Curriculum

This course applies economic concepts and quantitative methods to analyze the economic and financial implications of Fintech. It analyzes the demand and supply drivers of Fintech, economic incentives and determinants of Fintech adoption and formation, the implications of Fintech for the incumbent financial industry, central banking, economic growth, monetary policy, and financial stability. The course highlights the importance of promoting Fintech development and simultaneously ensuring the financial stability.

This course introduces the applications of machine learning for economic and financial analysis. It relates different business problems to the relevant supervised, unsupervised, and reinforcement learning tasks. Topics include valuation of property prices, macroeconomic forecasting, prediction of credit default risk, fraud detection of financial transaction, portfolio analysis, volatility prediction, and trading decision analysis. Students will learn and apply basic machine learning toolsto solve practical economic and financial problems.

This course introduces the art and science of applying and understanding econometric models in the analysis of business strategy. It aims to equip business leaders and strategists to understand and interpret econometric analysis in business strategy analysis, and to provide them with an understanding of three widely used techniques in modern business econometrics: randomized control trials, regression discontinuity, and differences-in-differences. Data analysis in economics, or “econometrics” as it is called by practitioners, has moved away from mathematical complexity and towards simpler tools that are accessible to businesses and can be applied easily to big data. After learning how these tools provide superior analytical results than traditional regression techniques in making inferences about the real world, business strategists will gain the practical knowledge to wield them successfully and make better business strategy decisions with real business data.

Understand real-world importance of monetary policy, financial system stability, and payments system efficiency.

Understand how central banks—the institutions which design and implement these policies—go about doing their work.

This course examines how macroeconomic shocks, policy regimes, and global capital flows transmit into asset prices across foreign exchange, bond, and equity markets. It develops a disciplined macro-to-market framework linking open-economy macroeconomic models to valuation, risk premia, factor rotation, and investment strategy. Core frameworks—including purchasing power parity, interest rate parity, Mundell–Fleming, and exchange rate overshooting—are applied to currency and capital market dynamics, while bond and equity valuation are embedded within macro-financial transmission mechanisms that decompose asset prices into risk-free rates, risk premia, and growth expectations. These macro signals are translated into structured investment processes, including duration positioning, style rotation, factor analysis, and thematic allocation, with particular focus on Asia-Pacific markets. A distinctive feature of the course is the structured and mandatory integration of artificial intelligence as an analytical research and learning infrastructure. Students may use a range of AI tools (including a course-specific NotebookLM resource and other platforms compliant with university policy) to support scenario development, macro-financial dashboards, and simulation exercises, but are required to critically supervise and refine AI-generated outputs using the formal macroeconomic frameworks developed in class. By the end of the course, students should be able to construct internally consistent, macro-driven investment theses suitable for institutional settings and grounded in rigorous economic reasoning.

This course provides an introduction to a wide variety of business cycle models designed to analyze macroeconomic shocks and policy events, with a particular focus on monetary policy. We cover the Real Business Cycle Model (RBC) and we study international business cycles, where results differ between emerging and developing economies, to cover a small open economy RBC model. We then introduce money into the modeling framework with the Money in Utility (MIU) model and the Overlapping Generations Model (OLG) with money. We cover models of imperfect information such as the Lucas island model, nominal rigidity in the canonical New Keynesian DSGE model. We extend this model with financial frictions in the BGG Financial Accelerator model. Key topics in monetary policy such as monetary policy rules, equilibrium determinacy time inconsistency, and reputation are presented. Numerical methods are emphasized and simulation methods taught using DYNARE using a simple “cookbook" approach, to compute the quantitative impact of economic shocks and policy events.

This course presents a modern introduction to international finance and open economy macroeconomics based on a micro-founded, dynamic general equilibrium approach. We will cover basic open economy topics including global imbalances, current account sustainability, theories to explain the current account, determinants of real interest rates, and international capital integration. This course presents data and real-World themes such as the US-China trade war and other contemporary global policy challenges. This course extends students' knowledge of closed economy macroeconomics to the open economy and numerous global finance topics such as the forward premium puzzle, the role of carry trades, providing valuable background for students wishing to enter policy, consulting, investment banking or asset management industries in a global setting.

This course shows you how to value any asset using simple, universal principles. Project cash flows are identified then discounted to reflect their timing and risk. Financial policy supports investment policy by identifying the financial structure that minimizes funding costs. The payout policy is part of the firm’s broader financial policy and can also affect firm value.

This course provides you with an introduction to the most fundamental aspects of modern Portfolio Theory, including both passive portfolio management and active portfolio management. We will start by showing you how to trade on financial exchanges, how to evaluate investment projects with different risk and return characteristics, and how to construct an “optimal” portfolio from a pool of risk-free and risky assets. We will then move on to examine classic topics in asset pricing, studying ways to determine the fair price of financial security given its fundamental risk. We will also cover key methods in equity valuation for active portfolio management, and finally, determine whether a portfolio manager is doing a decent job.

This course provides an introduction to banking and financial intermediation. It aims to enables students to understand (i) banking and financial intermediation as institutional arrangements to overcome some fundamental frictions of an economy, (ii) common practices in financial intermediation, (iii) financial crisis and regulations, and (iv) macroeconomic implications of financial intermediation.

This course is an introduction to an economics perspective of environmental problems, with attention to public policy solutions to pollution and climate change challenges. Part I will cover the ways in which markets fail to efficiently allocate resources in the presence of pollution along with the class of Pigouvian policies used to correct those failures. Part II will focus on the empirical techniques used by economists to assess the cost and benefits of environmental policies.

