they will also understand, as institutional investors, how to allocate alternative assets properly.

(* This course is conducted mainly in Chinese.)

This course presents modelling techniques in optimization that are known as linear programming, integer programming, and nonlinear programming. Applications to managerial decision problems in different industries including finance, accounting, human resources, and marketing will be discussed. Students can model managerial decision problems using spreadsheet optimization, e.g., Excel and Excel Solver.

The course provides the tools necessary to analyze the opportunities and potential competitive threats in commercial Web-based organizations. To quantify and apply the analysis, a particular focus is on valuing Internet companies based on a careful examination of their business model and environment. The course also covers the basic theory of financial intermediation as it applies to online financial service firms. It discusses the impact of a migration to online financial services and the competitive changes created.

This course provides introductory knowledge and systematic training for students to explore the field of machine learning which includes basic concepts, methodologies and application tools. The topics will cover the major tasks and major models, tree based models, deep learning models, and etc. Students choosing this course are expected to have a basic foundation of probability theory, matrix algebra and statistics.

Data visualization is the process used to communicate information clearly in graphical form. Topics covered include overview of the concepts and models used to visualize data, data models, graphical perception, and techniques for visual encoding and interaction, data visualization tools, data visualization projects using business-focused data from sources such as social media, e-commerce, marketing, etc.

This course aims to provide students with the general principles and practices of insurance, with an emphasis on risk analysis. The topics will include the economic theory of insurance, the major types of insurance products, the insurance environment, operations of insurance companies, insurance-related regulations, insurance clauses and related topics. By completion of this course, students will have fundamental knowledge of risk management from insurance product perspective.

In this course, students will develop an understanding of the legal framework and regulatory systems which underlie all business activities, including examination of the basic structure and purpose of actual legal documentation. Moreover, it will introduce basic legal principles that regulate the corporate finance and securities markets. Further, the course will cover legal cases related to asymmetric information, moral hazard, agency problems, and bankruptcy. By completion of this course, students are exposed to the basic legal implications of commercial conduct.

This course provides students with the skills to use predictive analytics and Big Data to make informed decisions in the financial sector. It covers topics such as the Fama and French asset pricing model, event studies, forecasting future earnings, and machine learning and textual analysis. Students will learn SQL coding skills necessary to manipulate large-scale financial databases and build predictive models. The course is a hybrid of a traditional seminar course and a computer science course, and is beneficial for students pursuing a variety of careers in the financial sector.

The course is aimed at introducing and basic learning of  the green bond products and related markets, in respect of the ESG principles, framework, policies, and finance. The course helps to gain understanding of how a green bond is designed, structured, priced and traded, and what the relevant investment characteristics are. The course also combines some basic scientific information and knowledge on climate changes and other environmental issues, as well as on modern corporate ESG practices with actual case studies. The course requires some fundamental knowledge on the bond math and bond market. A good understanding of modern environmental issues and scientific backdrop is also essential.