Housing has its unique characteristics in terms of heterogeneity, durability, and spatial fixity. These suggest that conventional economic concepts need to be readdressed in order to analyze the microeconomic issues of housing. In addition, a significant number of households borrow mortgages to finance their home purchases. A substantial collapse in housing prices might lead to negative equity for leveraged households and reduce their consumption and investment thereafter. The macroeconomic implication of housing market dynamics can be significant to the aggregate economy. The first part of the course focuses on microeconomic issues covering housing demand and supply analysis, models of housing and rental markets, and rationales/effects of public housing policies. The second part emphasizes the macroeconomic issues including the stylized facts on housing market dynamics, causes and consequences of housing market fluctuations, and housing market spillovers. The course objective is to develop analytical framework by which students can address both the microeconomic and macroeconomic issues of housing.

This course covers the basic theory and philosophy of value investing as it has developed since Graham. We will introduce and discuss the styles of important value investors including Graham and Buffett. We will present the basic techniques of investing: search; valuation and the construction of a portfolio. We will use the framework developed in class to study specific companies. This course will only focus on equities.

This course provides an introduction to monetary economics that treats money as the economywide response to some fundmental frictions. Starting from economic theories of money, it aims to enable students to examine (i) different causes for inflation (including fiscal policy and the relationship between debt and inflation), (ii) real effects of inflation (including the output-inflation correlation and wealth redistribution effect), (iii) real and nominal effects of different money injections (including the implication on the nominal interest rate from asset purchasing and the difference between asset-purchasing based injection and helicopter drop), (iv) competition of currencies (including what makes a monetary object, e.g., gold, fiat paper money, CBDC, cryptos, etc., a more acceptable object), and (v) a class of phenomena related to banking, credits and liquidity from monetary perspective.

In this course, students apply the econometric theories and models they've learned to real data. The students must establish their research questions, obtain datasets, analyze the data using the R program, and write their findings in written reports. The course focuses on data analysis with R. The students are expected to have basic knowledge of econometric theories and models, including linear regression, panel data analysis, time series analysis, estimation and hypothesis testing. Students must complete a course project using R.

This course presents a theoretical and empirical analysis of labor markets, utilizing primarily the tools developed in microeconomics and econometrics. We will investigate how wages are determined in the labor market and study the effects of private and public policies on wages and employment. Issues about unemployment, taxation, minimum wage, and monopsony will be studied.

This course has two objectives: 1) to provide basic tools and skills for evaluating public policies in both developed and developing countries, and 2) to learn, through examples, how these tools and skills are actually applied to public policy evaluation. The case studies will focus on human capital development such as health, education, and labor policies.

Asset management continues to be a major growth industry in the global economy. This course will examine developments in the industry, with an emphasis on (a) the main forces at play in the industry, and (b) participants’ responses to the challenges and opportunities that they are facing. We will first describe the main characteristics of the industry at present, exploring the assets that are managed, the main participants in asset management, and the principal investment styles that are employed. We will then consider challenges and opportunities facing the industry and the industry’s evolving response.

This course focuses on ESG (Environmental, Social, and Governance) Investing as it is applied in the asset management industry. We begin by defining ESG, tracing its evolution, and explaining its critical rise in investment management. The curriculum then examines corporate responses to ESG issues and their impact on profits and valuation. The core focuses on the asset management industry, exploring how it integrates ESG through data analytics, passive indexing, factor investing strategies, and active stewardship. We consider how asset managers are incorporating Artificial Intelligence (AI) techniques into ESG Investing, focusing on 1. Materiality and classification and 2. AI as a tool to earn excess returns. Finally, we assess market efficiency, fiduciary duty, and future challenges to ESG Investing.

This course discusses the economics of cities in the context of housing, labor, and transportation. Topics include business and individual location decisions, land use, urban amenities, agglomeration economies, local governance, etc. The course covers empirical methods for urban policy analysis, such as non-parametric estimations, spatial regressiondiscontinuity (RD) designs, the hedonic model, and discrete choice models. This course also discusses advanced general equilibrium models used in contemporary urban literature, including household sorting models, and quantitative spatial models. Students will learn basic tools for the visualization of spatial GIS data, and analytical tools for empirical evaluations of urban policies.

Macroeconomic and financial risk is the likelihood that changes in macroeconomic or financial conditions like interest rates, exchange rates, sovereign credit rating, government policy or regulation, political stability, commodity prices, or equity prices will affect the economic profit or investment return of an entity. For instance, if the central bank tightens monetary policy by increasing interest rates, the cost of borrowing will rise and it will lower profit for a firm which relies on debt financing. The rising interest rates also lower the investment return for bondholders. If a country devalues its currency or defaults on its sovereign debt, creditors or investors from foreign countries will realize investment loss. This course introduces fundamental concepts of macroeconomic and financial risk management. It focuses on identification, quantification, and management of various risks. It evaluates and applies different tools and procedures, comprising quantitative measures and qualitative assessment, to measure and manage risk. Problems and challenges that arise in risk management process are also addressed.

For MSc(ECON) students opting for the Research Preparation concentration only. This course aims to acquire students with research skills through producing a term paper under the supervision of a faculty member in the Department.

Data plays an increasingly important role in business decision making. This course introduces the key concepts and applications of business analytics in the world of Big Data. Example business problems to be solved analytically include customer relationship management, financial trading, social media marketing, search engine strategy, etc. Hands-on experience with popular data analytical tools will be included.

Recent breakthroughs in Large Language Models (LLMs) have made deep-learning-based Natural Language Processing a business imperative, reshaping workflows and decision-making across industries. This course aims to provide a comprehensive introduction to cutting-edge neural approaches for NLP. Students will learn how to design, train, and fine tune models using Python for various business applications such as sentiment analysis, summarization, and conversational AI.